Split (2)

train · 44.6k rows

paperID stringlengths 36 36	pwc_id stringlengths 8 47	arxiv_id stringlengths 6 16 ⌀	nips_id float64	url_abs stringlengths 18 329	url_pdf stringlengths 18 742	title stringlengths 8 325	abstract stringlengths 1 7.27k ⌀	authors stringlengths 2 7.06k	published stringlengths 10 10 ⌀	conference stringlengths 12 47 ⌀	conference_url_abs stringlengths 16 198 ⌀	conference_url_pdf stringlengths 27 199 ⌀	proceeding stringlengths 6 47 ⌀	taskID stringlengths 7 1.44k	areaID stringclasses 688 values	embedding stringlengths 9.26k 12.5k	umap_embedding stringlengths 29 44
60c93d4e-3838-47dc-84d8-7718a4830cea	noisyhate-benchmarking-content-moderation	2303.10430	null	https://arxiv.org/abs/2303.10430v1	https://arxiv.org/pdf/2303.10430v1.pdf	NoisyHate: Benchmarking Content Moderation Machine Learning Models with Human-Written Perturbations Online	Online texts with toxic content are a threat in social media that might cause cyber harassment. Although many platforms applied measures, such as machine learning-based hate-speech detection systems, to diminish their effect, those toxic content publishers can still evade the system by modifying the spelling of toxic words. Those modified words are also known as human-written text perturbations. Many research works developed certain techniques to generate adversarial samples to help the machine learning models obtain the ability to recognize those perturbations. However, there is still a gap between those machine-generated perturbations and human-written perturbations. In this paper, we introduce a benchmark test set containing human-written perturbations online for toxic speech detection models. We also recruited a group of workers to evaluate the quality of this test set and dropped low-quality samples. Meanwhile, to check if our perturbation can be normalized to its clean version, we applied spell corrector algorithms on this dataset. Finally, we test this data on state-of-the-art language models, such as BERT and RoBERTa, and black box APIs, such as perspective API, to demonstrate the adversarial attack with real human-written perturbations is still effective.	['Dongwon Lee', 'Thai Le', 'Yiran Ye']	2023-03-18	null	null	null	null	['hate-speech-detection']	['natural-language-processing']	[ 1.73788339e-01 5.09211328e-03 3.41011137e-01 1.16466001e-01 -6.18379056e-01 -1.01670861e+00 7.59934604e-01 -4.36888251e-04 -2.64757454e-01 6.09701574e-01 1.92784399e-01 -2.65762657e-01 4.77579981e-01 -7.50343502e-01 -8.82101893e-01 -5.89327991e-01 2.33324081e-01 4.56206724e-02 2.05311492e-01 -5.80697000e-01 3.68447661e-01 3.22570860e-01 -1.10705876e+00 5.88965714e-01 1.04764819e+00 1.47337109e-01 -3.19246650e-01 8.23292315e-01 -3.75347547e-02 8.24028254e-01 -1.58458292e+00 -1.10640395e+00 5.07640243e-01 -4.07303303e-01 -4.30325329e-01 -4.08801615e-01 1.77697837e-01 -4.14844185e-01 -7.50574768e-01 1.54233778e+00 7.24812686e-01 -1.08029060e-01 4.67017949e-01 -1.57821059e+00 -1.38512552e+00 8.11500132e-01 -3.46532583e-01 2.51897573e-01 7.88500190e-01 7.76592314e-01 2.80575931e-01 -5.17710030e-01 6.50117457e-01 1.46007848e+00 2.39840060e-01 9.15908635e-01 -8.48218322e-01 -1.17015243e+00 -1.92658290e-01 -9.91937816e-02 -1.28295982e+00 -4.51200932e-01 7.78318226e-01 -5.99462092e-01 6.07915640e-01 6.40409708e-01 2.09102288e-01 2.14286065e+00 5.32018363e-01 3.89689684e-01 1.06613827e+00 -2.79162496e-01 9.42734778e-02 5.10574639e-01 -4.81652655e-02 4.82389212e-01 3.11083704e-01 2.28719413e-01 -6.56599462e-01 -7.31921971e-01 -7.64244497e-02 5.33756614e-02 -4.61476594e-01 6.00254595e-01 -9.56234813e-01 7.97924578e-01 2.54083902e-01 1.80860147e-01 -1.76731035e-01 -3.63688648e-01 6.52486503e-01 3.22245240e-01 6.09878540e-01 1.00560451e+00 -1.71227485e-01 -1.51492417e-01 -2.64354348e-01 2.42934033e-01 1.04292166e+00 9.14897203e-01 3.90543491e-01 -3.94826718e-02 -5.90664327e-01 6.43986881e-01 -1.85965898e-03 9.76878345e-01 8.38885307e-01 -3.44415009e-01 7.02883363e-01 3.75970244e-01 1.90026209e-01 -1.53443539e+00 1.76479578e-01 -2.74952292e-01 -6.09868228e-01 3.84328142e-02 4.76655632e-01 -5.73970556e-01 -7.64180660e-01 1.45888126e+00 2.61375844e-01 1.83692470e-01 -1.11332759e-01 7.95710981e-01 4.67937827e-01 7.29949832e-01 -6.51272535e-02 -4.83793579e-02 1.06915379e+00 -9.69783306e-01 -9.41927671e-01 -9.67620686e-02 6.76094413e-01 -8.64873230e-01 1.77910185e+00 6.72631562e-01 -6.14211798e-01 -1.49435326e-01 -1.18363321e+00 2.15349808e-01 -9.51348364e-01 -9.09728885e-01 -4.40607481e-02 1.33344555e+00 -4.60700005e-01 7.91244268e-01 -2.22900674e-01 -1.30898193e-01 4.24669415e-01 -1.32352725e-01 -4.41477567e-01 5.07698767e-02 -1.84768951e+00 1.04954851e+00 3.31552476e-02 -3.92285466e-01 -1.21477389e+00 -7.75455892e-01 -5.19447207e-01 -2.33044967e-01 2.37092108e-01 -1.23672217e-01 1.38332474e+00 -9.10275280e-01 -1.40620852e+00 8.74521136e-01 3.22193295e-01 -3.38942975e-01 7.74450243e-01 -2.72121847e-01 -9.12025511e-01 -6.52518794e-02 -4.68012840e-02 -1.04477167e-01 1.32206535e+00 -1.24918938e+00 -5.65788336e-02 -3.81168246e-01 1.62258267e-01 -1.09376304e-01 -1.07087445e+00 6.14831209e-01 4.72905440e-03 -8.88063192e-01 -9.03267086e-01 -8.70273113e-01 1.11223988e-01 -4.20903236e-01 -1.13244259e+00 2.31671616e-01 7.71540105e-01 -9.87158537e-01 1.53750622e+00 -2.28841138e+00 -3.65557849e-01 2.48195201e-01 3.16233307e-01 8.56624484e-01 -3.55500519e-01 7.30418026e-01 -5.12261223e-03 9.78773355e-01 -1.15550995e-01 -3.30912054e-01 7.75399432e-02 -1.77857324e-01 -7.59086192e-01 6.56716347e-01 4.23441827e-03 7.01531708e-01 -9.59980547e-01 -1.43212661e-01 -2.76330560e-01 1.51715443e-01 -4.63510394e-01 3.61256570e-01 -3.70985419e-01 2.25600377e-01 -2.96643406e-01 4.30956721e-01 7.35399842e-01 5.42054117e-01 -6.04645908e-01 3.33394647e-01 2.49188632e-01 2.10972846e-01 -6.41575336e-01 8.85043204e-01 -2.15661079e-01 6.35408640e-01 -2.29909029e-02 -2.08448052e-01 7.74106383e-01 1.73270673e-01 -1.62137941e-01 -6.50886416e-01 3.00636351e-01 -8.78320038e-02 1.94352359e-01 -9.93510664e-01 4.47895467e-01 1.52505543e-02 -2.02549964e-01 6.07612789e-01 -3.36281121e-01 -1.67277306e-02 1.96346562e-04 3.83401930e-01 1.66144836e+00 -5.26649058e-01 7.98153458e-04 2.12149262e-01 4.17225331e-01 -1.54163733e-01 2.82041699e-01 9.82754946e-01 -4.83940244e-01 6.53294384e-01 6.53877318e-01 2.83320043e-02 -1.16593254e+00 -8.61855567e-01 3.10914785e-01 1.21986639e+00 -5.56962267e-02 -7.10024059e-01 -1.35461020e+00 -1.15622854e+00 7.80501887e-02 1.24066627e+00 -6.80505276e-01 -7.73104310e-01 -2.08137229e-01 -4.57036018e-01 1.50347269e+00 -2.36630723e-01 4.51885283e-01 -1.34191954e+00 8.86553377e-02 -8.87936652e-02 5.78437783e-02 -9.30214763e-01 -9.81477022e-01 -4.17710423e-01 1.65912107e-01 -1.08894336e+00 -4.22954708e-01 -2.53575355e-01 5.08187771e-01 2.64185905e-01 5.39079487e-01 3.00840080e-01 -1.35761723e-01 -3.00757252e-02 -8.07594597e-01 -9.41384017e-01 -1.28320038e+00 1.00818656e-01 2.77523041e-01 1.02119826e-01 3.82836640e-01 -4.20207113e-01 -6.03612810e-02 3.59577090e-01 -1.51670921e+00 -3.53979707e-01 1.17789485e-01 3.37017477e-01 -3.85361373e-01 1.56166136e-01 5.14641464e-01 -1.27415323e+00 1.45745349e+00 -6.67013288e-01 -1.03664190e-01 6.05337508e-02 -1.63021058e-01 -1.87425792e-01 1.29731464e+00 -1.07253933e+00 -8.16933453e-01 -5.72688878e-01 -2.59653509e-01 -3.64012927e-01 -2.94765323e-01 3.40078115e-01 -5.24089515e-01 -1.78729054e-02 1.35062659e+00 3.11996073e-01 8.08986127e-02 -5.14860690e-01 4.83324200e-01 1.34265137e+00 2.91714638e-01 -2.11361319e-01 1.56872296e+00 5.72507754e-02 -7.88372874e-01 -8.25862050e-01 -7.60360360e-01 -1.30487233e-01 -1.11086287e-01 -9.37905908e-02 6.15599573e-01 -4.93204176e-01 -5.80748916e-01 1.02326214e+00 -1.48820615e+00 -2.81357318e-01 3.54345202e-01 -7.92364180e-02 7.52078071e-02 6.50825322e-01 -7.27465808e-01 -7.91320443e-01 -5.29502511e-01 -8.48276317e-01 6.32307172e-01 5.65922260e-03 -4.06336188e-01 -5.80210924e-01 2.44239211e-01 5.13428330e-01 6.10845804e-01 4.05670851e-01 9.77929235e-01 -1.44118571e+00 2.06070319e-01 -6.85099959e-01 3.75225157e-01 6.71488702e-01 9.93898734e-02 4.95915174e-01 -1.14487958e+00 -1.79660484e-01 3.37945759e-01 -1.99025124e-01 9.87655595e-02 -7.06756353e-01 1.15679252e+00 -1.04577768e+00 -2.15331450e-01 3.50094616e-01 6.63587034e-01 2.50999719e-01 9.94636059e-01 3.25556606e-01 8.18333268e-01 3.97584617e-01 3.79423529e-01 4.63622361e-01 -2.77774513e-01 4.81479883e-01 5.02867877e-01 1.78295389e-01 2.15028524e-01 -7.86840260e-01 8.49489391e-01 7.11146593e-01 4.98320371e-01 -7.56277084e-01 -9.11739647e-01 -1.08962497e-02 -1.35810280e+00 -1.17207134e+00 -1.58805728e-01 2.07011223e+00 1.09657919e+00 5.25063396e-01 3.12896341e-01 2.80060738e-01 1.18722463e+00 2.38134339e-01 -4.94811058e-01 -7.66680360e-01 -7.81494156e-02 7.24871606e-02 4.88630533e-01 3.67647469e-01 -9.50657487e-01 1.05248833e+00 5.62647581e+00 9.62894678e-01 -1.09557807e+00 3.50704908e-01 4.92694736e-01 -3.04446489e-01 -4.32131022e-01 -4.73037541e-01 -5.56258678e-01 1.09395373e+00 1.17196882e+00 -6.55234933e-01 1.00359225e+00 7.86887825e-01 4.44092482e-01 5.73234975e-01 -9.01534081e-01 7.72335708e-01 5.27722239e-01 -8.84966135e-01 2.20765680e-01 5.55498898e-02 6.16429627e-01 -1.04082614e-01 2.35759363e-01 6.86044991e-01 4.40353841e-01 -1.26637030e+00 6.88746929e-01 4.15727228e-01 4.86719698e-01 -8.82686377e-01 6.39770031e-01 9.81772661e-01 -2.40007043e-02 -9.04879197e-02 -4.31109637e-01 -2.72129178e-01 -1.64046362e-01 7.00963259e-01 -9.10621047e-01 2.03463688e-01 4.06105220e-01 1.64685458e-01 -1.06198549e+00 7.76733279e-01 -6.24128759e-01 7.89372861e-01 2.57752594e-02 -4.73391861e-01 3.04739922e-03 2.39959601e-02 8.20663631e-01 1.12556422e+00 1.36040360e-01 -1.42421782e-01 -2.63361484e-01 9.32536662e-01 -5.06811500e-01 1.64098948e-01 -1.30851281e+00 -7.17159927e-01 7.88739145e-01 1.19310415e+00 3.44693139e-02 -2.45263912e-02 -1.86765715e-01 1.26249504e+00 4.45657402e-01 4.26696539e-01 -1.28789628e+00 -7.32208908e-01 8.55886519e-01 3.29472780e-01 -5.64472020e-01 -8.47454891e-02 5.89301810e-02 -1.14247954e+00 9.80348811e-02 -1.71203661e+00 -1.90271344e-02 -8.17824900e-01 -1.74003351e+00 5.68343222e-01 -3.43053490e-01 -9.43478644e-01 1.13088496e-01 -3.54427993e-01 -7.92527914e-01 9.60606873e-01 -5.54843247e-01 -7.35902131e-01 -1.24589637e-01 5.12727201e-01 3.49909872e-01 -4.18918520e-01 7.67363012e-01 3.32572818e-01 -1.01501095e+00 1.06759548e+00 -6.25900785e-03 6.42257333e-01 1.10882223e+00 -8.56030524e-01 7.70841479e-01 1.17527306e+00 -4.50470336e-02 9.69589055e-01 9.29600239e-01 -1.17644882e+00 -1.33415914e+00 -1.22474253e+00 6.19507611e-01 -9.24577296e-01 9.75675821e-01 -9.87767220e-01 -1.12739718e+00 6.70227647e-01 4.10859674e-01 -2.67130256e-01 8.69220078e-01 -3.97632301e-01 -5.34622669e-01 3.16535622e-01 -1.50758934e+00 1.20628381e+00 1.12249684e+00 -7.52052963e-01 -5.95401943e-01 7.61235118e-01 1.39017296e+00 -3.73828292e-01 -3.83296221e-01 -1.38684094e-01 1.50577173e-01 -7.91031778e-01 6.26754999e-01 -1.29924881e+00 8.17503870e-01 -1.77873343e-01 1.51285514e-01 -1.69577885e+00 -2.96377957e-01 -1.17326999e+00 -7.07425177e-02 1.71151328e+00 4.90621656e-01 -8.85820389e-01 3.11975151e-01 7.43520021e-01 4.94537503e-02 -2.65899688e-01 -5.88263512e-01 -9.05250251e-01 3.58619362e-01 -2.75644213e-01 7.55569160e-01 1.32721150e+00 2.59978265e-01 2.09412411e-01 -4.50805575e-01 3.85327667e-01 3.52258474e-01 -9.35635924e-01 1.18146789e+00 -4.85296458e-01 -1.48606196e-01 -2.54801869e-01 -1.96701005e-01 -2.71335065e-01 4.28285211e-01 -1.00103736e+00 -5.73228067e-03 -6.61905706e-01 2.00677365e-01 1.57279059e-01 6.13578297e-02 3.02640051e-01 -5.74482799e-01 2.79911697e-01 3.57197344e-01 2.88269557e-02 -3.11598301e-01 4.95830834e-01 1.16429448e+00 -2.68828094e-01 3.99467684e-02 -3.57258134e-02 -9.66879308e-01 6.77117407e-01 9.57469761e-01 -1.10109890e+00 -2.74316519e-01 -1.41894147e-01 3.98123801e-01 -4.51030940e-01 2.27987736e-01 -8.77113402e-01 7.28207752e-02 -3.14403594e-01 -2.50751898e-02 7.55779743e-02 -1.27279803e-01 -4.64169979e-01 -1.54600188e-01 4.88529414e-01 -5.97533584e-01 2.28098795e-01 -6.50971457e-02 4.98192549e-01 1.93194583e-01 -4.94838387e-01 8.08717847e-01 -7.27513060e-02 9.80131924e-02 3.75641078e-01 -7.44257629e-01 4.54589307e-01 1.26533306e+00 1.34894252e-01 -1.01722229e+00 -6.33728504e-01 -2.08269700e-01 -1.36812821e-01 7.86569655e-01 7.06589222e-01 4.65517879e-01 -1.09595168e+00 -8.71261775e-01 1.36449486e-01 2.10906565e-01 -6.57789290e-01 -3.84963974e-02 3.24695557e-01 -6.47954524e-01 -1.04198769e-01 -1.44536821e-02 1.48163542e-01 -1.31180263e+00 1.28109884e+00 2.78753430e-01 2.10376494e-02 -3.33725214e-01 6.72686636e-01 -1.37056991e-01 -6.83090985e-01 2.69083858e-01 1.99809194e-01 1.63425162e-01 -3.40401798e-01 9.32986259e-01 4.53160673e-01 -1.12628308e-03 -4.83122468e-01 -4.15656090e-01 -3.06322068e-01 -8.23005661e-02 -4.35647815e-02 7.08053350e-01 2.70813316e-01 -1.86435252e-01 2.06811234e-01 1.40994191e+00 6.75359070e-01 -7.17633665e-01 -4.50316211e-03 -6.85797557e-02 -7.94835806e-01 -5.69199860e-01 -9.90368068e-01 -6.59345031e-01 5.76495826e-01 1.73182815e-01 7.65966356e-01 5.39722264e-01 -4.81900811e-01 9.73740399e-01 4.60999250e-01 1.44133449e-01 -8.44341457e-01 5.35062432e-01 7.22414136e-01 1.22001135e+00 -9.99773026e-01 -3.51935297e-01 -4.90967393e-01 -7.47940838e-01 6.30504251e-01 7.59698212e-01 -6.11102507e-02 4.35495526e-01 4.16737825e-01 3.58875364e-01 1.39062122e-01 -6.83136344e-01 4.00743395e-01 -5.72364740e-02 9.51555729e-01 1.13470823e-01 9.10442173e-02 -2.73568779e-01 8.87974739e-01 -8.88401449e-01 -4.01866198e-01 9.77568567e-01 6.22715473e-01 -1.98639229e-01 -9.41138923e-01 -7.15638697e-01 3.82205039e-01 -7.79199004e-01 -2.85835117e-01 -1.16088390e+00 6.36042297e-01 4.47428748e-02 1.45490515e+00 -5.05456805e-01 -9.79306519e-01 5.76779068e-01 7.32144117e-02 1.43015804e-02 -9.46240723e-01 -1.26197875e+00 -6.53273404e-01 3.60316753e-01 -4.53122824e-01 6.13538027e-01 -2.87318766e-01 -8.47126842e-01 -8.69237006e-01 -2.93084621e-01 4.75604497e-02 6.04387283e-01 9.38318014e-01 4.34562236e-01 3.36675346e-01 9.87435341e-01 -5.44216573e-01 -1.12344205e+00 -1.43055630e+00 -4.99856710e-01 1.31585431e+00 1.23907730e-01 -1.95886344e-01 -9.30146158e-01 -1.19535133e-01]	[5.997866153717041, 8.07761001586914]
1bcf2347-b687-4752-8c44-4bca44aebc84	imojie-iterative-memory-based-joint-open	2005.08178	null	https://arxiv.org/abs/2005.08178v1	https://arxiv.org/pdf/2005.08178v1.pdf	IMoJIE: Iterative Memory-Based Joint Open Information Extraction	While traditional systems for Open Information Extraction were statistical and rule-based, recently neural models have been introduced for the task. Our work builds upon CopyAttention, a sequence generation OpenIE model (Cui et. al., 2018). Our analysis reveals that CopyAttention produces a constant number of extractions per sentence, and its extracted tuples often express redundant information. We present IMoJIE, an extension to CopyAttention, which produces the next extraction conditioned on all previously extracted tuples. This approach overcomes both shortcomings of CopyAttention, resulting in a variable number of diverse extractions per sentence. We train IMoJIE on training data bootstrapped from extractions of several non-neural systems, which have been automatically filtered to reduce redundancy and noise. IMoJIE outperforms CopyAttention by about 18 F1 pts, and a BERT-based strong baseline by 2 F1 pts, establishing a new state of the art for the task.	['Soumen Chakrabarti', 'Mausam', 'Keshav Kolluru', 'Vipul Rathore', 'Samarth Aggarwal']	2020-05-17	imojie-iterative-memory-based-joint-open-1	https://aclanthology.org/2020.acl-main.521	https://aclanthology.org/2020.acl-main.521.pdf	acl-2020-6	['open-information-extraction']	['natural-language-processing']	[ 2.56423920e-01 8.74212444e-01 -8.37692060e-03 -1.12951092e-01 -1.03593814e+00 -8.04034352e-01 5.76922178e-01 1.98514476e-01 -4.76030499e-01 1.26880753e+00 4.33206737e-01 -1.48233518e-01 3.59083340e-02 -8.58060479e-01 -1.04769301e+00 -6.04373962e-02 4.59846994e-03 6.24875426e-01 -1.22392969e-02 -2.50668883e-01 -1.01547353e-02 -1.65402459e-03 -1.31747401e+00 6.30490184e-01 1.07451952e+00 9.39657390e-01 4.95794043e-02 9.38033342e-01 -5.26922047e-01 6.89621270e-01 -9.04906511e-01 -9.09887493e-01 3.74782592e-01 -2.83913195e-01 -1.06911671e+00 -5.65276325e-01 5.96171141e-01 -2.98952997e-01 -2.43244335e-01 9.06076610e-01 4.70499039e-01 -1.20930590e-01 8.62042189e-01 -1.04755414e+00 -1.10154259e+00 1.43654513e+00 -2.17522278e-01 2.27249995e-01 3.30142111e-01 1.12782829e-01 1.42279553e+00 -1.14270782e+00 1.27565122e+00 1.00327229e+00 7.01430619e-01 5.58178365e-01 -1.26287758e+00 -7.55098641e-01 2.45629162e-01 -9.78488028e-02 -1.10335207e+00 -6.07476413e-01 2.03850627e-01 -2.15484276e-01 1.79074001e+00 1.81947693e-01 5.38147449e-01 1.57606208e+00 2.68987507e-01 1.39362991e+00 7.32573688e-01 -5.91689885e-01 1.30592212e-01 1.28970623e-01 6.59438312e-01 4.49290782e-01 7.73322642e-01 1.48832155e-02 -9.09569919e-01 1.10149374e-02 4.92408156e-01 -4.58548009e-01 -2.08668783e-01 1.48170501e-01 -1.13395166e+00 6.86776578e-01 4.32454020e-01 3.65985602e-01 -6.62030220e-01 -9.68313441e-02 5.36455631e-01 4.34698999e-01 6.49757683e-01 1.21525419e+00 -9.93320465e-01 -3.49173635e-01 -8.72695029e-01 7.02834189e-01 1.39773107e+00 1.51919520e+00 6.16503596e-01 -2.18586504e-01 -6.87264860e-01 5.67286909e-01 -7.26931468e-02 3.62599850e-01 5.80882609e-01 -7.29762018e-01 9.65086520e-01 4.41941321e-01 2.20585763e-02 -6.29154801e-01 -3.26763779e-01 -5.54889679e-01 -5.69830120e-01 -3.10876489e-01 4.21971679e-01 -7.65799165e-01 -9.87488270e-01 1.65352237e+00 -1.22562371e-01 -3.44768465e-01 4.34793830e-01 2.88498431e-01 1.17798424e+00 5.41584253e-01 2.37916261e-02 -1.39744774e-01 1.14425480e+00 -1.12132514e+00 -1.13775289e+00 -4.37349796e-01 6.76994920e-01 -3.61923069e-01 7.73225367e-01 8.07100117e-01 -1.19098377e+00 -2.46645480e-01 -1.17914271e+00 -4.70676333e-01 -8.14547420e-01 2.88975425e-02 7.04172850e-01 3.99927646e-01 -1.02950048e+00 7.39033103e-01 -5.13328969e-01 -1.04364403e-01 6.54710174e-01 1.88133165e-01 -4.71782029e-01 2.34984279e-01 -1.52877092e+00 9.29728746e-01 9.20097470e-01 3.81269865e-02 -4.37989503e-01 -9.19626057e-01 -1.02157199e+00 2.54949272e-01 7.64064431e-01 -8.82423520e-01 1.65344393e+00 -4.09298033e-01 -1.20760083e+00 4.21218723e-01 -3.35501254e-01 -8.46491694e-01 3.35831553e-01 -1.12074304e+00 -2.63438284e-01 -1.82215557e-01 3.02067429e-01 7.90915608e-01 5.23141980e-01 -1.10715878e+00 -5.15279889e-01 -3.20276618e-01 -2.25082830e-01 -1.17017917e-01 -2.89804429e-01 2.46691555e-02 -2.22400799e-01 -7.18450308e-01 -1.51834443e-01 -5.00421166e-01 -1.52433932e-01 -7.20585704e-01 -1.00497496e+00 -6.30919218e-01 3.21640104e-01 -8.46598864e-01 1.49700785e+00 -1.62827027e+00 2.48898819e-01 -1.01869769e-01 6.39946759e-01 4.57577318e-01 -4.08956379e-01 5.51864684e-01 -4.90166992e-02 7.87631333e-01 -5.03030896e-01 -3.99574310e-01 2.51460940e-01 3.71119231e-02 -4.59499419e-01 -4.81930733e-01 1.00734806e+00 1.48856568e+00 -1.11497414e+00 -5.16039670e-01 -4.67486560e-01 6.00772835e-02 -5.33106327e-01 2.05606565e-01 -6.97924256e-01 -2.81753778e-01 -1.74604103e-01 5.62331617e-01 5.95085800e-01 -1.41628027e-01 -8.88068788e-03 1.93473741e-01 -3.17510664e-02 8.00374866e-01 -9.80718434e-01 1.70315409e+00 -2.06015795e-01 7.18616486e-01 -1.84025183e-01 -3.47817540e-01 9.17613685e-01 4.27075982e-01 2.23983765e-01 -4.33618188e-01 3.05566192e-01 3.39848518e-01 8.44893139e-03 -6.07728183e-01 1.06021130e+00 1.65597528e-01 -3.57308745e-01 5.55432022e-01 8.63007545e-01 -9.73931476e-02 7.96358883e-01 5.49524009e-01 1.51300299e+00 4.39480573e-01 5.34475029e-01 1.26702432e-02 -3.01721767e-02 -1.98773175e-01 6.95753872e-01 1.27318323e+00 -1.44127905e-01 7.04364657e-01 6.41036272e-01 -2.40254223e-01 -9.58845079e-01 -1.00673652e+00 -1.96502686e-01 7.98394740e-01 -3.12956721e-01 -1.03531647e+00 -1.14774442e+00 -1.08867514e+00 1.06270448e-03 9.39745307e-01 -6.76172674e-01 4.73639034e-02 -5.64679980e-01 -6.06284022e-01 8.45846355e-01 6.91811383e-01 2.84911722e-01 -1.68553591e+00 -4.88530993e-01 5.54057479e-01 -4.96293366e-01 -1.19649696e+00 -8.84850472e-02 6.57411218e-01 -5.90306878e-01 -8.65265429e-01 -2.97352970e-01 -3.95580679e-01 1.07121654e-01 -4.25189793e-01 1.83504248e+00 -3.31220806e-01 -1.17059439e-01 -2.86281556e-01 -6.17143214e-01 -1.05387282e+00 -3.41022938e-01 8.40803027e-01 4.50555980e-02 -4.53098267e-01 1.01363647e+00 -4.47686851e-01 6.70951754e-02 -5.59425533e-01 -7.93076694e-01 8.60397443e-02 9.42970932e-01 9.43384826e-01 3.77889842e-01 -3.75094235e-01 8.26623619e-01 -1.54079485e+00 1.07626629e+00 -6.71416283e-01 -1.97398916e-01 2.40428865e-01 -6.70312583e-01 5.33798993e-01 6.22940481e-01 -1.73703834e-01 -1.21319723e+00 -1.19098991e-01 -2.05199406e-01 -1.87065408e-01 -3.98797333e-01 6.02200508e-01 -2.60406733e-01 5.96886575e-01 9.62211192e-01 4.46219370e-02 -3.70638669e-01 -5.49490452e-01 7.45567858e-01 7.45027542e-01 7.52338767e-01 -5.64190507e-01 5.90699732e-01 -2.72242486e-01 -3.88016492e-01 -7.24318087e-01 -1.20328486e+00 -1.26308933e-01 -9.18130338e-01 4.67089862e-01 6.51133657e-01 -6.70411289e-01 -2.57557571e-01 3.92063767e-01 -1.79084611e+00 -1.25122383e-01 -6.42772675e-01 1.10645175e-01 -4.19887632e-01 4.90226038e-03 -9.41316366e-01 -7.37764835e-01 -8.89023721e-01 -7.23077655e-01 1.05078721e+00 2.20846757e-01 -8.22091937e-01 -6.09440446e-01 2.04316020e-01 -1.20691091e-01 1.47462681e-01 2.25520164e-01 5.91455042e-01 -1.21456659e+00 -6.36289597e-01 -7.04589188e-02 -2.61786491e-01 2.89201140e-01 -1.67932540e-01 -6.85709491e-02 -1.19436872e+00 2.74260432e-01 -2.05586135e-01 -6.44651592e-01 1.19675267e+00 5.52377068e-02 8.10505450e-01 -8.02671909e-01 -4.68848228e-01 5.63267708e-01 1.22917438e+00 -5.68443649e-02 6.45330608e-01 3.64365429e-01 6.52800977e-01 6.97768927e-01 3.64525974e-01 2.09481180e-01 2.99044788e-01 6.42178059e-02 1.44126654e-01 1.39775425e-01 -1.37159839e-01 -6.29383266e-01 3.47051919e-01 8.08195889e-01 8.41268748e-02 -5.82249403e-01 -6.40272617e-01 7.30633736e-01 -1.82906950e+00 -8.30875993e-01 -2.31655017e-01 1.71044290e+00 1.24481940e+00 4.26746041e-01 -1.90587744e-01 8.75903741e-02 1.92469150e-01 -4.22490388e-02 -5.09763002e-01 -7.24986494e-01 -2.03482196e-01 7.70304322e-01 3.60034317e-01 3.44274491e-01 -1.18041527e+00 1.24526620e+00 7.12923527e+00 6.77018404e-01 -4.97515976e-01 -1.64658785e-01 3.11088771e-01 -3.03475618e-01 -5.03954947e-01 -5.53614572e-02 -1.33310747e+00 3.88366610e-01 1.24766922e+00 -1.34106100e-01 1.00651726e-01 6.64979279e-01 -5.88612139e-01 -5.84673993e-02 -1.50640774e+00 6.23097837e-01 2.32856944e-01 -1.26714730e+00 1.61959797e-01 9.23669059e-03 6.61490858e-01 3.37885052e-01 -4.32665259e-01 7.10593820e-01 8.86230469e-01 -1.09285760e+00 7.43071318e-01 7.36038923e-01 4.60837722e-01 -5.81030846e-01 9.05551434e-01 4.99283910e-01 -7.24709928e-01 -9.85860359e-03 -2.05365598e-01 -1.90659434e-01 2.95279473e-01 7.08745122e-01 -1.04031515e+00 8.25116396e-01 8.15709412e-01 8.09685409e-01 -8.54704320e-01 5.82191586e-01 -7.07580984e-01 6.04346335e-01 -3.19721073e-01 -4.24557388e-01 9.31507349e-02 1.09100834e-01 7.59790242e-01 1.64966273e+00 -1.08165719e-01 -2.40839459e-02 -3.25497948e-02 1.23881221e+00 -4.52660948e-01 8.79043490e-02 -1.03035033e+00 -4.34293747e-01 6.17114842e-01 1.19422388e+00 -2.07607135e-01 -5.52239954e-01 -2.17161193e-01 1.00833499e+00 9.89641905e-01 2.90417582e-01 -2.59376585e-01 -1.08940685e+00 4.78578389e-01 -3.62579733e-01 5.96421599e-01 -5.44616282e-02 -6.58805430e-01 -1.29337823e+00 3.39396805e-01 -8.80713284e-01 3.31018150e-01 -6.01747572e-01 -1.37863362e+00 9.66751754e-01 -1.21196799e-01 -8.06748331e-01 -9.05698538e-01 -7.15723395e-01 -1.89114660e-01 8.81821096e-01 -1.39499998e+00 -9.16218340e-01 1.99831411e-01 -1.38442531e-01 7.06104577e-01 -1.16429798e-01 1.03909576e+00 -1.53184623e-01 -6.68019652e-01 8.11197519e-01 -9.09389034e-02 6.63477123e-01 5.53459823e-01 -1.67938137e+00 1.18126261e+00 1.25913978e+00 4.53401387e-01 1.04993153e+00 6.61542952e-01 -8.53303730e-01 -1.06517231e+00 -1.09469926e+00 1.66103828e+00 -1.13383293e+00 5.26461363e-01 -8.00423503e-01 -1.00148392e+00 1.00295067e+00 7.61639237e-01 -1.43988788e-01 6.37896538e-01 6.15583658e-01 -5.22912383e-01 2.65865773e-01 -9.43244278e-01 5.18935144e-01 1.41530061e+00 -3.06784332e-01 -1.02858603e+00 2.23812349e-02 1.33528411e+00 -5.25419116e-01 -1.05157089e+00 4.21731502e-01 4.95505065e-01 -9.13672388e-01 6.15410626e-01 -1.04294074e+00 9.18342948e-01 2.50939280e-01 1.84824556e-01 -1.65030110e+00 -3.06574911e-01 -8.74904811e-01 -8.84421229e-01 1.40189421e+00 1.06656158e+00 -5.39968193e-01 4.56396282e-01 5.77365160e-01 -3.15278083e-01 -9.70304549e-01 -4.36997563e-01 -8.71955037e-01 3.58427286e-01 -4.16741103e-01 5.98244369e-01 5.03102422e-01 4.00052905e-01 1.00965679e+00 -1.04752019e-01 -2.67112941e-01 3.84263992e-01 -1.67233795e-01 7.48742938e-01 -1.33066249e+00 -4.14678216e-01 -3.43848944e-01 1.43287405e-01 -8.96996200e-01 2.54545927e-01 -1.02364480e+00 3.96637112e-01 -1.63391519e+00 1.80667326e-01 -1.78778574e-01 -1.39408901e-01 7.29655445e-01 -5.34727633e-01 6.59972951e-02 3.83835077e-01 -9.36913490e-02 -5.39215386e-01 5.06993055e-01 1.10292959e+00 -6.65244609e-02 -4.02978182e-01 -4.66838539e-01 -1.27933085e+00 4.83866870e-01 7.11367369e-01 -5.46811283e-01 -2.00043470e-01 -6.36200905e-01 6.33641541e-01 -2.21456453e-01 -1.66853696e-01 -9.07746315e-01 1.11069933e-01 2.79848844e-01 5.43905675e-01 -7.57489800e-01 1.55104458e-01 -2.57207334e-01 -4.25475806e-01 1.05141655e-01 -6.11730397e-01 9.01412591e-02 2.96633452e-01 3.39625239e-01 -1.29588902e-01 -4.17922705e-01 -6.18033633e-02 -4.05785829e-01 -3.65713447e-01 2.95148253e-01 -3.85295480e-01 5.59906185e-01 5.50755024e-01 -4.38139327e-02 -5.90876222e-01 -1.89964529e-02 -5.17578483e-01 2.49958098e-01 -1.36544079e-01 6.80377126e-01 5.72641969e-01 -9.18393552e-01 -1.04482663e+00 3.47847730e-01 2.44955465e-01 6.01016402e-01 -4.20477450e-01 4.08867478e-01 -1.29478440e-01 7.19450653e-01 -5.22000762e-03 -7.74763599e-02 -7.66283751e-01 6.10035419e-01 -1.18020743e-01 -7.94066429e-01 -6.41144931e-01 1.12315309e+00 -2.37710625e-01 -7.35896707e-01 6.66752383e-02 -6.84923768e-01 -2.58216709e-01 1.49818435e-01 7.98933446e-01 2.87456334e-01 4.26772505e-01 -1.22295164e-01 2.72435229e-02 -1.89502820e-01 -7.08679378e-01 -4.15975302e-01 1.32579207e+00 2.41242245e-01 -2.53435999e-01 5.07945597e-01 9.48970199e-01 6.70591146e-02 -9.36314642e-01 -3.20186973e-01 4.32530940e-01 -6.26927838e-02 -2.28655457e-01 -1.15433383e+00 -4.33889031e-01 6.86638057e-01 -1.67776093e-01 3.03137004e-01 7.19110489e-01 7.02688843e-02 1.15129459e+00 6.73920333e-01 3.07948112e-01 -9.44564402e-01 -2.69578218e-01 1.17875338e+00 1.01183879e+00 -1.08762872e+00 -2.81249881e-01 -5.32660663e-01 -4.81572002e-01 9.19750333e-01 9.15059149e-01 -1.73406616e-01 5.36259413e-01 7.41676509e-01 -5.42369522e-02 -1.64707974e-01 -1.18211329e+00 -3.15896213e-01 1.20102182e-01 7.47080743e-01 6.86906576e-01 8.20252746e-02 -4.32772785e-01 1.32214963e+00 -8.16762984e-01 1.48100078e-01 4.64048088e-01 9.90974724e-01 -2.34370589e-01 -1.11942911e+00 -5.36420196e-02 9.02185321e-01 -4.79691267e-01 -6.16360843e-01 -1.08794999e+00 6.83086574e-01 1.89860836e-01 8.85465920e-01 4.14533801e-02 -4.96163428e-01 3.30302626e-01 5.96586168e-01 4.78635192e-01 -9.17990088e-01 -9.28469956e-01 -3.93648207e-01 6.16014242e-01 -4.52943861e-01 2.12049961e-01 -8.17849934e-01 -1.18701518e+00 2.27989540e-01 -5.26712179e-01 1.46357715e-01 4.17228013e-01 9.59897995e-01 7.15765178e-01 8.14615369e-01 9.54049081e-02 -5.88874996e-01 -7.16838956e-01 -1.64373934e+00 -2.53653973e-01 3.10912699e-01 4.63720143e-01 -4.18537289e-01 2.67637037e-02 -3.30635943e-02]	[9.82254695892334, 8.758051872253418]
92a17130-d4d4-482a-84b6-46256e4c74c2	demystify-transformers-convolutions-in-modern	2211.05781	null	https://arxiv.org/abs/2211.05781v1	https://arxiv.org/pdf/2211.05781v1.pdf	Demystify Transformers & Convolutions in Modern Image Deep Networks	Recent success of vision transformers has inspired a series of vision backbones with novel feature transformation paradigms, which report steady performance gain. Although the novel feature transformation designs are often claimed as the source of gain, some backbones may benefit from advanced engineering techniques, which makes it hard to identify the real gain from the key feature transformation operators. In this paper, we aim to identify real gain of popular convolution and attention operators and make an in-depth study of them. We observe that the main difference among these feature transformation modules, e.g., attention or convolution, lies in the way of spatial feature aggregation, or the so-called "spatial token mixer" (STM). Hence, we first elaborate a unified architecture to eliminate the unfair impact of different engineering techniques, and then fit STMs into this architecture for comparison. Based on various experiments on upstream/downstream tasks and the analysis of inductive bias, we find that the engineering techniques boost the performance significantly, but the performance gap still exists among different STMs. The detailed analysis also reveals some interesting findings of different STMs, such as effective receptive fields and invariance tests. The code and trained models will be publicly available at https://github.com/OpenGVLab/STM-Evaluation	['Xiaowei Hu', 'Yu Qiao', 'Xiaogang Wang', 'Jie zhou', 'Lewei Lu', 'Xizhou Zhu', 'Wenhai Wang', 'Linjie Xing', 'Sitong Wu', 'Weiyun Wang', 'Min Shi', 'Jifeng Dai']	2022-11-10	null	null	null	null	['spatial-token-mixer', 'image-deep-networks']	['computer-vision', 'computer-vision']	[ 2.10637897e-01 -2.70486295e-01 1.03051983e-01 -3.22298586e-01 -3.28042716e-01 -5.75904608e-01 8.72942805e-01 -2.22954571e-01 -2.81081915e-01 3.20471525e-01 3.04018319e-01 -3.98862660e-01 -1.64688349e-01 -7.29176700e-01 -6.98630750e-01 -8.95505309e-01 8.32545832e-02 -3.69799793e-01 4.63045895e-01 -4.68957454e-01 7.10659564e-01 5.08077323e-01 -1.69786191e+00 3.41634810e-01 8.09032202e-01 1.04521394e+00 3.88395578e-01 4.66670811e-01 -2.41115659e-01 5.58406115e-01 -4.78299618e-01 -2.84019887e-01 4.53171968e-01 -3.51881534e-01 -9.65138376e-01 -4.53284740e-01 5.16156018e-01 -1.82836309e-01 -3.01586777e-01 1.04730606e+00 5.42495668e-01 -6.27322197e-02 4.98250932e-01 -1.21599424e+00 -1.20177150e+00 5.34924448e-01 -5.93071580e-01 4.99680281e-01 1.12468302e-01 5.80325365e-01 1.18685114e+00 -1.03636289e+00 4.16670620e-01 1.19360733e+00 6.17237210e-01 4.32479680e-01 -1.17198849e+00 -3.96173030e-01 3.11783016e-01 3.60337943e-01 -1.32402360e+00 -5.94722390e-01 6.25910938e-01 -4.30935740e-01 1.05642474e+00 1.89101517e-01 6.01600707e-01 1.05984414e+00 3.98190796e-01 6.92536116e-01 1.33965683e+00 -4.98468697e-01 -6.57881424e-02 2.34098449e-01 3.85658234e-01 6.67045534e-01 1.74040556e-01 3.63907486e-01 -5.60311973e-01 1.97533697e-01 9.58215773e-01 1.18232012e-01 -5.15865684e-01 -1.15189105e-01 -1.37790477e+00 7.25165963e-01 1.02654719e+00 5.28051674e-01 -1.21393606e-01 1.41059995e-01 2.73665667e-01 4.87845093e-01 1.34083763e-01 5.66494286e-01 -3.09288949e-01 1.32337078e-01 -6.29186392e-01 -5.83957508e-02 3.48040968e-01 8.15670073e-01 9.28905308e-01 3.90905840e-03 -3.83366674e-01 6.83539510e-01 2.61846423e-01 3.25070143e-01 5.66163361e-01 -9.12895322e-01 1.91048175e-01 6.34393334e-01 -1.99213609e-01 -9.50560689e-01 -2.06543073e-01 -5.74206531e-01 -7.31492817e-01 4.42090958e-01 4.56042200e-01 2.83062123e-02 -9.97100413e-01 1.78341949e+00 -1.82869971e-01 -6.56329840e-02 -1.93163857e-01 8.73080969e-01 8.39872718e-01 3.54760736e-01 -9.21993330e-02 2.93393254e-01 1.44824743e+00 -1.15303886e+00 -3.34960639e-01 -2.38408282e-01 4.34682518e-01 -7.48183191e-01 1.32202518e+00 1.17382454e-02 -9.94120836e-01 -8.91107917e-01 -1.05533087e+00 -2.68980235e-01 -6.17290676e-01 -5.85237592e-02 8.81914258e-01 4.85426366e-01 -1.47639871e+00 7.09619880e-01 -6.76886201e-01 -7.62696505e-01 5.55719078e-01 4.25796330e-01 -1.40496343e-01 1.53419286e-01 -9.68654752e-01 1.00537181e+00 6.72555491e-02 9.02558714e-02 -6.39550805e-01 -6.56416595e-01 -4.63777244e-01 6.26112595e-02 2.86494419e-02 -1.05812132e+00 1.13567948e+00 -1.23445523e+00 -1.45941722e+00 7.79136598e-01 -3.22849512e-01 -3.28176528e-01 1.07906312e-01 -2.23780155e-01 -9.29927602e-02 -6.84795827e-02 1.42497316e-01 1.05806518e+00 1.06397700e+00 -1.10861051e+00 -7.55918324e-01 -3.17250162e-01 2.01619297e-01 1.09345108e-01 -4.40429628e-01 2.16189325e-01 -6.16740175e-02 -4.25542623e-01 7.34310672e-02 -7.27559865e-01 -1.07185267e-01 -2.38182899e-02 -3.23146760e-01 -2.17426002e-01 6.65096879e-01 -1.72381565e-01 1.04985213e+00 -2.42656970e+00 -1.79581910e-01 5.82508482e-02 3.91129881e-01 2.44996279e-01 -2.28989094e-01 3.71564478e-01 -1.81571290e-01 2.76875764e-01 -4.15341072e-02 -4.51986194e-02 -2.16459900e-01 -7.96730891e-02 -6.24839425e-01 2.61996001e-01 5.06082356e-01 1.25549924e+00 -6.72221243e-01 -2.97567278e-01 2.40359500e-01 4.62107688e-01 -4.42444414e-01 -7.68152922e-02 1.11137569e-01 4.59547102e-01 -4.41246152e-01 7.24100649e-01 6.26914144e-01 -4.31119800e-01 -3.85035902e-01 -5.02541065e-01 -6.46669149e-01 4.73548651e-01 -6.50255024e-01 1.64593935e+00 -1.70151412e-01 8.33507359e-01 -2.46760413e-01 -8.61487865e-01 7.93484569e-01 -3.21593462e-03 5.60179651e-02 -8.82320285e-01 2.54839063e-01 1.93629384e-01 5.33043921e-01 -2.89298266e-01 5.32656372e-01 7.54258931e-02 3.02545637e-01 2.22572818e-01 1.28550932e-01 2.17261612e-01 -1.05972156e-01 -1.76383480e-02 1.13819766e+00 8.41977447e-02 2.39554793e-01 -4.81503963e-01 4.35387641e-01 7.50478134e-02 2.21657395e-01 9.07420695e-01 -3.92417699e-01 7.05890357e-01 3.04826379e-01 -4.33856845e-01 -7.50132382e-01 -1.20639098e+00 -2.31433779e-01 1.30148172e+00 2.70577341e-01 -2.40026414e-01 -6.06366456e-01 -4.47682232e-01 -1.65704876e-01 3.26559097e-01 -7.30481088e-01 -3.65875483e-01 -2.77251303e-01 -6.76154017e-01 6.75705016e-01 7.96425641e-01 8.40408623e-01 -1.16623735e+00 -1.00620401e+00 -1.09967805e-01 -5.72556034e-02 -9.00610447e-01 -2.87366867e-01 3.23824406e-01 -9.34240043e-01 -6.45973384e-01 -5.94133675e-01 -7.98451602e-01 6.54646933e-01 7.76050389e-01 7.57861316e-01 1.29075021e-01 -3.03600848e-01 2.29044169e-01 -4.41294581e-01 -5.44081509e-01 2.05331251e-01 2.33210996e-01 -1.11566216e-01 -4.61124517e-02 4.33924854e-01 -6.55156016e-01 -9.77821767e-01 3.07416260e-01 -6.07665539e-01 1.11070752e-01 9.15066957e-01 8.48644793e-01 2.93727130e-01 -3.16411525e-01 4.42547202e-01 -5.28600395e-01 7.03802824e-01 -1.94371387e-01 -2.98380435e-01 6.04122058e-02 -6.14899874e-01 3.16864789e-01 5.03939867e-01 -2.04312310e-01 -1.04010093e+00 -1.39586717e-01 -2.31637180e-01 -2.00597033e-01 -3.52714449e-01 2.56130934e-01 5.60098104e-02 -3.64743978e-01 8.53437781e-01 5.21145523e-01 -3.25821228e-02 -4.19119030e-01 5.14078259e-01 4.88078743e-01 3.03862125e-01 -5.28749228e-01 7.71767139e-01 7.73696721e-01 -2.49407068e-01 -8.79028678e-01 -8.00139785e-01 -2.36565232e-01 -5.03011763e-01 3.18315327e-02 8.25788558e-01 -6.02907300e-01 -6.51035428e-01 5.95578849e-01 -1.27543271e+00 -2.33215690e-01 -4.00516719e-01 2.87953466e-01 -3.61177355e-01 2.05500856e-01 -5.70864916e-01 -4.94649589e-01 -3.86667520e-01 -1.29278743e+00 8.24786127e-01 6.01924837e-01 -2.58807689e-01 -8.41299236e-01 -1.00765571e-01 8.53458419e-02 9.49013293e-01 -2.05696240e-01 9.24593091e-01 -4.62281197e-01 -7.54520237e-01 2.02925697e-01 -7.24110842e-01 3.77378047e-01 2.04513431e-01 2.19912812e-01 -1.48102498e+00 -2.50756651e-01 7.21039921e-02 -6.00383468e-02 1.23560023e+00 5.31488061e-01 1.01173460e+00 5.85515201e-02 -4.29121315e-01 9.06817079e-01 1.36916089e+00 1.58188701e-01 9.09374833e-01 4.99097288e-01 6.31358325e-01 6.51394248e-01 2.14014724e-01 6.72247931e-02 2.97471106e-01 5.63438535e-01 4.44843501e-01 -3.20424080e-01 -2.32571855e-01 -8.49863961e-02 5.13146758e-01 7.35139430e-01 -5.10711670e-01 1.44026160e-01 -7.56813705e-01 4.15138751e-01 -1.70054245e+00 -1.01186252e+00 -9.50424671e-02 2.14949918e+00 5.62099040e-01 2.61697441e-01 -1.98745281e-02 -3.39827091e-02 6.59193337e-01 1.71224818e-01 -4.36002523e-01 -5.53065360e-01 -1.57102734e-01 3.83784443e-01 4.50138420e-01 2.44200766e-01 -8.92819643e-01 1.03744555e+00 6.89997387e+00 7.20460832e-01 -1.49572623e+00 4.61354814e-02 4.54666823e-01 1.11881748e-01 -1.88326165e-01 2.35461116e-01 -8.54990125e-01 3.86393696e-01 6.49657011e-01 -1.46576494e-01 3.60672832e-01 6.37544990e-01 9.59443972e-02 -9.48997736e-02 -1.19093490e+00 8.05267453e-01 -9.90950018e-02 -1.36599004e+00 1.98990047e-01 1.71066612e-01 4.34322774e-01 5.20656347e-01 4.42746907e-01 1.00725107e-01 6.90956712e-02 -1.07265246e+00 7.24021375e-01 4.46874887e-01 6.59342110e-01 -2.18308359e-01 6.08106375e-01 -1.69080850e-02 -1.10680771e+00 -2.17419833e-01 -5.61490715e-01 -3.77890795e-01 -2.51097232e-01 4.42973554e-01 -3.54117662e-01 4.62333232e-01 9.33386385e-01 7.02902615e-01 -9.22209144e-01 1.10427785e+00 -1.73352554e-01 5.32558143e-01 -1.20879218e-01 -1.39461542e-02 3.18779320e-01 -1.64325669e-01 3.69838446e-01 1.17585397e+00 3.42629820e-01 -3.08921218e-01 -4.29219872e-01 1.29458749e+00 1.31853119e-01 -4.44368646e-02 -9.73044515e-01 1.27990901e-01 3.96487713e-01 1.44464791e+00 -8.13867092e-01 -7.52716959e-02 -8.04816604e-01 1.00987172e+00 3.54003072e-01 4.29684520e-01 -9.30136979e-01 -5.52787840e-01 8.85943711e-01 6.33405298e-02 3.73262495e-01 -2.75213748e-01 -6.09954774e-01 -9.00673330e-01 3.74613702e-02 -5.13701081e-01 -3.97674628e-02 -7.60723531e-01 -1.31133699e+00 6.06299460e-01 -2.45026246e-01 -1.14588058e+00 1.94120616e-01 -7.53942251e-01 -1.06308365e+00 9.57074702e-01 -1.60857248e+00 -1.07843661e+00 -4.54466343e-01 7.71848321e-01 4.00559187e-01 -6.44788072e-02 5.16079664e-01 2.41424859e-01 -5.38544536e-01 7.78985143e-01 -2.58809440e-02 2.00756893e-01 7.09952950e-01 -1.03104937e+00 6.72951281e-01 8.31240654e-01 2.49997184e-01 1.11682081e+00 4.09096748e-01 -1.08421490e-01 -1.39652979e+00 -8.19584548e-01 7.02468097e-01 -7.08067536e-01 6.56733513e-01 -2.83377767e-01 -8.68092000e-01 7.20472753e-01 5.39264679e-01 -1.11283541e-01 3.49999398e-01 2.26299718e-01 -6.01990700e-01 -2.49682695e-01 -8.56426537e-01 8.48341644e-01 1.49859238e+00 -4.78276372e-01 -6.97000206e-01 -1.15833543e-01 8.23225856e-01 1.15661025e-01 -4.74379808e-01 4.22093660e-01 5.85541129e-01 -1.53261602e+00 9.56274271e-01 -3.93159032e-01 5.88378429e-01 -3.90324712e-01 -9.09043774e-02 -1.30439472e+00 -8.47776711e-01 -2.79202282e-01 3.09788913e-01 1.31795788e+00 6.22206211e-01 -1.19384480e+00 3.53306085e-01 3.00799727e-01 -2.96778589e-01 -7.34308720e-01 -7.71957695e-01 -7.91702628e-01 1.32023275e-01 -2.37101331e-01 4.01646912e-01 8.84488106e-01 -6.73742145e-02 6.24329448e-01 1.17516883e-01 -1.07832812e-01 3.80070806e-01 2.18410343e-01 5.38324416e-01 -1.07642007e+00 -3.26270312e-01 -9.09994602e-01 -5.18525064e-01 -1.16375983e+00 -2.87145525e-01 -8.76225233e-01 -1.67703897e-01 -1.49849117e+00 2.06224710e-01 -2.42794678e-01 -4.76465255e-01 6.43285930e-01 -9.37748924e-02 2.41076306e-01 2.28252143e-01 4.20556396e-01 -3.98299187e-01 4.56856281e-01 1.38779247e+00 -1.32090310e-02 -1.52705401e-01 -3.66626270e-02 -1.29932642e+00 7.80597031e-01 1.06123233e+00 -1.39913857e-01 -4.77156132e-01 -7.39871681e-01 7.21418783e-02 -7.42448270e-01 6.62723660e-01 -1.17904317e+00 2.76576519e-01 -5.65240085e-02 4.28629786e-01 -2.17903838e-01 2.18168184e-01 -5.80864191e-01 -2.86874503e-01 5.62991619e-01 -2.21464366e-01 2.33535171e-01 1.81892276e-01 1.54018968e-01 -2.80437261e-01 -4.03496660e-02 7.88522482e-01 -2.41892710e-01 -9.26568389e-01 2.18775831e-02 -3.08743834e-01 -3.13007943e-02 7.98407376e-01 -6.79601371e-01 -8.05720925e-01 -9.85520557e-02 -4.00155574e-01 -1.07369147e-01 5.17279327e-01 4.43995118e-01 6.08363032e-01 -1.13103294e+00 -6.23177886e-01 4.46238875e-01 1.33439928e-01 -2.23150641e-01 8.11772645e-02 1.24425030e+00 -2.35130876e-01 4.72227335e-01 -5.93972862e-01 -7.26916850e-01 -9.54646587e-01 5.58380365e-01 2.87171185e-01 1.68117478e-01 -6.30956233e-01 9.74509001e-01 6.87043369e-01 3.99436913e-02 4.22425978e-02 -6.19610608e-01 -6.93293139e-02 -3.27076390e-02 5.37885487e-01 3.17784756e-01 6.28804509e-03 -3.05057317e-01 -4.97097403e-01 8.71023774e-01 -2.64819980e-01 4.85793650e-02 1.09244764e+00 -2.23643288e-01 -2.20332459e-01 4.01493967e-01 9.48872149e-01 -1.52016193e-01 -1.21566653e+00 -1.87545136e-01 -6.75778538e-02 -5.01623213e-01 -2.37816781e-01 -5.97226501e-01 -1.10544384e+00 1.17166543e+00 7.52260566e-01 4.25176054e-01 1.25051081e+00 1.23741016e-01 4.81875777e-01 3.03794056e-01 3.73194098e-01 -8.56040657e-01 -3.27351578e-02 8.17463398e-01 9.23356354e-01 -1.10155797e+00 -3.41984838e-01 -4.79906917e-01 -5.78281224e-01 7.16652513e-01 9.44002509e-01 -3.27568114e-01 5.54322958e-01 3.70042980e-01 1.79814056e-01 -2.39357710e-01 -6.93609595e-01 -5.82114577e-01 1.06089702e-02 8.38648498e-01 7.70166874e-01 -9.76366773e-02 -2.15785012e-01 3.55412811e-01 -2.83231407e-01 -9.98119116e-02 1.28470317e-01 8.41525316e-01 -5.47882020e-01 -9.86183822e-01 -2.34241411e-01 6.21000171e-01 -2.47597635e-01 -5.22541702e-01 -5.58863103e-01 6.66398227e-01 3.85239214e-01 7.91993022e-01 6.46708310e-02 -6.97315753e-01 4.30280626e-01 1.45165831e-01 7.12996602e-01 -4.58870441e-01 -8.88096690e-01 -3.08917224e-01 -2.59246707e-01 -6.11038983e-01 -3.60141367e-01 -4.22858268e-01 -1.20577085e+00 -4.57545549e-01 -3.42875332e-01 -2.47814193e-01 3.64767581e-01 7.85313427e-01 6.95681930e-01 5.89771211e-01 5.33500254e-01 -8.97501528e-01 -5.10331750e-01 -9.65280592e-01 -3.24536681e-01 4.17701185e-01 3.01567703e-01 -6.83523297e-01 -3.65157723e-01 4.50862609e-02]	[9.62692928314209, 1.911351203918457]
1d3ea688-da20-4b58-b1ca-473dfd12819c	localizing-anomalies-from-weakly-labeled	2008.08944	null	https://arxiv.org/abs/2008.08944v3	https://arxiv.org/pdf/2008.08944v3.pdf	Localizing Anomalies from Weakly-Labeled Videos	Video anomaly detection under video-level labels is currently a challenging task. Previous works have made progresses on discriminating whether a video sequencecontains anomalies. However, most of them fail to accurately localize the anomalous events within videos in the temporal domain. In this paper, we propose a Weakly Supervised Anomaly Localization (WSAL) method focusing on temporally localizing anomalous segments within anomalous videos. Inspired by the appearance difference in anomalous videos, the evolution of adjacent temporal segments is evaluated for the localization of anomalous segments. To this end, a high-order context encoding model is proposed to not only extract semantic representations but also measure the dynamic variations so that the temporal context could be effectively utilized. In addition, in order to fully utilize the spatial context information, the immediate semantics are directly derived from the segment representations. The dynamic variations as well as the immediate semantics, are efficiently aggregated to obtain the final anomaly scores. An enhancement strategy is further proposed to deal with noise interference and the absence of localization guidance in anomaly detection. Moreover, to facilitate the diversity requirement for anomaly detection benchmarks, we also collect a new traffic anomaly (TAD) dataset which specifies in the traffic conditions, differing greatly from the current popular anomaly detection evaluation benchmarks.Extensive experiments are conducted to verify the effectiveness of different components, and our proposed method achieves new state-of-the-art performance on the UCF-Crime and TAD datasets.	['Jian Yang', 'Zhen Cui', 'Chuanwei Zhou', 'Hui Lv', 'Chunyan Xu']	2020-08-20	null	null	null	null	['anomaly-detection-in-surveillance-videos', 'anomaly-detection-in-surveillance-videos']	['computer-vision', 'methodology']	[ 1.86207473e-01 -6.20573223e-01 -5.10441028e-02 -2.77658194e-01 -4.67869252e-01 -3.57969463e-01 5.32856703e-01 3.41397494e-01 -2.12554991e-01 3.35335016e-01 1.21718921e-01 -9.50459242e-02 -1.03835367e-01 -4.30970281e-01 -4.23352867e-01 -9.22174394e-01 -3.84777933e-01 -3.10812593e-01 4.77873713e-01 -4.51504625e-02 3.67255688e-01 5.54680288e-01 -1.75367260e+00 3.11514795e-01 1.06032658e+00 1.52731943e+00 -1.82481334e-01 3.69070858e-01 -5.56490183e-01 8.81203175e-01 -5.03707588e-01 2.66905099e-01 2.54219264e-01 -5.48373878e-01 -3.98049504e-01 5.44569850e-01 3.47193480e-01 -4.42380339e-01 -5.05700350e-01 1.05287409e+00 1.56767443e-01 3.48904222e-01 3.69819611e-01 -1.43669260e+00 -8.61041620e-02 -4.30256426e-02 -7.14835227e-01 1.10173965e+00 4.57082152e-01 3.10404748e-01 9.07111883e-01 -9.38814461e-01 3.39288920e-01 1.00048542e+00 2.87581086e-01 2.08804697e-01 -7.42257953e-01 -5.82775593e-01 9.52957153e-01 8.31389427e-01 -1.22820914e+00 -2.90759712e-01 1.09675705e+00 -4.76143658e-01 7.43638456e-01 1.95913076e-01 5.16384900e-01 1.12014711e+00 1.07322466e-02 8.76298785e-01 7.17007816e-01 -6.62774667e-02 1.96116790e-01 -4.28682983e-01 2.15821281e-01 6.39387965e-01 -5.84268980e-02 -3.62278759e-01 -5.14743686e-01 -2.79974610e-01 2.81568527e-01 4.85887527e-01 -2.65626490e-01 -3.16257596e-01 -1.07823789e+00 4.74011272e-01 1.73344642e-01 3.76335889e-01 -6.16177201e-01 -2.90953100e-01 9.64179754e-01 4.88890082e-01 7.08678484e-01 5.94100542e-02 -1.80939540e-01 -4.57125157e-01 -6.50324643e-01 5.90280406e-02 2.40222201e-01 6.41478181e-01 6.80070579e-01 3.19726467e-01 -5.26167035e-01 7.57610738e-01 8.91845003e-02 1.69646129e-01 5.94664574e-01 -6.25052869e-01 6.92065001e-01 8.27454031e-01 -1.77590344e-02 -1.54339182e+00 -2.25778103e-01 -3.13391715e-01 -6.93117976e-01 5.34605049e-03 4.01291341e-01 1.49530083e-01 -9.06991780e-01 1.55508447e+00 4.39431101e-01 1.00475562e+00 -6.93831071e-02 9.39046144e-01 2.68722594e-01 7.54861414e-01 2.12763235e-01 -4.64699119e-01 1.12666738e+00 -6.96875334e-01 -7.89771140e-01 3.26240994e-02 9.29931879e-01 -5.81354737e-01 1.03270197e+00 3.20748895e-01 -7.41546988e-01 -6.40780628e-01 -8.80917370e-01 4.79567170e-01 -3.38002801e-01 -1.01013497e-01 3.58574897e-01 2.74661392e-01 -5.30300438e-01 3.48189652e-01 -1.02203190e+00 -3.57343674e-01 4.97198492e-01 -1.57509789e-01 -3.88197482e-01 -1.53196827e-01 -1.07895446e+00 2.92953551e-01 6.34600520e-01 2.44608819e-01 -7.83184230e-01 -4.29557741e-01 -8.55690300e-01 -1.06804602e-01 7.29561925e-01 1.90153286e-01 7.90108025e-01 -1.12409914e+00 -9.93329048e-01 5.28616548e-01 -3.67836475e-01 -5.83901227e-01 4.99309868e-01 -2.44026408e-01 -9.88745213e-01 4.67494100e-01 1.20201476e-01 6.12328574e-03 8.37865651e-01 -8.53627205e-01 -1.07151449e+00 -5.05778193e-01 7.80837685e-02 2.12539837e-01 -6.42828822e-01 2.18250304e-02 -7.35995829e-01 -1.09988022e+00 3.98721963e-01 -8.04899514e-01 1.73346195e-02 -8.33065733e-02 -3.03350747e-01 -2.91940391e-01 1.43824828e+00 -8.12914193e-01 1.74085593e+00 -2.73238516e+00 -6.01106770e-02 6.47989571e-01 8.81711617e-02 3.49688053e-01 -1.71011597e-01 1.32167071e-01 -1.12190023e-01 -1.14575982e-01 -4.20719534e-01 5.02467826e-02 -2.07167953e-01 3.19891691e-01 -4.61928129e-01 4.94050264e-01 5.01325011e-01 3.48416418e-01 -8.91381323e-01 -5.83389819e-01 2.42738068e-01 -4.25356701e-02 -4.40258712e-01 2.40250915e-01 -7.34313577e-02 6.86044633e-01 -8.49910319e-01 9.48771894e-01 6.57512248e-01 1.78887069e-01 -3.20919484e-01 -1.84426624e-02 -1.85682960e-02 -8.45374689e-02 -1.25925994e+00 1.59532988e+00 -1.55855447e-01 4.23026741e-01 -1.09032750e-01 -1.44943202e+00 7.55653262e-01 3.62338543e-01 9.21578765e-01 -9.09834623e-01 -2.83286065e-01 3.19374382e-01 -4.41653915e-02 -8.44194889e-01 2.88147151e-01 5.23674130e-01 -2.67597772e-02 2.43702963e-01 -1.42273575e-01 6.97922051e-01 4.74442393e-01 1.76657930e-01 1.28710687e+00 1.56665862e-01 5.32556958e-02 -8.12611207e-02 1.12664247e+00 -9.36342627e-02 8.29816103e-01 5.34106255e-01 -5.58815300e-01 4.46269184e-01 6.98820055e-01 -5.98591268e-01 -6.84240282e-01 -1.04503238e+00 -3.34108770e-02 1.07997966e+00 4.00251627e-01 -4.79100704e-01 -6.57445848e-01 -1.17764223e+00 -1.22858919e-01 6.69542313e-01 -4.75363493e-01 -3.92693043e-01 -7.58674562e-01 -7.35567391e-01 4.02650416e-01 5.73767900e-01 6.98194563e-01 -9.08306003e-01 -3.99355769e-01 2.70507425e-01 -3.88077766e-01 -1.30187654e+00 -5.69374621e-01 -2.64118493e-01 -7.10603178e-01 -1.11416876e+00 -3.21942240e-01 -5.09355843e-01 6.32338822e-01 4.88804013e-01 5.09110570e-01 1.89977348e-01 -2.75591850e-01 4.65598851e-01 -6.85726464e-01 -7.48735592e-02 -7.55764171e-02 -3.30743015e-01 1.84517011e-01 7.23392010e-01 7.11281955e-01 -6.40817523e-01 -6.03531659e-01 5.23488641e-01 -1.10226822e+00 -4.97701496e-01 4.69806075e-01 6.98903322e-01 8.58122647e-01 2.73806095e-01 5.73254287e-01 -5.26864827e-01 3.70388687e-01 -8.69551539e-01 -3.58447760e-01 -5.60931340e-02 -3.04173321e-01 -1.83600366e-01 8.29563379e-01 -3.19876999e-01 -1.15774357e+00 -2.86242455e-01 -4.52967286e-02 -6.84347451e-01 -5.77254713e-01 4.48207885e-01 -3.12005907e-01 1.85213715e-01 2.14872628e-01 4.96325314e-01 -1.70763075e-01 -3.90143692e-01 -1.34414762e-01 4.97916907e-01 5.46556652e-01 -5.16687751e-01 7.08206415e-01 6.00393236e-01 -5.42248748e-02 -8.62321794e-01 -6.60981297e-01 -8.23439956e-01 -5.18344879e-01 -2.83233106e-01 8.66702616e-01 -8.33840847e-01 -1.67220041e-01 5.65854371e-01 -7.91463673e-01 2.88427591e-01 -2.67201364e-01 5.82320929e-01 -3.73692989e-01 8.94264400e-01 -4.31044102e-01 -7.75859296e-01 1.51262209e-01 -1.05290520e+00 7.87803411e-01 5.10963015e-02 -4.73944191e-03 -6.45677149e-01 -1.58044055e-01 7.80072510e-02 9.99314263e-02 4.79805201e-01 9.61068630e-01 -1.09341240e+00 -4.96345639e-01 -3.74089211e-01 -2.35318705e-01 4.59260792e-01 2.95954138e-01 7.64933750e-02 -7.21966147e-01 -2.68175066e-01 5.91220707e-02 5.45217805e-02 8.85754883e-01 1.13970250e-01 1.79281056e+00 -1.85543999e-01 -3.58227819e-01 5.00346363e-01 9.06241596e-01 5.27971745e-01 5.20620286e-01 4.28492308e-01 9.51104939e-01 5.25730550e-01 1.13829720e+00 7.12348878e-01 9.13765654e-02 8.09637964e-01 4.56584364e-01 2.34100968e-01 2.86971658e-01 1.24761036e-05 7.18974650e-01 6.99924767e-01 -1.95113018e-01 -2.16172099e-01 -8.44833076e-01 4.78328228e-01 -2.02600884e+00 -1.16782606e+00 -1.25461936e-01 2.19092607e+00 2.13785097e-01 3.37360829e-01 2.32273534e-01 3.61885995e-01 7.79420912e-01 5.82649410e-01 -5.95675290e-01 -2.75306880e-01 -1.99068308e-01 -2.38737598e-01 -3.28801349e-02 -1.07619792e-01 -1.35876501e+00 5.69795012e-01 4.70483732e+00 1.10948873e+00 -9.25219715e-01 3.37083638e-02 6.41660035e-01 -1.28612578e-01 5.98603934e-02 -2.22703040e-01 -4.36152101e-01 9.67879474e-01 6.92523658e-01 3.85397561e-02 7.57891089e-02 7.97273278e-01 5.37673831e-01 6.60309941e-02 -7.55340934e-01 8.20528865e-01 1.25819728e-01 -7.04003036e-01 2.10988581e-01 -1.01178445e-01 4.26654875e-01 -2.43841112e-01 -6.17044456e-02 3.74837726e-01 -4.63287413e-01 -5.13379335e-01 4.70082432e-01 5.38066626e-01 3.00551564e-01 -1.03234446e+00 7.87336648e-01 1.43225685e-01 -1.56651437e+00 -4.88975853e-01 -1.44104376e-01 1.22481592e-01 1.56322047e-01 6.22363627e-01 -4.04947847e-01 7.68946469e-01 9.27027762e-01 1.21423554e+00 -7.08141029e-01 1.02961278e+00 -4.65834746e-03 8.57719839e-01 -2.39549145e-01 5.06416976e-01 6.26424432e-01 -3.90300959e-01 9.76081610e-01 1.27134299e+00 5.99306583e-01 1.66731730e-01 6.37301981e-01 3.18408310e-01 2.76871443e-01 3.95076156e-01 -6.56305313e-01 3.78655307e-02 2.71259427e-01 9.49700475e-01 -6.53974712e-01 -1.89427778e-01 -7.32845843e-01 1.08441532e+00 -3.13241333e-02 5.18024862e-01 -1.04363608e+00 -3.56860459e-01 1.02533209e+00 2.47494280e-02 4.05241430e-01 -2.99158841e-01 2.23514110e-01 -1.40996325e+00 6.04839504e-01 -7.72524297e-01 8.51562619e-01 -2.69320637e-01 -1.32454622e+00 4.31002617e-01 7.87953809e-02 -1.83572042e+00 -3.09459567e-01 -3.92357886e-01 -9.64269817e-01 4.53966081e-01 -1.45599973e+00 -8.07211220e-01 -5.71975291e-01 8.66256595e-01 8.71648014e-01 -3.94347429e-01 4.13318515e-01 4.67824399e-01 -1.05208802e+00 6.25334084e-01 -8.31432641e-03 1.69925287e-01 5.46767652e-01 -1.06468463e+00 1.53157234e-01 1.38048089e+00 2.02230494e-02 1.50705844e-01 4.80223954e-01 -7.14150786e-01 -9.90007877e-01 -1.28711760e+00 2.55658627e-01 -4.04105186e-02 8.40504527e-01 -4.02589552e-02 -1.49997699e+00 4.32223976e-01 -1.99817374e-01 4.78072673e-01 5.38249731e-01 -1.56193271e-01 -3.79237324e-01 -2.38758057e-01 -9.93635118e-01 6.10968590e-01 1.42966473e+00 -6.01716936e-01 -4.74458575e-01 7.13841692e-02 4.80669796e-01 -2.02580690e-01 -4.91811812e-01 5.98786294e-01 1.23812102e-01 -1.02013636e+00 8.30473423e-01 -6.94285154e-01 1.40665546e-01 -7.53544092e-01 -2.10846603e-01 -1.05335581e+00 -1.51646376e-01 -2.94974536e-01 -6.40450716e-01 1.46920800e+00 -7.73186013e-02 -6.80081785e-01 6.40579581e-01 2.39140704e-01 -4.88093287e-01 -7.81097531e-01 -1.14018703e+00 -8.78200531e-01 -6.76482379e-01 -7.11300850e-01 5.53081572e-01 8.94305587e-01 -1.16850719e-01 -3.31177145e-01 -3.78657490e-01 4.47687298e-01 4.32598472e-01 3.41159478e-02 4.91364717e-01 -9.48137224e-01 4.69094329e-02 -5.11200368e-01 -1.16960084e+00 -8.43247771e-01 3.84199917e-01 -7.17444718e-01 -6.04850166e-02 -8.91170800e-01 -1.13077492e-01 -1.23980224e-01 -1.05482864e+00 3.16614866e-01 -4.38184142e-01 1.55850738e-01 -1.40854463e-01 2.84666538e-01 -9.63635266e-01 6.03391767e-01 6.87364399e-01 -4.90472503e-02 -2.02538416e-01 1.03871197e-01 -1.98518202e-01 9.17266726e-01 8.31609130e-01 -2.33326510e-01 -6.84127271e-01 -1.93712011e-01 -4.06234115e-01 -2.44324058e-01 5.72334588e-01 -1.31766415e+00 3.65016125e-02 -2.21140817e-01 3.97897661e-01 -8.06771100e-01 1.10709861e-01 -9.33388412e-01 -3.12328815e-01 2.59510517e-01 -2.54431486e-01 3.89853805e-01 1.39025494e-01 1.14257050e+00 -7.48866022e-01 -7.37445010e-03 4.97524798e-01 2.02927515e-01 -1.37959731e+00 7.34066606e-01 -6.06708944e-01 2.01416567e-01 1.48831868e+00 -4.16631043e-01 -7.09889531e-02 -2.28451222e-01 -7.23606229e-01 4.52027321e-01 3.91337067e-01 6.68090522e-01 6.98664844e-01 -1.60154283e+00 -6.19248331e-01 3.25374573e-01 6.48415267e-01 -2.79739320e-01 8.14492702e-01 1.10557342e+00 -2.99869388e-01 1.80804893e-01 -2.16500863e-01 -8.08739007e-01 -1.10262311e+00 7.52225757e-01 1.50429010e-01 -1.13673985e-01 -8.36870253e-01 3.49909276e-01 3.31264079e-01 2.15701669e-01 2.75447696e-01 -2.45573774e-01 -4.78080869e-01 1.65954396e-01 7.89619684e-01 5.00536442e-01 7.85712153e-02 -8.71016026e-01 -4.82991457e-01 4.99370039e-01 -2.46659800e-01 3.69174898e-01 9.80815768e-01 -4.21481490e-01 1.36402816e-01 4.79771644e-01 1.14054334e+00 4.70116250e-02 -1.34938180e+00 -4.96300936e-01 4.54774469e-01 -7.92708933e-01 -1.05745405e-01 -1.49778068e-01 -1.23962879e+00 8.14254463e-01 8.47094119e-01 3.39059561e-01 1.49950898e+00 -2.01598555e-01 9.47201073e-01 2.83136368e-01 6.18084893e-02 -1.13537121e+00 2.85656214e-01 3.54970872e-01 4.68176931e-01 -1.27338934e+00 -3.47419471e-01 -3.12563002e-01 -8.52172077e-01 1.03215098e+00 9.32688117e-01 5.03935926e-02 4.22090262e-01 -1.05807304e-01 -1.36157960e-01 -9.92479995e-02 -4.32034552e-01 -2.66500860e-01 4.49476928e-01 3.77947837e-01 8.96806717e-02 -3.32768798e-01 -2.48140275e-01 4.19442058e-01 6.91532552e-01 -4.51922327e-01 2.60748625e-01 1.03791535e+00 -4.72716421e-01 -7.09706128e-01 -2.56872565e-01 6.10623896e-01 -6.33142769e-01 2.35207334e-01 -4.71490175e-02 4.92111921e-01 3.32561344e-01 9.23735619e-01 3.68785053e-01 -3.60495329e-01 5.09682477e-01 2.25089267e-01 -2.41591379e-01 -2.52736419e-01 -4.47676331e-02 1.44137652e-03 -5.51318228e-02 -9.54974890e-01 -4.17099714e-01 -8.53180170e-01 -1.30611813e+00 -6.46482175e-03 3.52191515e-02 3.01164269e-01 1.44042939e-01 1.12356508e+00 5.63904345e-01 4.93733555e-01 9.20605242e-01 -6.08305156e-01 -2.14111552e-01 -6.90939963e-01 -5.41894794e-01 9.42083538e-01 4.43803579e-01 -8.48179936e-01 -4.57442045e-01 -1.14599690e-01]	[7.847970485687256, 1.5991747379302979]
ed2ac614-bd81-48ad-83f7-66aa7ab44839	hie-sql-history-information-enhanced-network-1	2203.07376	null	https://arxiv.org/abs/2203.07376v2	https://arxiv.org/pdf/2203.07376v2.pdf	HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsing	Recently, context-dependent text-to-SQL semantic parsing which translates natural language into SQL in an interaction process has attracted a lot of attention. Previous works leverage context-dependence information either from interaction history utterances or the previous predicted SQL queries but fail in taking advantage of both since of the mismatch between natural language and logic-form SQL. In this work, we propose a History Information Enhanced text-to-SQL model (HIE-SQL) to exploit context-dependence information from both history utterances and the last predicted SQL query. In view of the mismatch, we treat natural language and SQL as two modalities and propose a bimodal pre-trained model to bridge the gap between them. Besides, we design a schema-linking graph to enhance connections from utterances and the SQL query to the database schema. We show our history information enhanced methods improve the performance of HIE-SQL by a significant margin, which achieves new state-of-the-art results on the two context-dependent text-to-SQL benchmarks, the SparC and CoSQL datasets, at the writing time.	['Changshan Li', 'Xingjun Wang', 'Baohua Dong', 'Haibin Wang', 'Yanzhao Zheng']	2022-03-14	null	https://aclanthology.org/2022.findings-acl.236	https://aclanthology.org/2022.findings-acl.236.pdf	findings-acl-2022-5	['text-to-sql']	['computer-code']	[ 1.77746624e-01 3.20740521e-01 -4.55445021e-01 -1.13521218e+00 -9.86994624e-01 -7.15292573e-01 6.52918935e-01 2.86091417e-01 -1.23611003e-01 2.77276933e-01 5.31165540e-01 -5.72950959e-01 2.13525981e-01 -1.11837435e+00 -1.05984330e+00 4.10199791e-01 3.50736856e-01 6.21498823e-01 6.11831129e-01 -3.97759944e-01 -2.29093358e-02 -1.02254506e-02 -1.54625988e+00 1.06257665e+00 1.03906226e+00 1.13886213e+00 6.56507835e-02 4.65551883e-01 -9.10232246e-01 1.31324553e+00 -2.03017801e-01 -6.30416036e-01 -3.53901349e-02 -3.78294080e-01 -1.09140623e+00 -3.59162152e-01 2.81707495e-01 -2.87440836e-01 -2.69900829e-01 7.27415740e-01 1.06384479e-01 -3.15814346e-01 -4.46157157e-02 -1.29444027e+00 -2.32684493e-01 1.01930165e+00 -1.07335642e-01 -5.65502763e-01 8.77853394e-01 1.36962133e-02 1.27961910e+00 -8.65054786e-01 8.87696564e-01 1.43327820e+00 4.79849696e-01 3.96923453e-01 -1.06990469e+00 -1.25862047e-01 1.26522943e-01 4.58380505e-02 -1.00287366e+00 -4.37836647e-01 8.22191298e-01 -2.42492810e-01 1.42855251e+00 3.45989972e-01 2.56887943e-01 9.40783143e-01 -7.17802569e-02 9.90111172e-01 7.21431494e-01 -5.52214682e-01 1.09037228e-01 3.16096514e-01 4.21998739e-01 8.99621248e-01 -1.22167625e-01 -1.38735071e-01 -8.60107422e-01 -2.81929672e-01 3.00497085e-01 1.33136913e-01 5.02795465e-02 -4.87207532e-01 -1.00671518e+00 6.63391590e-01 1.86643019e-01 1.45918131e-01 -1.04480445e-01 9.90606658e-03 7.91267395e-01 4.74030733e-01 -2.47496907e-02 3.00221711e-01 -8.74415636e-01 -3.35277200e-01 -4.02193159e-01 2.84544855e-01 1.33990419e+00 1.59360230e+00 7.89375663e-01 -5.23945332e-01 -1.47539482e-01 7.34503806e-01 2.55257517e-01 5.24701715e-01 1.88854530e-01 -8.97487521e-01 1.05548227e+00 1.40250134e+00 -2.83075236e-02 -6.12421036e-01 -2.77438730e-01 1.90980196e-01 -2.53886044e-01 -4.35512483e-01 3.33118886e-01 7.55619407e-02 -5.66121221e-01 1.68865156e+00 3.18459153e-01 -4.23604786e-01 4.22681779e-01 5.44623733e-01 8.18542421e-01 6.39345646e-01 1.47184491e-01 -1.88121408e-01 1.48048294e+00 -8.89414310e-01 -7.45962322e-01 -4.68204170e-01 9.77849960e-01 -4.97573078e-01 1.62953675e+00 6.51256517e-02 -1.06183171e+00 -6.14370763e-01 -9.88133311e-01 -5.36877573e-01 -5.55032551e-01 -3.74038145e-02 7.51151264e-01 3.49316865e-01 -5.71539700e-01 2.04465255e-01 -1.08664095e+00 -5.82503617e-01 -2.28825398e-02 3.34261707e-03 -2.46058136e-01 -1.87086791e-01 -1.18909717e+00 4.72254276e-01 6.94311321e-01 -1.98925480e-01 -2.89053649e-01 -6.88581824e-01 -1.12781274e+00 1.13571905e-01 1.14768183e+00 -5.27739406e-01 1.43180311e+00 -2.80736029e-01 -1.38709116e+00 7.86534727e-01 -6.12353325e-01 -4.35035557e-01 5.61559737e-01 -4.72066373e-01 -4.14363742e-01 -1.73887417e-01 1.31866485e-01 2.85582215e-01 -1.49130111e-03 -1.02908313e+00 -7.83152640e-01 -7.79531121e-01 3.00610632e-01 1.08812694e-02 2.17797421e-02 -4.75855879e-02 -1.14944124e+00 -2.48433948e-01 1.27295718e-01 -6.75228715e-01 2.04869509e-01 -1.89317569e-01 -6.78376794e-01 -5.20642936e-01 6.81854665e-01 -5.98715186e-01 1.48958063e+00 -2.17493033e+00 -8.45448896e-02 5.56342788e-02 4.20745350e-02 1.39032700e-03 3.53364423e-02 8.74393404e-01 2.01962754e-01 1.79920927e-01 -1.92222819e-01 -2.18999580e-01 3.94116521e-01 4.95954841e-01 -7.68226147e-01 -3.97409558e-01 4.15185064e-01 1.24913800e+00 -6.05012357e-01 -7.96775162e-01 -5.40529303e-02 2.86204014e-02 -7.29382157e-01 7.98358262e-01 -1.10396504e+00 5.11997156e-02 -7.20803559e-01 8.11032414e-01 5.51143348e-01 -2.80131340e-01 8.04264367e-01 -4.00134444e-01 1.44599425e-02 7.16119230e-01 -7.89297700e-01 2.13531208e+00 -6.12793088e-01 3.35675590e-02 -2.92048931e-01 -7.92137802e-01 8.52248907e-01 2.68276602e-01 2.45335624e-01 -1.11005223e+00 -3.61388594e-01 3.80902916e-01 -6.24838829e-01 -8.45779121e-01 3.20920885e-01 7.32870772e-02 -6.86768770e-01 2.95734614e-01 7.16471374e-02 -2.20796153e-01 1.28048629e-01 3.65123302e-01 1.13535357e+00 4.42783624e-01 4.02293921e-01 2.77119905e-01 5.56695580e-01 2.03919679e-01 6.08098626e-01 9.27001417e-01 1.87248915e-01 2.93235242e-01 1.01347065e+00 -3.56383920e-01 -6.53450072e-01 -1.04528534e+00 2.06701189e-01 1.46442902e+00 1.91083699e-01 -9.25337851e-01 -6.85866117e-01 -1.24589634e+00 1.35158047e-01 1.09064901e+00 -2.77682930e-01 -1.42638758e-01 -8.84974003e-01 1.08113308e-02 6.18115902e-01 8.30077887e-01 6.75270557e-01 -1.02253342e+00 -5.19393265e-01 3.48822385e-01 -4.69248801e-01 -1.58084440e+00 -3.63933891e-01 2.91303754e-01 -8.49332690e-01 -1.13997233e+00 3.20880443e-01 -4.91757810e-01 1.28125131e-01 -3.65158945e-01 1.44885147e+00 3.50695141e-02 1.63569562e-02 3.42571646e-01 -3.81215960e-01 -3.59219402e-01 -5.38304746e-01 1.44998744e-01 -6.55255437e-01 -1.25082225e-01 7.63502002e-01 -2.74991632e-01 -8.47061425e-02 4.13380861e-01 -1.05492043e+00 3.42087418e-01 3.62847298e-01 7.07840264e-01 6.29082859e-01 -6.39899522e-02 3.03691596e-01 -1.55009866e+00 2.12526128e-01 -2.83499300e-01 -7.32336044e-01 8.59529972e-01 -7.66756833e-01 6.52673423e-01 6.72634423e-01 3.65218297e-02 -1.41050458e+00 2.45186746e-01 -2.21967757e-01 -5.38880154e-02 -1.77933380e-01 9.93335962e-01 -7.77841568e-01 5.90568304e-01 4.56289232e-01 3.90046947e-02 -2.98459560e-01 -5.87352395e-01 6.05982721e-01 6.13475263e-01 9.60914254e-01 -9.43466604e-01 4.99376565e-01 2.45920062e-01 -2.67099917e-01 -1.34995446e-01 -9.46264029e-01 -2.71296829e-01 -4.50269550e-01 3.42341840e-01 8.80449355e-01 -7.40879953e-01 -9.06711698e-01 2.96168745e-01 -1.48266423e+00 -1.50370151e-01 -2.59783834e-01 5.06045222e-02 -6.02196097e-01 1.44390538e-01 -6.71389639e-01 -8.52558970e-01 -1.56811327e-01 -1.13517427e+00 1.30840254e+00 6.60594646e-03 -4.67321575e-02 -8.15167010e-01 -1.04415722e-01 5.28138876e-01 2.65269578e-01 2.45321572e-01 1.55977809e+00 -1.12989271e+00 -8.62405062e-01 -4.05546337e-01 -3.83114308e-01 8.65063071e-02 6.64402619e-02 -2.73912907e-01 -8.52345467e-01 1.93292737e-01 2.64329165e-01 -6.70920551e-01 5.30603051e-01 -4.09770727e-01 1.03331769e+00 -3.08710426e-01 -3.92482638e-01 4.77289945e-01 1.54705644e+00 4.59239930e-01 6.35854602e-01 3.20341554e-03 7.50079155e-01 8.26318860e-01 7.80456424e-01 3.81521046e-01 8.61350060e-01 9.19292212e-01 3.44671905e-01 2.27807686e-01 1.72590241e-01 -9.79378104e-01 2.31479749e-01 6.48287833e-01 5.42949200e-01 -2.66229331e-01 -1.20634675e+00 2.50485927e-01 -2.14775443e+00 -5.60437739e-01 2.65326388e-02 2.16934347e+00 1.16266978e+00 4.58790988e-01 -1.11049369e-01 -2.83053756e-01 3.79783839e-01 1.51818037e-01 -7.05902934e-01 -1.89265475e-01 3.26211154e-02 3.99862193e-02 7.06192628e-02 5.96860409e-01 -8.79674673e-01 1.16625512e+00 5.34089088e+00 5.79564452e-01 -1.03159809e+00 -5.13333790e-02 2.34943986e-01 1.81487158e-01 -5.37138104e-01 3.85064006e-01 -9.19541121e-01 2.43120179e-01 1.07585299e+00 -1.30008072e-01 4.80809063e-01 1.08577061e+00 -3.05172175e-01 -9.05787945e-02 -1.91814935e+00 7.96120763e-01 -2.21002907e-01 -1.22833157e+00 1.73034906e-01 -3.27998519e-01 8.54548290e-02 -1.76122427e-01 -4.01197493e-01 7.82440603e-01 1.18189752e-01 -7.15772152e-01 6.69938326e-01 6.60452485e-01 8.85731459e-01 -3.96776617e-01 8.03655624e-01 3.59352380e-01 -1.46157944e+00 -5.40497713e-02 1.20964341e-01 3.57634932e-01 1.43441617e-01 5.36987305e-01 -8.18018198e-01 1.06913245e+00 5.05252600e-01 5.45912862e-01 -7.04444885e-01 3.67511362e-02 -9.61788595e-02 4.16011274e-01 -3.00539702e-01 3.84969898e-02 -1.18696935e-01 1.55384302e-01 9.91006717e-02 1.13391745e+00 8.95876586e-02 1.79786772e-01 4.09854650e-01 1.18983638e+00 -2.10094467e-01 3.19732446e-03 -6.46797240e-01 -5.72937012e-01 6.38325870e-01 5.87623656e-01 -9.83714089e-02 -6.16832912e-01 -9.10573900e-01 8.89734387e-01 3.70531410e-01 3.23273897e-01 -8.06702912e-01 -6.62821710e-01 1.82413682e-01 2.26691633e-01 2.63075352e-01 5.33044897e-02 -4.52918053e-01 -1.44426203e+00 7.45951951e-01 -1.00974560e+00 6.48606062e-01 -7.65372574e-01 -1.12559128e+00 6.67417705e-01 1.80316582e-01 -6.74926221e-01 -6.10552847e-01 -4.59984273e-01 -2.87709296e-01 7.21785247e-01 -1.30295503e+00 -1.23417020e+00 -3.47542167e-01 5.35692573e-01 5.48522055e-01 -9.45897475e-02 8.28948081e-01 2.72329837e-01 -4.06107485e-01 6.42965078e-01 -5.26151836e-01 3.05917799e-01 7.03800380e-01 -1.38169932e+00 7.00967133e-01 6.63865507e-01 -9.69173908e-02 1.03369880e+00 4.26416248e-01 -8.13790977e-01 -2.14630413e+00 -1.08779168e+00 1.39073896e+00 -7.50931919e-01 4.40429747e-01 -8.44601989e-01 -1.15112042e+00 1.10271835e+00 1.65621229e-02 -3.31495479e-02 3.48772526e-01 2.55998850e-01 -7.99513996e-01 -3.02607954e-01 -9.49013114e-01 5.64388335e-01 1.22655916e+00 -1.21083057e+00 -8.78356695e-01 5.60402311e-02 1.44540346e+00 -5.43704510e-01 -9.53203142e-01 8.71393621e-01 5.73085666e-01 -1.12292862e+00 7.79729009e-01 -7.35570908e-01 5.25872588e-01 -1.40331879e-01 -7.46655941e-01 -4.75820571e-01 6.16253197e-01 -6.04194164e-01 -2.57112890e-01 1.52899039e+00 5.99607706e-01 -5.00963569e-01 8.99851441e-01 1.03383780e+00 -1.72033012e-01 -8.26554894e-01 -5.35205722e-01 -5.52224338e-01 -2.95745611e-01 -8.53320956e-01 9.42669749e-01 6.71202779e-01 4.79573458e-01 7.22667754e-01 1.28930423e-03 7.20204264e-02 1.38187066e-01 5.90475678e-01 1.03474700e+00 -1.06323993e+00 -5.01939952e-01 -4.53965738e-02 1.49053290e-01 -1.48867810e+00 1.08588576e-01 -8.43490243e-01 1.73249811e-01 -1.43035388e+00 1.99067280e-01 -2.64560342e-01 1.30156308e-01 7.95743287e-01 -1.66926503e-01 -8.12995851e-01 1.84309408e-01 6.96739331e-02 -7.64495134e-01 4.37804937e-01 6.58138335e-01 -1.57081723e-01 -4.62774009e-01 -1.59410253e-01 -7.19863892e-01 3.75427186e-01 2.57026643e-01 -3.46043646e-01 -7.20897019e-01 -5.92945278e-01 4.38433856e-01 8.68141830e-01 1.12864383e-01 -7.60880888e-01 5.14864981e-01 -2.96469033e-01 -2.29807645e-01 -7.03269899e-01 2.33013749e-01 -9.82371032e-01 1.74938768e-01 1.72406957e-01 -7.46976495e-01 1.85969114e-01 9.18082148e-02 6.17258489e-01 -6.03611290e-01 -9.14777592e-02 3.64020497e-01 -1.74454808e-01 -6.88206673e-01 4.65616509e-02 1.46375537e-01 4.53880101e-01 5.77948391e-01 3.10793191e-01 -5.93366563e-01 -2.92495549e-01 -5.50295651e-01 4.56774861e-01 3.67743224e-01 5.21417677e-01 4.85241979e-01 -1.17838335e+00 -1.86445460e-01 5.22358000e-01 6.60585999e-01 1.66965023e-01 -1.11291267e-01 6.70307398e-01 -4.41934764e-01 8.67456377e-01 1.95615575e-01 -6.14085674e-01 -1.01829672e+00 6.41025782e-01 1.50275797e-01 -6.06958330e-01 -2.82082051e-01 4.91154701e-01 1.81386203e-01 -9.84165907e-01 6.83129609e-01 -7.50480235e-01 2.16951504e-01 -4.17644680e-01 2.77002633e-01 -6.42703101e-02 1.68942437e-01 1.08741205e-02 -5.38283765e-01 4.83510464e-01 -2.14767382e-01 -2.64726669e-01 1.07756734e+00 -1.32463314e-02 -3.70999813e-01 6.69255674e-01 1.37299621e+00 9.80953798e-02 -8.41594815e-01 -8.30189109e-01 7.59312570e-01 -3.87450755e-01 -5.78855395e-01 -1.15007615e+00 -7.17867553e-01 8.06025386e-01 1.81727320e-01 3.49492311e-01 1.15984213e+00 3.68952453e-01 1.05106843e+00 8.51965249e-01 6.10092103e-01 -9.99218583e-01 1.47446379e-01 6.97896957e-01 8.47888589e-01 -1.41819143e+00 -4.42409486e-01 -9.01148200e-01 -8.88349473e-01 1.13617110e+00 8.47763777e-01 5.67244053e-01 4.54709172e-01 4.61744934e-01 6.83590546e-02 -4.24414903e-01 -1.04897618e+00 -6.64465502e-02 8.30883905e-02 4.10981238e-01 6.34710729e-01 -1.73950687e-01 -2.35939860e-01 9.99110520e-01 -3.66372541e-02 3.24570477e-01 -4.06178869e-02 1.51022232e+00 -2.07504243e-01 -1.60184586e+00 1.67863950e-01 3.06659102e-01 -2.39760607e-01 -1.32490113e-01 -5.90771019e-01 9.10131335e-01 -1.60581097e-01 1.04191458e+00 -5.54870404e-02 -6.38937235e-01 9.45328712e-01 7.39110708e-01 1.86154008e-01 -7.82838464e-01 -6.69789851e-01 -2.52852892e-03 4.96562421e-01 -1.10798979e+00 -3.55189517e-02 -3.54706168e-01 -1.70185924e+00 -2.64553010e-01 -1.43155470e-01 1.93514362e-01 5.70694506e-01 9.20450628e-01 7.62368321e-01 2.77707011e-01 5.02366722e-01 4.01206799e-02 -7.25182831e-01 -6.25212371e-01 -2.28408203e-01 6.36047244e-01 8.72657225e-02 -1.42343834e-01 1.07807070e-01 1.14126258e-01]	[9.933039665222168, 7.8452067375183105]
20abdfb6-f0fc-4bcd-a95b-8d6b379ff6b2	detecting-affordances-by-visuomotor	1611.00274	null	http://arxiv.org/abs/1611.00274v1	http://arxiv.org/pdf/1611.00274v1.pdf	Detecting Affordances by Visuomotor Simulation	The term "affordance" denotes the behavioral meaning of objects. We propose a cognitive architecture for the detection of affordances in the visual modality. This model is based on the internal simulation of movement sequences. For each movement step, the resulting sensory state is predicted by a forward model, which in turn triggers the generation of a new (simulated) motor command by an inverse model. Thus, a series of mental images in the sensory and in the motor domain is evoked. Starting from a real sensory state, a large number of such sequences is simulated in parallel. Final affordance detection is based on the generated motor commands. We apply this model to a real-world mobile robot which is faced with obstacle arrangements some of which are passable (corridor) and some of which are not (dead ends). The robot's task is to detect the right affordance ("pass-through-able" or "non-pass-through-able"). The required internal models are acquired in a hierarchical training process. Afterwards, the robotic agent is able to distinguish reliably between corridors and dead ends. This real-world result enhances the validity of the proposed mental simulation approach. In addition, we compare several key factors in the simulation process regarding performance and efficiency.	['Ralf Möller', 'Hendrik Hasenbein', 'Wolfram Schenck']	2016-11-01	null	null	null	null	['affordance-detection']	['computer-vision']	[ 3.31809193e-01 1.32725820e-01 1.12998724e-01 -1.21117815e-01 8.01584423e-02 -5.79870343e-01 7.89945781e-01 -2.82984767e-02 -5.40568054e-01 5.91139257e-01 -1.34445488e-01 -2.33179882e-01 -2.23629639e-01 -7.11498976e-01 -6.18141115e-01 -5.80082655e-01 -3.40294361e-01 4.32983458e-01 2.61555880e-01 -4.57172304e-01 5.53107858e-01 7.27380812e-01 -2.02191734e+00 3.03472370e-01 6.11649096e-01 5.38115919e-01 1.18817496e+00 7.80964792e-01 2.31647030e-01 7.95513034e-01 -2.61587888e-01 5.62112629e-01 1.36202261e-01 -5.58047652e-01 -9.26670194e-01 4.21565861e-01 -4.38436568e-01 -3.47780168e-01 -1.27617687e-01 1.10449791e+00 2.90342476e-02 4.38538373e-01 9.51705873e-01 -1.32770514e+00 -3.16472501e-01 3.33366007e-01 1.61679342e-01 -7.50841871e-02 9.92502630e-01 5.70195198e-01 6.02192461e-01 -7.89873660e-01 8.77350509e-01 1.37362671e+00 -1.49660721e-01 5.58230758e-01 -1.11952555e+00 -9.15727839e-02 1.73002020e-01 3.08384687e-01 -1.20952010e+00 -3.91435623e-01 4.68486756e-01 -6.36879504e-01 1.12378836e+00 3.22761357e-01 1.09269810e+00 1.02309334e+00 3.77978593e-01 6.44373417e-01 1.13571751e+00 -6.07068300e-01 5.32218993e-01 -1.96222514e-01 -9.89485346e-03 6.95132136e-01 -8.31292272e-02 6.45739079e-01 -4.37655360e-01 2.11825088e-01 1.04556346e+00 4.62039337e-02 -2.58547246e-01 -6.20255232e-01 -1.62175381e+00 2.63727218e-01 6.77638948e-01 4.40678567e-01 -8.18412006e-01 -5.37972674e-02 -1.07591979e-01 5.50836146e-01 -6.36998475e-01 5.13787508e-01 1.87867194e-01 1.58536900e-02 -3.28631431e-01 2.94301957e-01 5.85445523e-01 8.62542987e-01 4.64048147e-01 -1.53688833e-01 9.55449045e-02 2.43199363e-01 6.19053781e-01 3.43151748e-01 5.56882858e-01 -1.06221044e+00 3.75385821e-01 8.26372266e-01 8.00061405e-01 -8.77499580e-01 -6.99920535e-01 -1.53742172e-02 -4.67806011e-01 9.93928552e-01 5.56972325e-01 3.22357953e-01 -9.97227073e-01 1.65379810e+00 4.76854056e-01 -9.83205587e-02 4.27361250e-01 1.31547737e+00 3.05694103e-01 6.91348255e-01 3.13686341e-01 -9.71243456e-02 1.64097595e+00 -7.57343233e-01 -5.49913704e-01 -3.09326142e-01 6.62446856e-01 -4.72866654e-01 1.19113553e+00 4.90752369e-01 -8.94843459e-01 -8.31756234e-01 -1.36563635e+00 1.55888319e-01 -3.42793792e-01 3.42591286e-01 4.73835140e-01 2.28997506e-02 -8.92096579e-01 6.37612820e-01 -8.37457895e-01 -6.78385854e-01 -2.12637514e-01 2.05617025e-01 -6.51790977e-01 1.00487866e-01 -9.81812835e-01 1.17154825e+00 8.21882308e-01 4.55975235e-01 -1.46363950e+00 4.37218338e-01 -9.61293578e-01 -5.93036674e-02 2.70251542e-01 -7.70646632e-01 1.08639753e+00 -9.53502357e-01 -1.48262167e+00 8.00756216e-01 -1.00032121e-01 -1.20195895e-01 6.62320793e-01 2.41778865e-02 -4.34363693e-01 2.00339079e-01 2.53548682e-01 6.59965575e-01 9.11060274e-01 -1.61685526e+00 -7.14798748e-01 -4.77560103e-01 2.83560604e-01 7.82071352e-01 3.91540945e-01 -1.04701698e-01 -1.75411344e-01 -1.20645955e-01 7.86636353e-01 -1.16371965e+00 -2.28121758e-01 -1.02373615e-01 -5.69101095e-01 -1.86384529e-01 3.54235291e-01 -2.56276667e-01 8.28620791e-01 -2.20403075e+00 5.10189712e-01 2.68293858e-01 4.93204482e-02 -2.32196391e-01 -2.04134151e-01 7.51830578e-01 -9.30478275e-02 -2.71714091e-01 -2.92512551e-02 -3.33865806e-02 -1.39335692e-01 3.41684908e-01 -1.74800023e-01 2.65085608e-01 -1.16709858e-01 3.60196888e-01 -9.97478664e-01 -2.85440832e-01 3.99884582e-01 1.85559615e-01 -2.75377512e-01 5.18553853e-01 -1.07830405e-01 8.56535077e-01 -6.87070847e-01 1.89627558e-01 2.10189030e-01 8.90030935e-02 4.27434176e-01 3.56056578e-02 -5.59894145e-01 3.80679727e-01 -1.40734112e+00 1.67254496e+00 -1.92692131e-01 1.19383752e-01 -3.07327107e-04 -6.07524633e-01 7.77629912e-01 4.08596247e-01 -1.68431014e-01 -5.73093295e-01 2.13263273e-01 2.17076421e-01 4.48921829e-01 -1.07435787e+00 5.46002626e-01 1.77530020e-01 -8.87180716e-02 4.23812807e-01 -2.06543773e-01 -2.84068912e-01 4.33977425e-01 1.37698790e-02 9.15728092e-01 8.84678721e-01 6.69789493e-01 -1.06485158e-01 4.59899843e-01 2.99192607e-01 5.80561534e-02 7.33124375e-01 -2.67107904e-01 8.39303881e-02 3.03193063e-01 -4.18038040e-01 -1.15820777e+00 -1.35208321e+00 3.89232635e-01 1.12370515e+00 6.81715667e-01 1.86249595e-02 -8.10980916e-01 -4.72993776e-02 -3.12310547e-01 1.01108611e+00 -6.51702166e-01 -2.19700858e-01 -6.50519490e-01 -2.29584292e-01 8.71323608e-03 3.26204389e-01 3.27280015e-01 -1.87670755e+00 -1.73062229e+00 2.68329650e-01 -3.29280138e-01 -8.74765575e-01 9.29750353e-02 1.15084328e-01 -9.25023913e-01 -9.31321323e-01 -2.04326287e-01 -8.68307173e-01 1.00710273e+00 2.86290348e-01 4.09100831e-01 2.21018806e-01 6.40896484e-02 1.32484421e-01 -3.20481002e-01 -3.87319513e-02 -8.97925198e-01 -5.12124300e-01 2.54364073e-01 5.48988937e-05 -5.43749705e-02 -4.04886454e-01 -6.35553360e-01 3.85381192e-01 -7.86898851e-01 6.01169825e-01 7.04072475e-01 5.92837691e-01 4.40455198e-01 -3.77669223e-02 2.75159001e-01 1.32216126e-01 9.09388304e-01 -3.45933437e-01 -3.16762984e-01 8.36835504e-02 -8.62317681e-02 2.82761216e-01 3.87507766e-01 -7.07400560e-01 -1.17180371e+00 3.39634001e-01 3.39912213e-02 1.59655400e-02 -7.09775448e-01 5.67929864e-01 -1.10112868e-01 3.82894367e-01 7.33429849e-01 4.78965551e-01 9.19162706e-02 -1.68691948e-01 2.40771458e-01 5.85200071e-01 6.78995311e-01 -3.86446476e-01 4.89808023e-01 5.29884636e-01 5.97883016e-02 -6.85922503e-01 1.08522978e-02 -7.07325041e-02 -1.04942417e+00 -8.30810964e-01 9.44651842e-01 -5.29822946e-01 -1.06156099e+00 5.35190821e-01 -1.23101401e+00 -5.73469818e-01 -1.08136803e-01 8.44021022e-01 -9.84202027e-01 2.21094534e-01 -4.86583143e-01 -1.10827899e+00 3.30099970e-01 -1.45304263e+00 7.24915922e-01 1.38811678e-01 -6.17813528e-01 -2.90132165e-01 -3.34185719e-01 -2.15070784e-01 -1.48019478e-01 2.52997607e-01 1.01320660e+00 -3.25642258e-01 -6.14456713e-01 -1.69228092e-01 3.66220176e-02 -2.64093816e-01 -7.65179619e-02 -1.52761325e-01 -5.42782307e-01 -1.11588620e-01 1.67027280e-01 -1.61866277e-01 3.47112268e-01 2.23293193e-02 3.52356613e-01 1.86117757e-02 -6.61070228e-01 -9.96931344e-02 1.14739990e+00 8.69752705e-01 7.33167946e-01 5.50079286e-01 3.47259223e-01 8.93467665e-01 1.11494792e+00 1.92379817e-01 4.44372207e-01 7.05816925e-01 9.50788975e-01 1.69903114e-01 1.24411412e-01 -3.75467598e-01 5.08117914e-01 4.15469378e-01 -5.90676665e-01 -1.11796856e-01 -8.57721984e-01 3.10072184e-01 -1.86815703e+00 -1.03904378e+00 -3.07361931e-01 2.25865722e+00 2.39781514e-01 3.89523506e-01 -6.37948141e-02 5.11054158e-01 7.46405840e-01 -2.29690239e-01 -5.29913664e-01 -5.14708519e-01 2.49994069e-01 -4.22157735e-01 -1.85058534e-01 5.32509029e-01 -6.79248512e-01 1.14025879e+00 5.71193600e+00 2.63049304e-01 -9.74208951e-01 -2.23952115e-01 -1.27742842e-01 3.23198318e-01 1.16527947e-02 1.07232623e-01 -2.16948703e-01 1.94995925e-01 4.84660417e-01 2.70015001e-01 7.34133124e-01 7.16590285e-01 4.97605264e-01 -8.72206628e-01 -1.43647850e+00 5.17639518e-01 -1.08138546e-01 -7.33128786e-01 1.29647836e-01 -7.50460997e-02 9.99951456e-03 -3.60481471e-01 -2.05721423e-01 2.13856176e-01 1.51793003e-01 -9.19282317e-01 1.39840698e+00 7.41634130e-01 6.98940277e-01 -4.35876757e-01 1.45131767e-01 1.05323601e+00 -1.31224442e+00 -4.20228601e-01 -2.07687736e-01 -6.23031318e-01 4.87602115e-01 -2.18446776e-01 -9.46197867e-01 4.03332978e-01 4.33806181e-01 7.16963038e-02 -1.21987842e-01 7.71607459e-01 -7.33823299e-01 -9.35047567e-02 -1.73246741e-01 -4.22991723e-01 2.58985102e-01 -3.60075295e-01 8.96551073e-01 6.60144448e-01 5.69656491e-01 2.96928138e-01 1.58898786e-01 9.50111389e-01 7.00976551e-01 -1.23688728e-01 -8.10319841e-01 3.12968612e-01 5.52486777e-01 8.82109463e-01 -1.06670260e+00 -6.50406241e-01 1.70907289e-01 1.29081237e+00 3.90517354e-01 5.90655148e-01 -4.33711797e-01 -1.19514272e-01 4.23275471e-01 -1.16524845e-01 -1.19333625e-01 -6.18721426e-01 4.65515815e-02 -7.69779503e-01 -7.74017796e-02 -5.43226898e-01 7.27134943e-02 -1.43066144e+00 -5.65507472e-01 7.77282298e-01 1.51542008e-01 -1.51439762e+00 -6.42475188e-01 -5.83651304e-01 -4.16672081e-01 9.60169196e-01 -9.44287121e-01 -9.15952802e-01 -4.21226680e-01 7.48543561e-01 5.96445143e-01 1.18472211e-01 1.21084809e+00 -4.14308190e-01 3.99158336e-02 -3.93872797e-01 -4.26028877e-01 -1.23167448e-01 7.23377615e-02 -9.35320914e-01 2.73181289e-01 7.17737079e-01 -1.98293835e-01 6.48359120e-01 1.02266324e+00 -8.10717642e-01 -1.13509929e+00 -4.00272757e-01 9.18784559e-01 -3.27850282e-01 3.89373362e-01 -2.80894607e-01 -7.31391311e-01 6.90063834e-01 -1.51600063e-01 -4.96595770e-01 2.18545794e-01 -5.88648438e-01 2.45890068e-03 4.97259200e-01 -1.24636734e+00 1.19982600e+00 1.31040502e+00 -3.60706776e-01 -1.24658060e+00 -9.12735984e-02 2.86649287e-01 -3.53908867e-01 -3.31965059e-01 2.21039474e-01 9.77795184e-01 -1.27182567e+00 8.53353441e-01 -6.55853033e-01 3.16342771e-01 -7.84447491e-01 4.95886207e-02 -1.29659903e+00 -5.13859689e-01 -2.01509759e-01 1.95146322e-01 3.43454808e-01 1.24362342e-01 -6.49725735e-01 1.89587995e-01 2.02574581e-01 -2.16003627e-01 -3.13551366e-01 -1.00155461e+00 -7.53844917e-01 -5.83382666e-01 -6.58760846e-01 5.61290443e-01 6.57621503e-01 6.00925207e-01 2.64805466e-01 -1.92982510e-01 4.20446306e-01 4.56030101e-01 2.92388141e-01 7.21525550e-01 -1.28198862e+00 -7.59050548e-02 -3.27081770e-01 -4.66561377e-01 -1.30411232e+00 -4.85090464e-02 -7.91387737e-01 3.44610274e-01 -1.77496243e+00 -6.02779128e-02 -2.13638663e-01 -9.28187594e-02 3.80270064e-01 1.86636597e-01 -1.69286147e-01 5.69443703e-01 6.43942177e-01 -1.77990213e-01 2.08149418e-01 1.67906380e+00 3.00344616e-01 -5.70341349e-01 1.35297328e-02 6.76755831e-02 1.00205719e+00 9.04859722e-01 -2.59528846e-01 -3.83743644e-01 -1.01413310e-01 2.60899186e-01 7.51060486e-01 5.80042243e-01 -1.16430271e+00 2.16065958e-01 -2.55853772e-01 3.44101369e-01 -5.40980399e-01 6.48379326e-01 -9.85866368e-01 2.37127513e-01 1.07949078e+00 -3.33373070e-01 3.48751068e-01 -1.39305413e-01 5.25305390e-01 1.38264567e-01 -4.49665397e-01 4.39676017e-01 -3.23118836e-01 -1.18920338e+00 -4.50605810e-01 -1.19232023e+00 -8.19456220e-01 1.33716226e+00 -8.17967057e-01 8.42828453e-02 -2.46067822e-01 -1.45396411e+00 6.27370328e-02 3.81226569e-01 4.89138186e-01 8.36688399e-01 -1.26326025e+00 -2.56328970e-01 5.60651660e-01 2.75036454e-01 -3.14962775e-01 2.47162640e-01 7.97656953e-01 -4.85732913e-01 2.18536913e-01 -8.20526540e-01 -6.40783310e-01 -1.10541975e+00 8.43767881e-01 2.35790491e-01 7.49990344e-02 -4.70241785e-01 2.86139876e-01 2.23180428e-01 -4.76537079e-01 -3.82580422e-02 -4.31837916e-01 -7.54914880e-01 -1.27079695e-01 3.18753481e-01 3.66244435e-01 -5.08569300e-01 -1.06603658e+00 -1.83968395e-01 4.53342468e-01 5.58468819e-01 -6.94670081e-01 8.47642958e-01 -4.90885288e-01 1.24317757e-03 7.03685462e-01 3.92483562e-01 -3.87369961e-01 -1.30218577e+00 2.27278516e-01 4.75781672e-02 -3.07998478e-01 -6.34997249e-01 -8.80752444e-01 -5.33893108e-02 8.11658204e-01 6.69483364e-01 3.66219491e-01 9.81899440e-01 -1.76068209e-02 -2.12726789e-03 7.22891390e-01 9.69234347e-01 -1.04628861e+00 2.74868906e-01 5.99563181e-01 1.19688022e+00 -9.23486233e-01 -3.66017312e-01 -4.71914917e-01 -6.83355272e-01 1.20943093e+00 4.51045692e-01 -1.42044634e-01 1.36285856e-01 6.24053739e-02 -2.48379689e-02 -3.18957984e-01 -5.99752486e-01 -3.91216904e-01 1.50384605e-02 8.04274142e-01 -8.60847756e-02 3.99399459e-01 -3.67542356e-01 1.31151751e-01 -4.77340400e-01 1.50680065e-01 6.10367775e-01 9.77864802e-01 -8.61631274e-01 -5.39835393e-01 -5.99649489e-01 -7.58544803e-02 4.14233506e-01 2.27715045e-01 -7.37096220e-02 1.02193344e+00 1.42810881e-01 1.14324903e+00 3.05415869e-01 -3.28520030e-01 5.10052860e-01 1.27454817e-01 6.42515421e-01 -5.81730843e-01 -2.33416036e-01 3.88764553e-02 1.45655349e-01 -8.03301036e-01 -3.55850577e-01 -6.80421114e-01 -2.10106158e+00 1.17572725e-01 1.77281305e-01 -9.14300382e-02 8.36058021e-01 1.02434218e+00 7.72711039e-02 6.14997625e-01 3.71080458e-01 -1.41253161e+00 -4.80165690e-01 -9.72165585e-01 -4.32512552e-01 6.57738507e-01 2.60749787e-01 -1.00166309e+00 -3.20288152e-01 9.49560255e-02]	[4.6127238273620605, 0.8330073356628418]
3032d484-b3e1-4d46-9d20-f5a04b41d638	team-donotdistribute-at-semeval-2020-task-11	2008.09703	null	https://arxiv.org/abs/2008.09703v1	https://arxiv.org/pdf/2008.09703v1.pdf	Team DoNotDistribute at SemEval-2020 Task 11: Features, Finetuning, and Data Augmentation in Neural Models for Propaganda Detection in News Articles	This paper presents our systems for SemEval 2020 Shared Task 11: Detection of Propaganda Techniques in News Articles. We participate in both the span identification and technique classification subtasks and report on experiments using different BERT-based models along with handcrafted features. Our models perform well above the baselines for both tasks, and we contribute ablation studies and discussion of our results to dissect the effectiveness of different features and techniques with the goal of aiding future studies in propaganda detection.	['Nazli Goharian', 'Michael Kranzlein', 'Shabnam Behzad']	2020-08-21	null	https://aclanthology.org/2020.semeval-1.196	https://aclanthology.org/2020.semeval-1.196.pdf	semeval-2020	['propaganda-detection']	['natural-language-processing']	[-2.02454068e-02 -2.41049558e-01 -5.07772624e-01 -1.80617988e-01 -1.02249336e+00 -7.87398696e-01 1.51618087e+00 3.55710268e-01 -7.85414457e-01 3.80277485e-01 1.04785478e+00 -8.90620708e-01 3.81227210e-02 -3.58340442e-01 -2.26811022e-01 -2.29085296e-01 -2.93956935e-01 3.28617766e-02 1.95148274e-01 -4.63474125e-01 1.10872638e+00 2.82832444e-01 -7.78932810e-01 9.10418391e-01 5.70021152e-01 3.77432555e-01 -3.60276788e-01 8.38345587e-01 4.58323099e-02 1.76401126e+00 -1.21731579e+00 -4.48266625e-01 5.44277430e-02 -4.10627723e-01 -1.12206483e+00 -5.67713261e-01 9.59738076e-01 -4.46761936e-01 -5.23293674e-01 8.72422695e-01 5.88354409e-01 -3.28751057e-02 8.94496441e-01 -6.51679099e-01 -6.91441178e-01 1.03296173e+00 -8.12140822e-01 1.18075490e+00 7.69853592e-01 -1.23122007e-01 8.28785241e-01 -7.26547062e-01 1.06987154e+00 1.25532830e+00 8.02449048e-01 4.83039409e-01 -1.00227416e+00 -7.12719440e-01 -9.80931669e-02 4.87010956e-01 -9.90824342e-01 -8.45723093e-01 7.51336813e-01 -8.28645468e-01 1.13888431e+00 2.80667454e-01 2.90783972e-01 1.83627474e+00 4.71691161e-01 9.77539659e-01 1.11866987e+00 -4.82802153e-01 -1.30170397e-02 2.09957510e-01 6.59196794e-01 1.06595671e+00 1.19918965e-01 3.48705016e-02 -8.96088779e-01 -6.08641863e-01 3.29489142e-01 -7.15146482e-01 -1.26575828e-01 4.46640551e-01 -1.13132834e+00 1.34937465e+00 3.27695549e-01 6.52113795e-01 -8.04995224e-02 2.34248266e-02 8.93711030e-01 4.53404397e-01 1.04206240e+00 9.69268739e-01 -7.90783912e-02 -3.54626536e-01 -1.28765261e+00 8.18242013e-01 1.01011837e+00 5.15976548e-01 -7.73088560e-02 6.38021678e-02 -7.49456942e-01 6.58607483e-01 -3.19138587e-01 3.69866341e-01 2.24703178e-01 -6.59777999e-01 8.12384784e-01 9.47136208e-02 2.00293154e-01 -1.30350184e+00 -7.28858471e-01 -4.28256869e-01 -2.44566455e-01 -3.17608975e-02 3.29943240e-01 -4.42239493e-01 -1.06232703e+00 1.24551785e+00 -1.96168214e-01 -1.72047019e-01 -4.43405151e-01 6.36285961e-01 8.90213490e-01 7.01298594e-01 2.96875834e-01 -3.25812995e-01 1.30841649e+00 -1.09120572e+00 -8.39698195e-01 -1.75910935e-01 1.21082461e+00 -9.34245765e-01 7.55089998e-01 3.08411479e-01 -8.28269243e-01 -2.10574120e-02 -8.69338512e-01 -7.84064159e-02 -2.28356004e-01 3.27280946e-02 5.44812679e-01 7.21775234e-01 -3.96709591e-01 5.27780592e-01 -7.40883768e-01 -4.41900760e-01 5.67256033e-01 -5.86180329e-01 -1.19946124e-02 5.16392469e-01 -1.25094557e+00 1.37402081e+00 8.59366804e-02 -5.11651218e-01 -1.12061119e+00 -7.66192377e-01 -7.35295534e-01 -1.44278780e-01 3.66053164e-01 -1.42184019e-01 1.40750515e+00 -5.80393851e-01 -9.24339771e-01 9.73172605e-01 1.53060690e-01 -7.69657731e-01 4.09657657e-01 -6.44795060e-01 -7.10799277e-01 1.47615433e-01 3.36154938e-01 -1.20907582e-01 9.24622357e-01 -5.42029977e-01 -6.42866194e-01 -3.65392081e-02 2.18492597e-01 -2.44673252e-01 -4.87010688e-01 1.09178591e+00 4.54330593e-01 -1.00468099e+00 -4.76784468e-01 -5.99445522e-01 1.02563038e-01 -6.23552799e-01 -5.48138738e-01 -3.26229930e-01 8.83975208e-01 -1.29681706e+00 1.53666627e+00 -1.77108526e+00 -1.18164849e-02 1.65820122e-03 3.16390604e-01 3.09955567e-01 -2.38321096e-01 5.75180113e-01 2.76085198e-01 5.74466228e-01 4.13412750e-01 -8.71842578e-02 -2.19229504e-01 -6.83214128e-01 -6.15311623e-01 7.35233605e-01 -1.09557301e-01 5.56134284e-01 -8.44246805e-01 -4.78469044e-01 -2.25997325e-02 -5.46323955e-02 -4.38280702e-01 -2.22928464e-01 -1.67365804e-01 2.28910714e-01 -6.90485179e-01 5.35429001e-01 1.05569601e-01 -6.51277378e-02 -7.10941255e-02 -1.24765188e-01 -3.44729066e-01 8.97717834e-01 -2.15312392e-01 1.50429273e+00 -4.15066123e-01 9.79357004e-01 2.04075724e-01 -6.61167443e-01 3.09638709e-01 1.81166083e-01 2.49148961e-02 -6.33486688e-01 3.39769363e-01 5.38953021e-02 1.09087832e-01 -5.47124505e-01 5.44255495e-01 1.34323701e-01 -3.36406142e-01 8.05388689e-01 7.74016082e-02 3.21435094e-01 3.18873763e-01 9.28997338e-01 1.72496915e+00 -1.70178235e-01 5.85311592e-01 -5.83518147e-01 2.31946990e-01 2.46813357e-01 1.71293188e-02 1.34418249e+00 -4.16481465e-01 6.85705319e-02 5.23166478e-01 -7.79933155e-01 -7.33775914e-01 -7.46581972e-01 -1.33928195e-01 1.56578302e+00 -3.20172757e-01 -9.44388866e-01 -3.08548957e-01 -1.36719394e+00 -2.39584237e-01 1.08781338e+00 -9.96455073e-01 1.64645389e-01 -8.39825153e-01 -7.61625648e-01 1.10348988e+00 4.36935157e-01 5.20860493e-01 -9.02983308e-01 -8.17070603e-01 1.55849010e-01 -2.98691869e-01 -1.06086922e+00 -3.53540540e-01 4.78304625e-02 -3.79877687e-01 -1.26316607e+00 -4.46161568e-01 -5.99941850e-01 -1.46594658e-01 2.61326373e-01 9.14162159e-01 8.80661607e-02 -3.93607706e-01 9.82389450e-02 -7.58846283e-01 -5.10079026e-01 -7.33975351e-01 3.99211854e-01 -1.28850669e-01 -6.78152561e-01 2.96268582e-01 -1.28098562e-01 -1.94517210e-01 -2.20882505e-01 -1.79622948e-01 1.98240712e-01 1.47330910e-01 6.30008876e-01 -7.36019731e-01 -2.91181386e-01 4.68334317e-01 -1.00759292e+00 1.09030914e+00 -5.02280653e-01 -1.33313864e-01 1.57802388e-01 -3.48955989e-01 -7.59937763e-02 3.48488629e-01 -1.71870440e-01 -1.21604431e+00 -6.20771348e-01 -1.59956068e-01 1.57176942e-01 1.58133373e-01 7.65643299e-01 6.18221045e-01 -4.03287522e-02 1.48952270e+00 -1.81935772e-01 -2.18596652e-01 -8.68089855e-01 2.99210310e-01 7.13718593e-01 3.30783933e-01 -3.94582897e-01 7.21167684e-01 1.50481477e-01 -6.58145308e-01 -7.10471809e-01 -1.31707454e+00 -5.19969463e-01 -1.76532846e-02 -8.89902376e-03 6.29430532e-01 -8.62633348e-01 -4.22010664e-03 4.74750280e-01 -1.34437442e+00 -1.20110549e-01 2.88483530e-01 4.09975320e-01 -2.69880384e-01 2.96498269e-01 -1.37635565e+00 -9.45305586e-01 -6.40063643e-01 -6.25899076e-01 7.43674636e-01 -2.86783725e-01 -5.78805983e-01 -1.08696222e+00 3.98171574e-01 5.40277839e-01 4.97682691e-01 2.97418445e-01 9.48387623e-01 -1.17341006e+00 3.48645508e-01 -3.43112260e-01 -1.84540018e-01 -6.58437535e-02 -1.03339441e-01 8.66770968e-02 -7.60755897e-01 -1.20758153e-01 1.76978447e-02 -6.47296548e-01 1.49332094e+00 4.08117801e-01 1.04848433e+00 -8.66856813e-01 -4.86252517e-01 1.06848165e-01 6.59928918e-01 -2.60585994e-01 3.19533855e-01 8.04300666e-01 3.50541145e-01 3.78981501e-01 4.56671894e-01 4.96802717e-01 -2.09923625e-01 7.60708928e-01 7.24973977e-02 1.36005759e-01 -1.17356531e-01 -2.34884739e-01 7.12523878e-01 2.84298301e-01 -2.48653352e-01 -4.74868238e-01 -1.09959018e+00 6.65888369e-01 -1.70444834e+00 -1.68728149e+00 -2.59073853e-01 1.51057017e+00 8.33137512e-01 3.05516601e-01 5.25883317e-01 -6.21031560e-02 6.74284995e-01 9.04944599e-01 3.72612983e-01 -8.25092614e-01 5.69955744e-02 3.58416378e-01 4.34735954e-01 6.45550489e-01 -1.68289709e+00 1.09411407e+00 8.25424480e+00 1.23651731e+00 -8.68269503e-01 4.77428973e-01 2.35214189e-01 -5.01865149e-01 -2.16964744e-02 -1.88562125e-01 -7.41981208e-01 4.06022221e-01 1.00865650e+00 -2.09869608e-01 1.62455991e-01 7.10161984e-01 1.75175712e-01 -3.87904011e-02 -8.30601215e-01 3.24116141e-01 3.84520680e-01 -1.86883438e+00 -5.45977131e-02 4.36088182e-02 6.39126539e-01 3.71537894e-01 -4.48115729e-03 6.02326870e-01 6.29783273e-01 -8.51445615e-01 8.80355060e-01 -1.89869761e-01 2.45002821e-01 -4.31003958e-01 6.90507531e-01 5.93200505e-01 -2.44593695e-01 -2.05937505e-01 2.37069353e-01 -5.01428485e-01 4.95339900e-01 4.10006672e-01 -8.83746922e-01 3.43798220e-01 3.73285413e-01 8.36726367e-01 -7.94020176e-01 6.85996652e-01 -5.52997947e-01 1.30901372e+00 -1.43541247e-01 -2.61442631e-01 5.04510939e-01 6.40344560e-01 9.67319787e-01 1.68307006e+00 -7.85590857e-02 -1.08513936e-01 1.67451322e-01 5.91727614e-01 2.29442120e-02 3.06109697e-01 -3.72484088e-01 -3.87159199e-01 4.04687196e-01 1.20610094e+00 -5.75178504e-01 -3.76334757e-01 -1.81806207e-01 5.23744583e-01 4.52198416e-01 1.98648602e-01 -1.04851544e+00 -1.78180709e-01 6.40379414e-02 3.61463249e-01 -9.40827206e-02 -3.14132988e-01 -2.71686047e-01 -1.33550441e+00 -4.65694070e-01 -9.77122068e-01 7.04076409e-01 -2.18291745e-01 -1.35289645e+00 4.53893065e-01 2.58766055e-01 -5.44631660e-01 -3.73135746e-01 -4.29570705e-01 -9.93586898e-01 4.54965770e-01 -6.93343520e-01 -1.19603348e+00 2.11197972e-01 2.33575433e-01 8.58432293e-01 -5.94187260e-01 7.65070438e-01 1.91411525e-02 -4.17750716e-01 5.04441738e-01 -7.03912526e-02 5.07201970e-01 1.05095947e+00 -8.75703096e-01 6.48486197e-01 9.61754560e-01 3.16141218e-01 8.13459456e-01 1.14055991e+00 -9.36121225e-01 -7.72023976e-01 -7.31850982e-01 9.09564972e-01 -7.61896849e-01 1.34881139e+00 -3.98218811e-01 -4.55503911e-01 7.17141330e-01 4.35597688e-01 -6.78131044e-01 6.89531863e-01 1.05836093e+00 -9.27144229e-01 7.04629183e-01 -9.39435959e-01 4.37402487e-01 1.23596859e+00 -5.04462242e-01 -8.96421909e-01 8.73558819e-01 1.47635981e-01 -1.61023438e-01 -3.20117444e-01 3.39357495e-01 7.95483232e-01 -5.35239697e-01 6.43779933e-01 -1.10314596e+00 1.01866758e+00 5.51243603e-01 4.73643579e-02 -1.09897554e+00 -6.24776602e-01 -3.74213398e-01 -5.51063240e-01 9.05483484e-01 4.92945313e-01 -2.47761771e-01 4.59506840e-01 -5.27456030e-02 5.15367137e-03 -3.11175257e-01 -1.00609148e+00 -8.23811769e-01 4.81226385e-01 -1.87656313e-01 -4.19014484e-01 1.23678029e+00 3.40023965e-01 8.57076824e-01 -8.35157692e-01 -3.07962984e-01 3.45212489e-01 -2.02175304e-02 6.77326798e-01 -6.16776407e-01 -2.98723131e-01 -7.13225126e-01 -3.97928238e-01 -7.87795246e-01 2.80231386e-01 -8.30489576e-01 -2.26129323e-01 -1.29562199e+00 6.76600635e-01 6.95178509e-02 -1.06885798e-01 5.33813775e-01 -7.48033971e-02 9.06951502e-02 2.24165529e-01 3.00796360e-01 -7.36033678e-01 2.17595100e-01 5.12466252e-01 -5.22826016e-01 -5.55590391e-02 -1.81913227e-01 -8.52973640e-01 8.64740551e-01 7.96248019e-01 -6.16148591e-01 -8.63542110e-02 -6.67268217e-01 2.19548494e-01 -2.84592092e-01 6.00750804e-01 -8.77435744e-01 -8.01118091e-02 -2.74768502e-01 1.75516590e-01 -6.56352818e-01 -2.53618006e-02 5.66838868e-03 -5.82579792e-01 6.70714557e-01 -8.37543428e-01 -2.11002082e-01 1.73796386e-01 5.44748187e-01 3.13528657e-01 -3.29032451e-01 5.67893624e-01 -1.28510803e-01 -4.99605417e-01 -2.56704479e-01 -1.05808234e+00 2.08394825e-01 8.24515522e-01 3.55748415e-01 -1.18244052e+00 -6.00580931e-01 -7.92263508e-01 -3.56313772e-02 2.59229362e-01 6.26940787e-01 8.74902159e-02 -8.94326031e-01 -1.22137713e+00 -3.63035738e-01 -2.19180807e-02 -1.26606059e+00 -3.13450280e-03 9.76021111e-01 -6.56719446e-01 4.12596405e-01 -1.31992728e-01 -8.31985846e-03 -1.55415463e+00 6.00002885e-01 7.84461945e-02 -6.66394830e-01 -6.58727705e-01 8.65456164e-01 -1.95050195e-01 1.29916921e-01 1.14228986e-01 3.80075723e-01 -3.63352269e-01 1.13966599e-01 1.16901362e+00 7.41810024e-01 3.52841727e-02 -4.54598069e-01 -5.98211467e-01 -3.05276573e-01 -9.54676390e-01 -1.94791779e-01 1.22576845e+00 3.50405574e-01 2.44249150e-01 1.32489532e-01 1.05634570e+00 6.88329935e-01 -1.57721415e-01 -2.11141780e-01 2.54233927e-01 -4.01184380e-01 5.22253215e-01 -1.38466322e+00 -3.34651828e-01 3.88068855e-01 3.17523450e-01 3.89880598e-01 4.78266358e-01 1.10760957e-01 5.83050311e-01 3.37051302e-01 3.99816364e-01 -1.26872694e+00 1.85810998e-01 6.78899050e-01 1.16621506e+00 -9.70056534e-01 7.31394947e-01 -4.10211116e-01 -3.34767789e-01 9.58477557e-01 4.33688194e-01 -3.96152049e-01 5.21486640e-01 4.74817872e-01 1.99514367e-02 -7.27175236e-01 -7.88322091e-01 6.60375431e-02 3.98093492e-01 1.34647369e-01 8.38241220e-01 -1.28820300e-01 -1.26884472e+00 3.38321835e-01 -1.01613514e-01 -2.84287751e-01 4.49891657e-01 1.36914301e+00 -6.82921171e-01 -6.26663685e-01 -2.46425509e-01 7.91330934e-01 -9.65560377e-01 -3.80437464e-01 -1.03098071e+00 8.52387607e-01 -2.48537049e-01 1.11838984e+00 -2.25090757e-01 -7.04978466e-01 -2.46322993e-02 1.48278764e-02 7.53890514e-01 -8.05012524e-01 -1.09452724e+00 -8.25123396e-03 1.14670873e+00 -5.47466934e-01 -4.62891608e-01 -6.77930117e-01 -3.91330272e-01 -7.65826821e-01 -6.39732063e-01 2.89487332e-01 4.44376081e-01 9.32182014e-01 1.93524614e-01 2.49652296e-01 3.89712632e-01 -6.37604535e-01 -1.11714637e+00 -1.61371899e+00 -3.21875423e-01 4.09865111e-01 1.98773921e-01 -5.90397596e-01 -5.92577040e-01 -1.55481398e-01]	[8.469738006591797, 10.676770210266113]
90cdf3ac-8a35-47a0-83b0-1cef9961382b	extractive-summarization-of-call-transcripts	2103.10599	null	https://arxiv.org/abs/2103.10599v2	https://arxiv.org/pdf/2103.10599v2.pdf	Extractive Summarization of Call Transcripts	Text summarization is the process of extracting the most important information from the text and presenting it concisely in fewer sentences. Call transcript is a text that involves textual description of a phone conversation between a customer (caller) and agent(s) (customer representatives). This paper presents an indigenously developed method that combines topic modeling and sentence selection with punctuation restoration in condensing ill-punctuated or un-punctuated call transcripts to produce summaries that are more readable. Extensive testing, evaluation and comparisons have demonstrated the efficacy of this summarizer for call transcript summarization.	['Aleksandr Iakubovich', 'Pratik K. Biswas']	2021-03-19	null	null	null	null	['punctuation-restoration']	['natural-language-processing']	[ 6.05450749e-01 4.33193535e-01 1.15262382e-01 -3.54531884e-01 -1.20224094e+00 -6.87427640e-01 8.05682302e-01 7.57338047e-01 7.94202611e-02 1.17609799e+00 1.39289832e+00 -7.55688474e-02 1.40477344e-01 -1.76273406e-01 4.67211902e-02 -2.64154017e-01 9.48441401e-02 7.15983510e-01 -1.84373274e-01 -3.39489758e-01 9.43719506e-01 2.02178165e-01 -1.17911017e+00 7.03759134e-01 1.25192928e+00 1.93481475e-01 5.41513920e-01 1.17712545e+00 -8.45786810e-01 9.25021887e-01 -1.70334911e+00 -7.14368075e-02 -4.97712791e-01 -9.58044469e-01 -1.31022537e+00 5.68886101e-01 3.00920069e-01 2.07492784e-02 1.36923850e-01 8.00580561e-01 3.51840198e-01 4.90635127e-01 7.01052010e-01 -6.56151414e-01 -1.35452300e-01 1.09051156e+00 -4.63127643e-01 4.88966227e-01 1.03157222e+00 -3.74301016e-01 7.93237746e-01 -5.43031275e-01 9.12987590e-01 1.43129075e+00 5.22476375e-01 3.87589097e-01 -8.49398375e-01 -1.96064740e-01 -1.58770774e-02 -2.94952244e-01 -7.42606044e-01 -4.31346297e-01 6.07925832e-01 -2.22246408e-01 1.72344553e+00 1.02553129e+00 7.68022835e-01 7.44747341e-01 8.31396818e-01 8.21209908e-01 6.20984733e-01 -5.16586244e-01 1.25619560e-01 2.30273649e-01 9.07788277e-01 1.17430441e-01 2.99834967e-01 -9.94940817e-01 -6.31272078e-01 -6.49981678e-01 -1.50337800e-01 -1.14905179e-01 -4.81169038e-02 6.70424879e-01 -1.04871392e+00 8.78013074e-01 -4.75690305e-01 5.12460530e-01 -8.72664154e-01 -2.29978040e-01 1.12138188e+00 2.63589442e-01 8.97930861e-01 6.99649274e-01 -1.54026791e-01 -5.02888560e-01 -1.35999298e+00 3.83246273e-01 1.26520932e+00 1.34453666e+00 2.47043222e-01 2.93774754e-01 -6.32693410e-01 7.52940655e-01 -1.69798642e-01 4.68346506e-01 7.90971935e-01 -7.87947297e-01 8.05390060e-01 6.87798440e-01 3.20811182e-01 -8.06292117e-01 -3.40285212e-01 -2.19136268e-01 -5.84530473e-01 -5.40482819e-01 -7.10654557e-01 -6.11917019e-01 -7.39970386e-01 9.08587039e-01 1.93824600e-02 -6.25239909e-01 5.62991500e-01 1.11847237e-01 1.50036311e+00 1.44620180e+00 1.14577405e-01 -1.15551007e+00 1.42246270e+00 -1.11952448e+00 -1.40485144e+00 -1.35530487e-01 4.61341113e-01 -1.14808643e+00 8.55183840e-01 3.82754445e-01 -1.30538654e+00 -3.34572345e-01 -1.02753437e+00 -2.20618203e-01 -1.86080024e-01 1.43065467e-01 3.62741619e-01 5.07856905e-01 -9.03906107e-01 4.21038151e-01 -4.00897652e-01 -9.35447574e-01 -1.08356215e-02 3.10560197e-01 -2.20538706e-01 4.91805583e-01 -7.17269897e-01 9.04735506e-01 6.95898533e-01 -3.74518692e-01 -2.76107103e-01 -2.94473499e-01 -8.73825133e-01 2.58012474e-01 2.88847893e-01 -8.37215602e-01 1.83346510e+00 -6.23135924e-01 -1.67785537e+00 4.05377656e-01 -7.86461115e-01 -6.08808637e-01 4.79061157e-02 -5.02835870e-01 -3.18607390e-01 4.63814497e-01 2.25742340e-01 2.42070585e-01 5.34949303e-01 -1.25074470e+00 -9.47916627e-01 -2.09526002e-01 -5.15565693e-01 5.53940594e-01 1.44670844e-01 5.32607794e-01 2.16083205e-03 -8.40237260e-01 1.18199863e-01 -4.12527174e-01 7.72836246e-03 -1.71342468e+00 -1.08476090e+00 -5.83881199e-01 1.12229598e+00 -1.17599618e+00 1.65933132e+00 -1.70300293e+00 2.48084646e-02 -2.03822672e-01 4.09266949e-02 3.13355535e-01 2.41136193e-01 1.51693237e+00 4.88045774e-02 4.75001514e-01 -2.83923894e-01 -7.49765456e-01 -2.44235739e-01 1.86932012e-02 -6.75928354e-01 -5.08584194e-02 -1.09336287e-01 6.90491617e-01 -7.32018054e-01 -9.37849343e-01 2.19561145e-01 8.41318741e-02 -7.80012235e-02 1.57610938e-01 -2.24869221e-01 3.92361999e-01 -7.17251241e-01 3.86224449e-01 2.12032214e-01 4.15081859e-01 -8.91276598e-02 -2.31092218e-02 -5.42472541e-01 8.98859560e-01 -7.42188752e-01 1.44622719e+00 -1.31224051e-01 9.93024349e-01 -1.42763168e-01 -6.87885106e-01 1.14381135e+00 6.33504212e-01 2.48591661e-01 -1.48206681e-01 2.38490164e-01 -3.59282494e-02 -5.85462809e-01 -8.03616643e-01 1.37612939e+00 -6.80192262e-02 -5.51088810e-01 7.51989186e-01 -3.82452384e-02 -8.59948158e-01 6.21579707e-01 8.35630059e-01 9.54833984e-01 -4.97815490e-01 9.93728578e-01 -1.67449653e-01 4.43796009e-01 5.90206265e-01 4.35238361e-01 9.15894508e-01 8.28466937e-02 5.79032242e-01 4.72309947e-01 -1.67736858e-02 -1.04536843e+00 -5.76032877e-01 2.90394157e-01 8.75521243e-01 -2.96266824e-01 -9.01578367e-01 -1.14245176e+00 -4.59829777e-01 -5.28108060e-01 1.58805871e+00 -4.28350717e-01 1.08805552e-01 -7.60390282e-01 -1.94338351e-01 2.87251294e-01 4.44746166e-02 4.27737147e-01 -1.41415095e+00 -6.45648897e-01 5.26990175e-01 -6.37331307e-01 -6.81829810e-01 -7.81932712e-01 2.06040457e-01 -1.14445388e+00 -4.88274902e-01 -4.57303077e-01 -9.37654793e-01 5.60161173e-01 3.91678959e-01 8.29379857e-01 -3.33174199e-01 -8.88282433e-02 2.93032587e-01 -7.54144311e-01 -9.79065061e-01 -8.48401427e-01 3.83972615e-01 -1.78443015e-01 -5.28552949e-01 1.10349670e-01 -3.72069269e-01 1.71470679e-02 -5.66903055e-01 -9.74871516e-01 1.02903754e-01 3.09965134e-01 4.46106315e-01 1.87824979e-01 3.81268337e-02 1.00212562e+00 -1.27287197e+00 1.72716188e+00 -3.28162313e-01 3.55921865e-01 4.19202030e-01 -1.69397578e-01 -1.57593172e-02 6.08152866e-01 -2.33920142e-01 -1.50851417e+00 -1.51241630e-01 4.41707745e-02 7.14951038e-01 -2.36617461e-01 7.00072050e-01 1.20128721e-01 7.29333222e-01 5.11852145e-01 6.59813881e-01 -1.45899206e-01 -5.39073050e-01 2.11450383e-01 1.26784396e+00 7.14328468e-01 -1.18142121e-01 2.24244937e-01 1.70788601e-01 -6.79368854e-01 -1.39464235e+00 -6.87019348e-01 -8.58392119e-01 -4.65938956e-01 -3.26014996e-01 5.26372015e-01 -4.88500118e-01 -3.35803688e-01 1.19992122e-02 -1.53750217e+00 3.60835254e-01 -6.68446004e-01 3.87416512e-01 -5.27492166e-01 6.72404647e-01 -4.53023165e-01 -1.01629341e+00 -1.25979424e+00 -5.85833132e-01 1.10005605e+00 6.79455280e-01 -1.34643960e+00 -7.02110052e-01 2.01034859e-01 4.49465722e-01 1.96905658e-01 3.97578478e-01 9.76197958e-01 -1.37592709e+00 3.17437440e-01 -4.78763849e-01 3.61537188e-01 1.79664016e-01 5.07113934e-01 2.89641559e-01 -5.30146897e-01 -2.55908035e-02 4.55991715e-01 -1.88761950e-02 8.58479977e-01 6.14843309e-01 3.81299615e-01 -1.17022789e+00 -4.56239551e-01 -1.57674536e-01 9.27897573e-01 7.32667029e-01 5.27306497e-01 2.45557398e-01 1.07176617e-01 7.84887969e-01 7.25395977e-01 6.07885242e-01 2.83631176e-01 1.40462384e-01 -2.81942517e-01 2.97578007e-01 -2.39196718e-02 -1.49445906e-01 5.25383890e-01 1.29139113e+00 3.15866619e-01 -7.38005996e-01 -4.97705817e-01 6.67328358e-01 -1.79530978e+00 -1.25798118e+00 -4.81506020e-01 1.57741821e+00 9.74491060e-01 1.16386861e-01 1.72077209e-01 2.29877904e-02 8.67931664e-01 3.01337212e-01 -1.89142868e-01 -1.60048831e+00 -1.60303086e-01 -1.32750273e-02 1.06700256e-01 7.94663787e-01 -6.48863316e-01 1.09410954e+00 6.87783766e+00 8.26961100e-01 -7.89591134e-01 -1.25310868e-01 4.00491297e-01 -1.39554337e-01 -4.16232288e-01 2.61858776e-02 -7.65033901e-01 2.32924536e-01 1.06729722e+00 -1.03973603e+00 -2.74246544e-01 6.23118043e-01 8.62602174e-01 -7.85477221e-01 -8.58321905e-01 7.10130095e-01 5.72798967e-01 -1.53215945e+00 6.72637522e-01 -3.55619460e-01 1.05315685e+00 -4.05930817e-01 -4.07427698e-01 2.83951104e-01 2.16192782e-01 -7.05542505e-01 7.89141297e-01 5.80148280e-01 1.20438822e-01 -1.04569280e+00 1.10084558e+00 6.41634643e-01 -8.44017982e-01 1.80216327e-01 -3.80985230e-01 -1.91521779e-01 6.06327116e-01 3.66916299e-01 -1.27908349e+00 7.65799046e-01 2.50680268e-01 4.25131291e-01 -3.36720794e-01 1.00910473e+00 6.76191971e-02 7.61609375e-01 -2.13072985e-01 -4.39589679e-01 3.63885820e-01 -2.82132387e-01 1.31683791e+00 1.88986158e+00 3.11222047e-01 6.42064452e-01 1.79034755e-01 4.54422206e-01 1.09401062e-01 6.08720422e-01 -5.20459950e-01 -2.81519771e-01 7.03433037e-01 1.01345611e+00 -9.82677639e-01 -9.57010567e-01 3.05398166e-01 1.07306421e+00 -3.56440783e-01 3.14562708e-01 -2.55260885e-01 -8.10694396e-01 -2.30394602e-02 -2.00345472e-01 2.44097590e-01 -1.02073871e-01 -5.95508814e-01 -5.14773905e-01 3.56913023e-02 -8.05389643e-01 2.31332034e-01 -8.12362909e-01 -7.43794858e-01 9.40047324e-01 3.77228230e-01 -9.58679199e-01 -5.93158066e-01 6.16315305e-01 -1.41393423e+00 7.55435467e-01 -4.69144017e-01 -8.53558660e-01 3.23105324e-03 -8.52158889e-02 1.56008554e+00 -2.84462720e-01 9.02635872e-01 -4.64064121e-01 -7.09183156e-01 -6.02792054e-02 2.77346909e-01 -4.77910757e-01 3.35524470e-01 -1.40388799e+00 4.95245457e-01 6.38405740e-01 -1.16477162e-01 9.27280366e-01 1.53935230e+00 -1.16924036e+00 -9.13890004e-01 -9.96630192e-01 1.84472215e+00 -1.95640206e-01 1.83341831e-01 -1.67049989e-01 -7.52624452e-01 6.86333776e-01 1.04707992e+00 -1.58612013e+00 7.88949013e-01 -3.32509249e-01 4.63665903e-01 8.01567659e-02 -1.15729821e+00 5.36719263e-01 1.60105914e-01 -1.33255899e-01 -1.67604017e+00 5.58858812e-01 1.06481075e+00 -3.00904363e-01 -3.08831751e-01 -1.94196090e-01 3.14349234e-02 -6.75900459e-01 3.41354638e-01 -4.97667551e-01 2.73595512e-01 3.49089690e-02 2.16278136e-01 -1.57491255e+00 2.04185724e-01 -1.48059833e+00 1.72695130e-01 1.91099060e+00 4.25040722e-01 -3.39277804e-01 4.22153324e-01 4.12943095e-01 -6.80131972e-01 -2.01220781e-01 -7.05952287e-01 -5.30131817e-01 -3.06267679e-01 -1.16081610e-02 3.67690533e-01 5.17396390e-01 8.74390304e-01 9.04847562e-01 -3.64064932e-01 -3.61227840e-01 2.81395257e-01 3.31755839e-02 6.88991606e-01 -1.24354219e+00 7.30340004e-01 -4.38496292e-01 1.72244638e-01 -8.47725213e-01 -1.11235520e-02 -4.34747815e-01 3.49244922e-01 -2.42051673e+00 5.49167633e-01 6.02075458e-01 6.54776037e-01 -5.62976161e-03 -1.50143296e-01 -5.75251043e-01 2.20400020e-01 3.47667307e-01 -8.32719445e-01 4.94620174e-01 9.58247840e-01 -2.08993718e-01 -8.95215094e-01 3.07852089e-01 -1.00196135e+00 6.42557204e-01 1.06730437e+00 -7.93571651e-01 -5.46391904e-01 2.11036876e-01 -5.73152862e-02 4.94691968e-01 -5.22505641e-01 -8.15651953e-01 4.86054510e-01 -1.99705839e-01 -1.07261598e-01 -1.58451176e+00 4.49822471e-02 -2.57115513e-01 1.25261232e-01 4.02363092e-01 -8.42608809e-01 3.48241866e-01 3.94644022e-01 3.51538569e-01 -5.13337433e-01 -7.38847256e-01 2.11643219e-01 -2.88986206e-01 -2.04021782e-01 -4.37937289e-01 -1.17320645e+00 -1.05976738e-01 8.75376344e-01 -7.38936365e-01 -3.04448277e-01 -9.54178095e-01 -6.60805166e-01 2.09317043e-01 3.62679525e-03 2.24252716e-01 6.86133325e-01 -7.28293657e-01 -1.19783342e+00 -2.84006655e-01 -1.74838796e-01 1.06020525e-01 2.24364966e-01 4.19461668e-01 -7.49253333e-01 1.11660123e+00 5.13898470e-02 -1.50608793e-01 -1.80082679e+00 4.89115641e-02 -2.72837758e-01 -4.26776439e-01 -9.35999930e-01 6.36445522e-01 -1.90284893e-01 1.17369788e-02 3.96748334e-01 -5.79966664e-01 -8.69491279e-01 5.13398945e-01 9.90876257e-01 8.03648710e-01 2.80745178e-02 -7.73535132e-01 -7.68330395e-02 1.77473471e-01 -5.38587868e-01 -3.39735001e-01 1.32543504e+00 -8.38364899e-01 -4.05066222e-01 7.95472205e-01 1.14986610e+00 3.07019681e-01 -5.49793720e-01 8.00713226e-02 4.53218132e-01 2.24195257e-01 -2.67258137e-01 -8.50928783e-01 -4.89946939e-02 2.96445042e-01 -3.06850553e-01 7.91385651e-01 8.88582349e-01 1.65279686e-01 1.11193120e+00 7.26922095e-01 -2.66102612e-01 -1.46624339e+00 -6.97694644e-02 8.53427649e-01 1.50352025e+00 -8.83309841e-01 3.91171694e-01 -3.77759278e-01 -1.20874572e+00 1.19530118e+00 3.47004756e-02 8.81463662e-02 9.13044736e-02 1.88025296e-01 -8.03294554e-02 -5.23997188e-01 -1.00466287e+00 1.83546320e-01 1.76589936e-01 6.36144161e-01 5.33075809e-01 9.43458229e-02 -1.03290236e+00 7.67223954e-01 -9.43551123e-01 -4.25935894e-01 1.08312106e+00 1.20594919e+00 -1.14861715e+00 -6.84027195e-01 -5.30925214e-01 6.35156929e-01 -7.15665400e-01 -2.18484327e-01 -1.42514527e+00 6.86528325e-01 -5.02450347e-01 1.72646475e+00 1.05470113e-01 -1.21337511e-01 5.65236449e-01 3.42458934e-01 -1.45925194e-01 -1.42309594e+00 -1.37761807e+00 4.29536700e-01 6.33593798e-01 4.59909178e-02 -3.78466189e-01 -9.71107602e-01 -1.61876631e+00 -4.18471694e-01 -3.70715052e-01 1.08132005e+00 8.69216442e-01 1.07507610e+00 2.73463875e-01 7.46733963e-01 6.21814430e-01 -6.65647149e-01 -4.31053609e-01 -1.63296068e+00 -6.15765572e-01 9.68874916e-02 6.42792344e-01 2.94401646e-01 -2.22018167e-01 5.26512325e-01]	[12.52334213256836, 9.509374618530273]
476449e1-af6d-4b91-a6dd-a636b52ae8dc	whose-hand-is-this-person-identification-from	2011.08900	null	https://arxiv.org/abs/2011.08900v1	https://arxiv.org/pdf/2011.08900v1.pdf	Whose hand is this? Person Identification from Egocentric Hand Gestures	Recognizing people by faces and other biometrics has been extensively studied in computer vision. But these techniques do not work for identifying the wearer of an egocentric (first-person) camera because that person rarely (if ever) appears in their own first-person view. But while one's own face is not frequently visible, their hands are: in fact, hands are among the most common objects in one's own field of view. It is thus natural to ask whether the appearance and motion patterns of people's hands are distinctive enough to recognize them. In this paper, we systematically study the possibility of Egocentric Hand Identification (EHI) with unconstrained egocentric hand gestures. We explore several different visual cues, including color, shape, skin texture, and depth maps to identify users' hands. Extensive ablation experiments are conducted to analyze the properties of hands that are most distinctive. Finally, we show that EHI can improve generalization of other tasks, such as gesture recognition, by training adversarially to encourage these models to ignore differences between users.	['David Crandall', 'Yanwei Fu', 'Satoshi Tsutsui']	2020-11-17	null	null	null	null	['person-identification']	['computer-vision']	[ 1.22158058e-01 -2.48139009e-01 -1.22429766e-01 -3.15956771e-01 -1.98268201e-02 -9.78665173e-01 5.36367953e-01 -8.65947247e-01 -4.29430991e-01 3.35704744e-01 7.62130171e-02 3.46671529e-02 9.07092392e-02 -3.59466195e-01 -3.88844997e-01 -9.02308762e-01 8.33021328e-02 2.79880017e-01 -1.58441558e-01 6.08358979e-02 2.43248358e-01 1.00768661e+00 -1.46671271e+00 2.71288827e-02 1.03281558e-01 4.10854101e-01 -2.50615001e-01 9.31041777e-01 3.59187394e-01 4.36789930e-01 -4.78454083e-01 -5.85299969e-01 4.51894015e-01 -4.91769224e-01 -5.55921555e-01 1.45980999e-01 1.08755267e+00 -8.72461855e-01 -6.44521892e-01 1.08614683e+00 6.75077498e-01 2.24261671e-01 8.86954248e-01 -1.18435371e+00 -5.86020947e-01 9.43148062e-02 -1.00282812e+00 1.40317485e-01 6.50938392e-01 2.38785356e-01 5.86189151e-01 -7.16178417e-01 7.59460330e-01 1.42213905e+00 4.56678510e-01 1.14592910e+00 -9.09802794e-01 -7.97662616e-01 2.51996964e-01 4.55639511e-02 -1.62480664e+00 -7.89088368e-01 8.76508355e-01 -4.68991011e-01 4.21211302e-01 4.72733527e-01 4.57173616e-01 1.57248867e+00 4.10224823e-03 9.10643876e-01 1.03308260e+00 -5.26266634e-01 2.92479303e-02 1.91981420e-01 9.17221531e-02 7.53785610e-01 2.01701656e-01 6.02319278e-02 -6.20996118e-01 -1.64724335e-01 1.05796242e+00 1.83085844e-01 -4.01501775e-01 -4.76999551e-01 -1.14946842e+00 3.14580530e-01 1.92715690e-01 3.38417947e-01 -2.81193733e-01 2.24154592e-01 -6.49915934e-02 1.59303188e-01 7.16255978e-02 2.25102395e-01 -4.89212275e-02 -2.35411420e-01 -5.97519815e-01 1.60261437e-01 7.05665350e-01 1.07595873e+00 2.27775544e-01 -8.21698233e-02 -8.25098995e-03 4.33473885e-01 8.24923664e-02 7.86686718e-01 3.23037475e-01 -9.29044485e-01 2.07400486e-01 4.02671069e-01 2.92642862e-01 -8.65412533e-01 -4.17458713e-01 4.25494947e-02 -5.41235924e-01 5.39368868e-01 1.17726409e+00 -3.99905980e-01 -6.53666317e-01 1.92790890e+00 2.12332562e-01 1.53935626e-02 -1.98155060e-01 1.11029088e+00 4.92088526e-01 -1.75384492e-01 3.29484828e-02 -1.32530406e-01 1.50129163e+00 -4.49160844e-01 -5.05642354e-01 -1.74718603e-01 5.78728095e-02 -6.62366271e-01 1.07230079e+00 3.46758187e-01 -9.05959249e-01 -2.76489168e-01 -6.19347274e-01 2.92340934e-01 -3.59676838e-01 2.23271057e-01 6.20662987e-01 1.42157435e+00 -6.98818624e-01 4.90414262e-01 -7.86106884e-01 -9.00194883e-01 3.19402844e-01 5.57446837e-01 -6.05966866e-01 1.03319444e-01 -7.40126550e-01 7.81530321e-01 -3.95589352e-01 1.78261057e-01 -5.73773444e-01 -1.98452845e-01 -6.29435241e-01 -1.46922246e-01 1.55783936e-01 -5.40983856e-01 1.04567873e+00 -1.28615189e+00 -1.33493817e+00 1.15911376e+00 -7.57287741e-01 3.12516123e-01 8.27733397e-01 -1.82976589e-01 -4.47423339e-01 2.02075511e-01 -1.57527179e-01 5.04540086e-01 1.22288859e+00 -1.25294197e+00 -2.27039546e-01 -1.20322180e+00 2.12606609e-01 3.41707975e-01 -5.02509415e-01 3.79386783e-01 -6.20626986e-01 -4.71475810e-01 4.65267971e-02 -1.13497698e+00 4.08751011e-01 2.59663224e-01 -6.63221836e-01 -7.32707232e-02 1.05739868e+00 -6.83689415e-01 7.00175941e-01 -2.18063807e+00 6.23409338e-02 4.39929634e-01 1.59410208e-01 1.00003682e-01 -5.37892990e-02 8.90745372e-02 3.01212259e-02 -8.48235637e-02 1.11363851e-01 -2.80366272e-01 -1.55984700e-01 2.70983521e-02 -1.76247433e-01 9.23905134e-01 -2.88517833e-01 8.30357373e-01 -7.94793308e-01 -3.38748336e-01 1.47006139e-01 6.64678395e-01 -1.41594738e-01 5.57109080e-02 3.86231631e-01 8.63458157e-01 -4.84989494e-01 8.82720113e-01 7.04215884e-01 9.20664147e-02 3.59047651e-01 -1.48287848e-01 2.12346300e-01 -3.50424260e-01 -1.13630235e+00 1.21198976e+00 -2.85885453e-01 8.63058448e-01 9.89347473e-02 -2.98220098e-01 3.44228625e-01 4.89435077e-01 2.60553807e-01 -4.45083261e-01 1.34157166e-01 -1.70320600e-01 1.95585921e-01 -7.53532767e-01 2.01685712e-01 -1.20769449e-01 3.43318790e-01 8.74260187e-01 -4.22382116e-01 5.42710066e-01 -2.28790641e-01 -1.34934008e-01 7.79534042e-01 1.51631594e-01 1.15497403e-01 2.03925781e-02 4.04447407e-01 -5.46960056e-01 2.73049235e-01 8.20462108e-01 -5.48237860e-01 8.26081038e-01 2.41097122e-01 -2.20635846e-01 -8.39009345e-01 -1.14605212e+00 -1.37644887e-01 1.15542507e+00 3.30130011e-01 2.85247564e-01 -9.76476252e-01 -8.73022914e-01 1.75586313e-01 4.36452419e-01 -8.11618209e-01 6.38121367e-02 -5.85083783e-01 -3.75285268e-01 8.56220424e-01 8.61326575e-01 3.70185345e-01 -1.05482054e+00 -7.88630843e-01 -4.91285831e-01 1.93558708e-01 -9.68969762e-01 -9.57285643e-01 -3.79600018e-01 -4.74572212e-01 -1.31822956e+00 -1.30021727e+00 -5.91498911e-01 1.02822280e+00 4.54241455e-01 7.69585252e-01 -2.28509665e-01 -4.14580584e-01 1.18508685e+00 -1.26948863e-01 -3.08963895e-01 8.52067173e-02 -2.65381187e-01 6.81131542e-01 4.32124972e-01 8.02635968e-01 -4.14305329e-01 -8.78778219e-01 6.07011735e-01 -3.77055556e-01 -5.31622529e-01 1.35664523e-01 4.64985728e-01 1.05832110e-03 -1.36278689e-01 8.10146928e-02 -9.31700945e-01 4.23502207e-01 1.21266373e-01 -7.61237890e-02 5.55972576e-01 2.59197932e-02 -3.99650216e-01 4.56080705e-01 -6.77947283e-01 -1.15263534e+00 2.15663239e-01 3.31970513e-01 -6.22830212e-01 -5.25157332e-01 -4.37248081e-01 -4.11319196e-01 -3.30460519e-01 6.41953588e-01 2.71845311e-01 -1.00591807e-02 -4.91875678e-01 3.32064301e-01 8.85123610e-01 5.28865695e-01 -4.89454746e-01 8.26446235e-01 9.40681815e-01 -1.75749093e-01 -1.46039593e+00 -2.66494930e-01 -6.15809202e-01 -1.02727473e+00 -4.26303118e-01 8.57302248e-01 -6.23621285e-01 -1.26576185e+00 7.38479912e-01 -1.10106564e+00 -1.29974887e-01 -6.00752905e-02 4.90188420e-01 -3.64223808e-01 6.36667311e-01 -2.60225624e-01 -1.30288410e+00 -8.87153074e-02 -9.87949312e-01 1.17826259e+00 4.63637650e-01 -6.18713260e-01 -9.86199975e-01 -1.74288601e-01 1.42437682e-01 1.15187891e-01 1.23376427e-02 5.29851854e-01 -3.66077095e-01 -4.08254951e-01 -4.01966274e-01 -1.29303351e-01 1.08144425e-01 6.26338780e-01 9.01178941e-02 -1.58171415e+00 -4.68398184e-01 -1.64835796e-01 3.88670377e-02 5.29147387e-01 5.04692197e-01 1.07395995e+00 -2.14609265e-01 -5.24572372e-01 6.65013671e-01 9.17630613e-01 5.82259357e-01 5.47554791e-01 -5.58148101e-02 8.60802770e-01 1.04033852e+00 1.76404878e-01 2.40874082e-01 1.27609801e-02 7.85025120e-01 1.42684847e-01 -7.76546448e-03 -5.62807508e-02 -4.37816344e-02 4.50498343e-01 -1.28736109e-01 -8.17417622e-01 -2.05697030e-01 -7.26513386e-01 3.01337808e-01 -1.31634831e+00 -1.18500912e+00 1.90783352e-01 2.29980278e+00 2.55508810e-01 -5.03109574e-01 4.62636501e-01 -7.65025094e-02 1.01124299e+00 -1.39203472e-02 -8.16671789e-01 1.43261356e-02 -8.76587778e-02 1.11905888e-01 5.93423128e-01 3.43466789e-01 -1.22660613e+00 8.18701327e-01 6.45819712e+00 5.85485697e-02 -1.26485395e+00 -8.72856677e-02 4.10274684e-01 -3.28276932e-01 -1.01918407e-01 -3.09296221e-01 -7.48196125e-01 4.35905099e-01 1.28105968e-01 2.90773481e-01 6.83884084e-01 7.44421363e-01 2.77142655e-02 5.32063507e-02 -1.52607059e+00 1.32296693e+00 3.56906950e-01 -5.98142326e-01 -9.03842971e-02 1.93970338e-01 5.10893047e-01 -5.54185867e-01 5.67967117e-01 -2.16810778e-01 4.25522700e-02 -1.26316845e+00 4.30528373e-01 5.70157647e-01 1.04621398e+00 -5.66560507e-01 3.65726292e-01 1.40715122e-01 -1.01676190e+00 -1.04657255e-01 -1.68608546e-01 9.07962993e-02 -1.69131681e-01 -2.72347897e-01 -5.39586842e-01 7.24565331e-03 7.37981915e-01 4.05251890e-01 -6.19178712e-01 5.58060884e-01 4.84097861e-02 1.86124995e-01 -3.64679128e-01 1.31960446e-02 -1.07717507e-01 -1.40174255e-01 7.26872683e-01 1.03633344e+00 1.14379875e-01 2.90600866e-01 -3.48700047e-01 8.11580479e-01 5.83066419e-02 -1.41697064e-01 -9.56084430e-01 1.87641308e-02 2.82285273e-01 9.48784828e-01 -6.16550028e-01 7.67530128e-02 -4.61613536e-01 1.45073783e+00 -2.42968187e-01 7.53650010e-01 -3.76686245e-01 -3.85506511e-01 1.01892900e+00 2.59439349e-01 -4.37384956e-02 -1.85072526e-01 -8.46824721e-02 -1.23215151e+00 2.56908894e-01 -8.70979965e-01 3.16771775e-01 -7.46983767e-01 -1.23340559e+00 3.49408448e-01 -2.77703673e-01 -1.12165689e+00 -4.71395046e-01 -8.57477903e-01 -7.69021451e-01 1.02070737e+00 -8.68022859e-01 -1.35554862e+00 -8.03413153e-01 8.49270701e-01 3.52236390e-01 -4.94916767e-01 8.41916680e-01 8.01823940e-03 -5.67842424e-01 1.05356216e+00 2.04805896e-01 6.78315639e-01 9.03300941e-01 -1.19760621e+00 4.64519978e-01 7.40055263e-01 2.91640878e-01 1.16415012e+00 5.02323806e-01 -4.65721905e-01 -1.74022686e+00 -5.27352393e-01 4.15033221e-01 -1.03673756e+00 2.10234046e-01 -1.86150894e-01 -5.23979127e-01 9.65285420e-01 -1.49494112e-01 -1.44894570e-01 4.80865777e-01 2.89256155e-01 -5.59774518e-01 -7.13081434e-02 -1.22215641e+00 9.61833537e-01 1.22710443e+00 -9.12255764e-01 -2.65987754e-01 2.11759046e-01 -3.89480799e-01 -2.24734873e-01 -3.94188136e-01 7.81187490e-02 1.39625597e+00 -1.00822592e+00 1.19706452e+00 -8.84524167e-01 -9.02750939e-02 -2.40812391e-01 -2.49729589e-01 -8.20629537e-01 1.89879234e-03 -5.69863617e-01 -9.75985304e-02 1.31787252e+00 -2.91797698e-01 -7.27864802e-01 1.20026720e+00 8.47130597e-01 9.09189165e-01 -2.65132517e-01 -8.90394688e-01 -9.40267026e-01 4.42065038e-02 -1.26175642e-01 3.42702299e-01 9.73856568e-01 2.91844620e-03 -4.22790609e-02 -4.18589503e-01 2.21481532e-01 9.33193445e-01 1.17105670e-01 1.01963544e+00 -1.06452358e+00 -2.61798859e-01 -4.57919657e-01 -5.68444252e-01 -8.81783307e-01 2.00158089e-01 -5.18752754e-01 -2.89560527e-01 -8.69866073e-01 4.52776968e-01 -3.43910068e-01 -1.35441825e-01 2.29947388e-01 2.13238262e-02 4.75595266e-01 1.53581694e-01 3.35783124e-01 2.51931157e-02 -2.45458726e-02 1.39418221e+00 -2.64727384e-01 -2.80706942e-01 3.08220267e-01 -6.36958838e-01 9.12116647e-01 5.69212556e-01 6.67149499e-02 -3.46984535e-01 -2.51716852e-01 -2.56710351e-01 -2.71181725e-02 7.27440000e-01 -7.56646395e-01 3.19339871e-01 -2.24533021e-01 8.34978640e-01 -2.55671769e-01 5.40732503e-01 -8.03290129e-01 7.57333264e-02 3.33272547e-01 -9.14740637e-02 -3.87354530e-02 -1.26338705e-01 5.67038655e-01 2.00652629e-01 -2.20079407e-01 9.72895443e-01 -3.75629902e-01 -6.45690203e-01 3.25506538e-01 -3.83292168e-01 -2.01369211e-01 1.03138924e+00 -5.99989355e-01 -2.91727126e-01 -7.09661603e-01 -8.78229439e-01 -1.41924396e-01 8.40244234e-01 4.01478976e-01 6.00848317e-01 -9.34131205e-01 -4.35070425e-01 3.69288504e-01 -1.31299561e-02 -4.84781891e-01 2.85672456e-01 8.85904670e-01 -4.09242064e-01 3.52480352e-01 -4.13825274e-01 -6.94781661e-01 -1.79943967e+00 5.13280213e-01 6.65949583e-01 5.33253729e-01 -7.19188094e-01 9.16105211e-01 6.88806057e-01 -1.57146171e-01 4.23891157e-01 2.55895019e-01 -1.01405233e-01 5.52132428e-02 7.44161308e-01 5.35108507e-01 -3.42781723e-01 -9.07828510e-01 -6.63461447e-01 1.10896540e+00 -1.56101525e-01 -2.16030061e-01 7.75443196e-01 -3.01910881e-02 7.48445764e-02 2.48256058e-01 9.77450132e-01 4.21400458e-01 -1.29705238e+00 -4.16023023e-02 -3.13495040e-01 -9.94571149e-01 -4.47059214e-01 -4.99069631e-01 -1.15121114e+00 1.10150826e+00 1.01614118e+00 -1.80174351e-01 8.27477872e-01 2.76340637e-02 4.88133639e-01 5.67892790e-01 5.09428680e-01 -8.57460678e-01 6.62952438e-02 1.77703500e-01 6.94219410e-01 -1.13129854e+00 -1.11424863e-01 -4.21764046e-01 -7.20887601e-01 1.19403934e+00 6.00991666e-01 2.72650179e-02 5.73574305e-01 9.62535441e-02 3.10880870e-01 -1.35331675e-01 1.74290136e-01 -3.43937844e-01 4.35174495e-01 9.64923322e-01 3.26555669e-01 1.68501511e-01 3.48816693e-01 2.69599855e-01 -2.03176036e-01 -3.60482961e-01 2.86546737e-01 8.91506135e-01 6.52400032e-02 -8.46578002e-01 -6.02721214e-01 3.29819143e-01 -3.41327697e-01 3.61266375e-01 -8.29820454e-01 9.33923602e-01 5.78829050e-02 5.92843235e-01 3.17373604e-01 -4.36583608e-01 2.38491908e-01 4.61975962e-01 1.12755883e+00 -4.03309613e-01 -1.48377165e-01 -2.63408601e-01 -3.19761246e-01 -4.23481733e-01 -5.18897891e-01 -9.77205634e-01 -6.87294245e-01 -6.35657907e-01 -9.86455232e-02 -5.41012466e-01 4.85407621e-01 9.20614064e-01 -1.69021130e-01 -5.41972630e-02 5.62382400e-01 -1.00684857e+00 -4.19611424e-01 -7.32137859e-01 -9.94213223e-01 5.30808330e-01 4.09166902e-01 -7.78929591e-01 -3.76865238e-01 1.31696731e-01]	[6.661126136779785, -0.6248324513435364]
a308808c-dba9-49dc-9586-bbfa3e7ac3d6	a-4d-light-field-dataset-and-cnn	1608.06985	null	http://arxiv.org/abs/1608.06985v1	http://arxiv.org/pdf/1608.06985v1.pdf	A 4D Light-Field Dataset and CNN Architectures for Material Recognition	We introduce a new light-field dataset of materials, and take advantage of the recent success of deep learning to perform material recognition on the 4D light-field. Our dataset contains 12 material categories, each with 100 images taken with a Lytro Illum, from which we extract about 30,000 patches in total. To the best of our knowledge, this is the first mid-size dataset for light-field images. Our main goal is to investigate whether the additional information in a light-field (such as multiple sub-aperture views and view-dependent reflectance effects) can aid material recognition. Since recognition networks have not been trained on 4D images before, we propose and compare several novel CNN architectures to train on light-field images. In our experiments, the best performing CNN architecture achieves a 7% boost compared with 2D image classification (70% to 77%). These results constitute important baselines that can spur further research in the use of CNNs for light-field applications. Upon publication, our dataset also enables other novel applications of light-fields, including object detection, image segmentation and view interpolation.	['Jun-Yan Zhu', 'Ting-Chun Wang', 'Ravi Ramamoorthi', 'Ebi Hiroaki', 'Alexei A. Efros', 'Manmohan Chandraker']	2016-08-24	null	null	null	null	['material-recognition']	['computer-vision']	[ 6.72832310e-01 -3.71644229e-01 9.23411250e-02 -3.86655897e-01 -4.65190858e-01 -5.40656149e-01 5.78517258e-01 -3.33542943e-01 -3.96696515e-02 5.22227943e-01 -6.60938248e-02 -2.30400205e-01 2.03146204e-01 -9.31875706e-01 -1.00083041e+00 -6.71652615e-01 3.94253463e-01 2.34635040e-01 3.71519566e-01 1.40589401e-02 5.35281658e-01 9.01022434e-01 -1.94381404e+00 6.09503984e-01 3.43279511e-01 1.43837309e+00 3.60565633e-01 6.59738481e-01 4.11127843e-02 7.14900732e-01 -4.49701637e-01 -1.56211585e-01 6.12017334e-01 5.39521910e-02 -8.28780949e-01 3.61403674e-01 1.50171876e+00 -9.76490200e-01 -5.00777781e-01 8.28038990e-01 6.29718482e-01 8.16688582e-04 7.19786525e-01 -6.77459598e-01 -1.06174231e+00 3.12158698e-03 -4.74007308e-01 4.07241404e-01 5.50551713e-01 5.36304832e-01 8.39093983e-01 -1.02221394e+00 6.82617486e-01 8.84603858e-01 4.97626424e-01 6.99640036e-01 -1.16722345e+00 -4.70555544e-01 -1.68407992e-01 4.50404286e-02 -7.73254514e-01 -6.54425204e-01 1.06892073e+00 -5.89024246e-01 1.41411233e+00 -2.64565051e-02 7.91465402e-01 8.64085495e-01 3.34411800e-01 9.17593598e-01 1.44336104e+00 -6.35399342e-01 6.88754469e-02 -1.60472944e-01 -2.35770606e-02 7.75867879e-01 1.82326764e-01 3.32184315e-01 -3.89725506e-01 2.19261885e-01 1.02133214e+00 1.27231091e-01 -3.87881905e-01 -2.12351099e-01 -1.26950991e+00 3.62104833e-01 5.54848433e-01 8.46678466e-02 -1.23107232e-01 1.85635045e-01 -7.50705078e-02 2.31861964e-01 8.29219580e-01 6.33727193e-01 -4.21777129e-01 2.23224342e-01 -7.25872874e-01 2.14111432e-01 4.34151620e-01 9.40358639e-01 1.09973979e+00 1.57429621e-01 9.96196866e-02 9.47796762e-01 9.78119671e-02 8.29787493e-01 -1.71381891e-01 -1.17398989e+00 2.77695119e-01 5.89766264e-01 1.40655190e-01 -6.26602352e-01 -5.89623332e-01 -1.30396158e-01 -4.97828573e-01 6.07656002e-01 7.92341232e-01 1.90986738e-01 -1.12211609e+00 1.12062716e+00 9.15486515e-02 4.83822934e-02 -2.49241680e-01 1.05023324e+00 1.35055482e+00 5.10415375e-01 -5.66365778e-01 9.15602818e-02 1.11796772e+00 -8.13659787e-01 -2.16057464e-01 -2.27822319e-01 1.48468927e-01 -1.30556786e+00 9.47213888e-01 6.65293694e-01 -1.53917074e+00 -5.78770339e-01 -9.79672313e-01 -3.47088814e-01 -3.80661815e-01 1.63059473e-01 1.12331617e+00 4.52468932e-01 -9.70549345e-01 4.84592378e-01 -3.97317737e-01 -4.85660821e-01 8.86764944e-01 4.25846100e-01 -1.57662243e-01 -4.83223647e-01 -6.01814687e-01 5.60718060e-01 -2.32109472e-01 -1.65763780e-01 -9.57614124e-01 -1.02493930e+00 -4.19473439e-01 -4.11353528e-01 1.97797433e-01 -8.63621712e-01 1.10697985e+00 -7.76691020e-01 -1.42508554e+00 1.52585673e+00 -7.73605853e-02 -7.36645758e-02 4.36878949e-02 5.03648669e-02 -3.06987584e-01 3.90024036e-01 9.68473498e-03 7.50157118e-01 9.40834880e-01 -1.47560620e+00 -7.46453822e-01 -3.59329551e-01 4.88521993e-01 -6.95886239e-02 8.65925625e-02 -3.90256499e-03 -2.95365125e-01 -4.69740450e-01 3.66612449e-02 -1.02764809e+00 2.05245733e-01 2.63294697e-01 -3.88430953e-01 -2.47424677e-01 6.33988500e-01 -3.38012695e-01 3.80008131e-01 -1.88183808e+00 -4.02876467e-01 -2.22967044e-01 5.46056986e-01 2.77677298e-01 -1.11950666e-01 1.73982903e-01 -1.31944969e-01 -2.50730544e-01 -4.19229232e-02 -1.28510386e-01 -3.23404551e-01 -9.41112265e-02 -2.75533587e-01 6.16234422e-01 3.60730410e-01 9.60902035e-01 -6.52905226e-01 -9.42787603e-02 7.64095008e-01 4.43674803e-01 -6.95613384e-01 1.54084995e-01 -5.91755033e-01 4.47831064e-01 -1.21692337e-01 1.12231755e+00 1.11358988e+00 -4.86904323e-01 -3.20921838e-01 -7.89898098e-01 -2.09276214e-01 3.56278330e-01 -6.83398068e-01 1.76935160e+00 -6.93269551e-01 1.16072381e+00 1.19770505e-01 -6.97279811e-01 7.54770756e-01 -5.89314848e-02 8.89834881e-01 -9.28547382e-01 2.17254713e-01 1.43873796e-01 -2.17996716e-01 -5.15959203e-01 3.45584959e-01 -2.74430569e-02 6.83645308e-01 7.49716997e-01 1.74009144e-01 -5.43211222e-01 2.90349051e-02 -2.08652228e-01 9.27080810e-01 4.90827300e-02 -2.46125758e-01 -2.75350153e-01 1.69393688e-01 -2.81278044e-01 -3.92150618e-02 8.44931364e-01 -1.92480132e-01 1.03772056e+00 -2.82182544e-01 -1.06645107e+00 -1.22968256e+00 -1.06861663e+00 -6.04174197e-01 9.98539269e-01 2.32442066e-01 2.24713519e-01 -4.15579081e-01 -6.06979012e-01 2.24848762e-01 2.86356717e-01 -4.64418560e-01 3.42048705e-01 -7.21515477e-01 -8.76883328e-01 3.52146849e-02 5.74600637e-01 6.26625359e-01 -9.53553081e-01 -4.42970306e-01 -8.11196566e-02 -2.61350535e-03 -1.34219706e+00 -1.67790443e-01 3.61919969e-01 -7.38424003e-01 -1.36450696e+00 -7.85903573e-01 -1.00056612e+00 5.52953362e-01 6.90170228e-01 1.66245806e+00 4.51261178e-03 -6.00294650e-01 8.03049743e-01 -2.68430114e-02 -4.80463326e-01 -1.99312940e-01 -7.35611841e-02 -1.26747295e-01 -9.18580145e-02 7.44590104e-01 -6.73333645e-01 -1.12605548e+00 3.29312831e-01 -6.71377778e-01 1.72308043e-01 6.36223316e-01 7.42526710e-01 4.85512793e-01 -1.72898993e-01 8.62486586e-02 -6.58456624e-01 2.08282128e-01 -6.97831511e-02 -7.21481621e-01 9.85041261e-02 -4.17603344e-01 -2.64775425e-01 5.10783076e-01 -2.10647210e-01 -1.23835492e+00 7.79442443e-03 -2.20498383e-01 -4.23464179e-01 -8.05346072e-01 -4.22373772e-01 2.62942582e-01 -7.08409429e-01 9.35355008e-01 9.82319489e-02 -2.34616846e-01 -4.68312800e-01 3.00576478e-01 6.14380777e-01 3.98611486e-01 -6.38440490e-01 5.48643827e-01 9.83130395e-01 4.23254043e-01 -1.07505298e+00 -1.08119226e+00 -5.01203656e-01 -6.28650904e-01 -3.69840384e-01 9.45266604e-01 -9.18839335e-01 -1.08264387e+00 7.41834104e-01 -1.31599402e+00 -5.28393090e-01 -3.39610189e-01 3.40028465e-01 -6.74710035e-01 2.27706656e-01 -9.03844059e-01 -6.26264989e-01 -2.56177276e-01 -1.25340652e+00 1.46327245e+00 9.76310521e-02 2.88265467e-01 -9.83363450e-01 -1.76313534e-01 8.15947413e-01 3.33084911e-01 4.96624410e-02 1.01447451e+00 2.35591516e-01 -1.27769911e+00 1.51729167e-01 -6.43994331e-01 5.42579174e-01 3.86519134e-01 7.48353973e-02 -1.59564114e+00 -2.30537325e-01 -1.87981632e-02 -6.87234044e-01 1.18209779e+00 8.39295924e-01 1.39554405e+00 2.47027412e-01 -2.03275219e-01 9.15711522e-01 1.46202791e+00 3.23781252e-01 8.12350094e-01 2.84153342e-01 9.55988228e-01 4.09733593e-01 1.16830999e-02 2.42975861e-01 1.57807797e-01 6.75889015e-01 5.65869033e-01 -4.71931189e-01 -8.86067748e-01 1.59279212e-01 -7.94537440e-02 4.95289862e-01 -4.64560866e-01 -3.68553162e-01 -7.25400865e-01 3.04168791e-01 -1.00104499e+00 -1.14203918e+00 -2.06690729e-01 1.97827578e+00 7.01937854e-01 4.49584238e-02 7.67356297e-03 1.24015845e-01 3.93484861e-01 2.50299662e-01 -7.99895346e-01 -8.16870481e-02 -3.43099058e-01 4.79661584e-01 7.28774309e-01 6.28186107e-01 -1.23250639e+00 7.89173782e-01 7.63585854e+00 5.92215538e-01 -1.51341343e+00 -2.81635612e-01 7.78942227e-01 -1.11133881e-01 -4.02847111e-01 -3.72819692e-01 -9.70416427e-01 3.93748015e-01 3.24074142e-02 7.88482785e-01 1.00452709e+00 6.41430557e-01 -9.69144627e-02 -2.28336126e-01 -1.35542226e+00 1.35245991e+00 3.58408123e-01 -1.53070617e+00 -3.40623036e-02 5.64279035e-03 1.16083848e+00 5.26681185e-01 3.28902870e-01 -4.04094398e-01 2.03790009e-01 -8.74654174e-01 5.29303968e-01 5.31985164e-01 1.13553321e+00 -2.65007079e-01 2.37427905e-01 -1.52742371e-01 -8.81669581e-01 6.58996478e-02 -6.14105523e-01 1.29914228e-02 -1.15566989e-02 8.75805497e-01 -1.00664818e+00 2.25711703e-01 1.01605546e+00 1.21914649e+00 -6.69003665e-01 8.54785860e-01 1.76288068e-01 5.97596347e-01 -3.53987485e-01 3.31831276e-02 -8.80498663e-02 -1.22719787e-01 4.84891027e-01 1.03299975e+00 9.53210331e-03 -1.28079563e-01 4.71028276e-02 1.27352262e+00 -3.22592407e-01 -4.15904909e-01 -9.06570137e-01 6.46460578e-02 -1.08219333e-01 1.17707276e+00 -7.81772792e-01 -1.62907615e-01 -9.59255099e-01 6.43119335e-01 1.18109263e-01 5.75517356e-01 -3.29699695e-01 -2.11135492e-01 5.95815599e-01 5.62198579e-01 2.87104577e-01 -3.03472281e-01 -5.93902886e-01 -1.29648912e+00 9.39040408e-02 -5.33639312e-01 -1.68262161e-02 -1.43627799e+00 -1.96991825e+00 3.76160175e-01 -2.09444925e-01 -1.10517931e+00 2.25020111e-01 -1.33329940e+00 -3.09627175e-01 7.58237243e-01 -1.94750440e+00 -1.32753789e+00 -5.51838219e-01 6.91731989e-01 5.31657517e-01 -2.34650940e-01 5.62453270e-01 3.72132719e-01 -6.37822598e-02 1.02979891e-01 2.66133130e-01 4.30942737e-02 7.50101805e-01 -1.28191853e+00 4.80483264e-01 5.55899501e-01 -7.29697570e-03 4.00122523e-01 2.92656302e-01 -4.04399782e-01 -1.62937295e+00 -9.08464551e-01 3.69346321e-01 -1.02062249e+00 2.01628581e-01 -4.41333532e-01 -5.62394679e-01 7.11066067e-01 4.10049766e-01 9.18560028e-02 5.63990951e-01 1.28813967e-01 -3.39006990e-01 -4.53859657e-01 -1.08080781e+00 4.03121352e-01 1.32775581e+00 -7.36263990e-01 -2.83295155e-01 8.06911111e-01 4.43963528e-01 -5.92227280e-01 -8.72340083e-01 6.38174653e-01 5.93929052e-01 -1.40753102e+00 1.40701067e+00 -2.16446429e-01 7.10483909e-01 -6.95715547e-02 -3.13014716e-01 -9.47916090e-01 -4.27184731e-01 -3.36524963e-01 3.41895334e-02 8.70095968e-01 1.55845359e-01 -6.22325063e-01 1.17370033e+00 4.97035801e-01 -4.15474981e-01 -7.39091337e-01 -4.58944678e-01 -4.91698802e-01 1.39546409e-01 -5.05811155e-01 5.22767603e-01 8.17303300e-01 -8.45214188e-01 3.27127069e-01 -2.78317899e-01 -9.56764221e-02 7.81419754e-01 7.15204000e-01 8.64046872e-01 -1.23777485e+00 -2.84471482e-01 -5.80574214e-01 -1.45154193e-01 -1.53793776e+00 6.80878088e-02 -1.05845344e+00 -1.14311643e-01 -1.69202089e+00 2.31277898e-01 -5.79345167e-01 -4.93605845e-02 3.37194264e-01 1.59336552e-01 7.25506544e-01 4.81130853e-02 2.08909199e-01 -5.93505442e-01 2.71977156e-01 1.86136067e+00 -5.34999073e-01 -2.11473573e-02 -9.95657686e-03 -4.88209099e-01 5.98718703e-01 5.11002243e-01 8.24592412e-02 -2.21299112e-01 -9.54663813e-01 2.80769169e-01 -4.19864982e-01 5.43373525e-01 -1.14851868e+00 -3.43777961e-03 -2.96802878e-01 9.43685055e-01 -7.83461809e-01 6.85694993e-01 -7.87700295e-01 -2.55609185e-01 -5.60486019e-02 -4.82110009e-02 -3.91921997e-01 2.30522126e-01 2.46576130e-01 5.30571342e-02 6.40611276e-02 9.46436644e-01 -6.41972303e-01 -7.25353956e-01 4.90972757e-01 -3.88994962e-01 1.35914385e-01 6.77733898e-01 -3.20288658e-01 -8.24929595e-01 -2.91608006e-01 -3.72666568e-01 -4.14640844e-01 8.21050644e-01 9.93867368e-02 7.53814816e-01 -1.36179972e+00 -4.11766648e-01 6.18381739e-01 2.52121836e-01 2.07657665e-01 2.49044538e-01 3.19763958e-01 -8.61043930e-01 5.53339899e-01 -3.63655686e-01 -1.00072300e+00 -9.39556956e-01 6.26273751e-01 5.42305470e-01 4.12995487e-01 -6.32675529e-01 9.60185766e-01 4.95931059e-01 -2.23886773e-01 3.44944298e-02 -7.06713796e-01 9.92406979e-02 -4.82766479e-01 4.08713192e-01 4.25302744e-01 5.05355179e-01 -3.02871019e-01 -2.13819385e-01 1.14434588e+00 4.31276439e-03 3.56772363e-01 1.57545078e+00 1.76758077e-02 -1.60288692e-01 2.59757131e-01 1.26424980e+00 1.60925165e-01 -1.40962362e+00 -3.16395074e-01 -8.37352931e-01 -8.82151365e-01 3.52365464e-01 -9.96765733e-01 -1.36535752e+00 1.17408085e+00 7.54034936e-01 3.00957948e-01 1.37590015e+00 2.49451399e-01 9.66620207e-01 5.16499639e-01 3.25651109e-01 -9.97167647e-01 3.52615625e-01 4.77371871e-01 7.52374232e-01 -1.59688079e+00 1.40414853e-02 -6.16128325e-01 5.89843504e-02 1.37009990e+00 8.56220484e-01 -2.05169573e-01 8.03073168e-01 2.72839248e-01 1.23653285e-01 -5.46261311e-01 -5.51500618e-01 -3.14566761e-01 5.24926126e-01 9.53659058e-01 5.27520478e-01 -1.63861975e-01 5.44090986e-01 -2.52460778e-01 -3.53288762e-02 -2.83545256e-03 3.59130681e-01 7.52703786e-01 -4.30175781e-01 -8.92769039e-01 -2.10472450e-01 7.08991647e-01 -3.93379509e-01 -2.02069238e-01 -3.28424931e-01 3.67164671e-01 3.91556054e-01 9.50962543e-01 3.44487548e-01 -3.21703434e-01 3.46069932e-01 -2.43880570e-01 1.17952394e+00 -6.03252232e-01 -2.61572838e-01 3.49946022e-02 -7.30284601e-02 -5.14508009e-01 -9.26462173e-01 -3.58617723e-01 -5.02498090e-01 -5.19305527e-01 -3.50027323e-01 -7.99948215e-01 5.73233485e-01 6.10167503e-01 1.76997781e-01 2.74642676e-01 7.09641457e-01 -1.35929251e+00 1.79823890e-01 -7.13846803e-01 -4.90170985e-01 6.05712235e-01 5.78958154e-01 -8.04691434e-01 -4.28086817e-01 2.10656077e-01]	[9.627568244934082, -2.7028849124908447]
a59fb0b0-3b7a-43bf-8b8a-7b5a115eebba	patch-drosonet-classifying-image-partitions	2305.05256	null	https://arxiv.org/abs/2305.05256v1	https://arxiv.org/pdf/2305.05256v1.pdf	Patch-DrosoNet: Classifying Image Partitions With Fly-Inspired Models For Lightweight Visual Place Recognition	Visual place recognition (VPR) enables autonomous systems to localize themselves within an environment using image information. While Convolution Neural Networks (CNNs) currently dominate state-of-the-art VPR performance, their high computational requirements make them unsuitable for platforms with budget or size constraints. This has spurred the development of lightweight algorithms, such as DrosoNet, which employs a voting system based on multiple bio-inspired units. In this paper, we present a novel training approach for DrosoNet, wherein separate models are trained on distinct regions of a reference image, allowing them to specialize in the visual features of that specific section. Additionally, we introduce a convolutional-like prediction method, in which each DrosoNet unit generates a set of place predictions for each portion of the query image. These predictions are then combined using the previously introduced voting system. Our approach significantly improves upon the VPR performance of previous work while maintaining an extremely compact and lightweight algorithm, making it suitable for resource-constrained platforms.	['Shoaib Ehsan', 'Klaus D. McDonald-Maier', 'Michael Milford', 'Bruno Ferrarini', 'Bruno Arcanjo']	2023-05-09	null	null	null	null	['visual-place-recognition']	['computer-vision']	[ 1.41302601e-01 -1.23858124e-01 -2.09913164e-01 -3.61397803e-01 -1.17612079e-01 -6.57759964e-01 7.05060601e-01 1.33875817e-01 -6.71285868e-01 4.63288605e-01 -6.01886213e-02 -3.96758288e-01 2.23366126e-01 -8.97138298e-01 -7.76885390e-01 -4.93559927e-01 -1.36265783e-02 1.11551262e-01 6.44099951e-01 -2.23452851e-01 5.51915944e-01 9.19748664e-01 -1.92594600e+00 2.42095426e-01 3.73533666e-01 1.17387307e+00 6.17793322e-01 6.70020521e-01 -6.84573278e-02 8.30053449e-01 -5.00555277e-01 1.59679994e-01 3.12963396e-01 -1.66198805e-01 -4.84718859e-01 -3.79009873e-01 5.05704820e-01 -2.28217334e-01 -5.75775206e-01 6.34705663e-01 4.62066412e-01 2.71730274e-01 4.57296103e-01 -1.28702939e+00 -5.95060885e-01 1.95831642e-01 -2.52675563e-01 1.14607856e-01 1.71036750e-01 4.76446748e-02 8.93992841e-01 -9.18263078e-01 8.24145675e-01 6.49191439e-01 8.77617896e-01 6.99964881e-01 -1.10960722e+00 -5.63782930e-01 1.21467397e-01 1.50810361e-01 -1.54798710e+00 -6.79663837e-01 5.58712840e-01 -2.27246910e-01 1.59086394e+00 1.46031439e-01 8.01224291e-01 8.64985287e-01 3.12557131e-01 6.84195399e-01 8.85723114e-01 -2.77803928e-01 6.08790874e-01 -1.83661897e-02 -5.46831489e-01 8.07591796e-01 1.15067869e-01 1.30961284e-01 -7.48345137e-01 9.90617573e-02 1.01899397e+00 2.11652637e-01 -1.01778023e-01 -8.84518623e-01 -1.24392712e+00 6.74297333e-01 1.20982003e+00 3.47501189e-01 -2.68334627e-01 4.77767408e-01 1.98609710e-01 7.58893276e-03 9.33037177e-02 4.27110404e-01 -2.41462260e-01 6.92360774e-02 -1.35505807e+00 1.74443096e-01 7.09961534e-01 8.81785452e-01 9.75724518e-01 -1.24926016e-01 -4.63007577e-03 5.93995392e-01 5.87217033e-01 1.22473150e-01 5.34820378e-01 -8.27376485e-01 2.44010329e-01 8.02441657e-01 6.95132986e-02 -1.00435984e+00 -4.32351887e-01 -2.49330431e-01 -4.52974290e-01 5.20693421e-01 1.78379908e-01 2.03819409e-01 -1.20467210e+00 1.38517046e+00 1.99261159e-01 2.32657149e-01 2.15028450e-01 8.77705514e-01 8.78804326e-01 6.56093478e-01 6.34762645e-02 6.61810040e-01 1.02446425e+00 -1.28482676e+00 3.67838331e-03 -5.51782310e-01 5.40766716e-01 -5.89794159e-01 5.43996453e-01 1.39773518e-01 -5.71144640e-01 -3.67999822e-01 -1.50497949e+00 -3.11224163e-01 -9.52534437e-01 2.76569426e-01 7.02433467e-01 5.76703846e-01 -1.57504165e+00 6.99242651e-01 -7.91335404e-01 -7.50489652e-01 7.19139993e-01 6.22417271e-01 -5.67218304e-01 9.61488485e-03 -6.23908579e-01 1.15390229e+00 3.69189262e-01 1.19747743e-01 -1.02695918e+00 -3.63828391e-01 -1.06710124e+00 5.40828845e-03 -1.11688428e-01 -4.35654998e-01 1.21931708e+00 -7.90666401e-01 -1.47504711e+00 8.98310781e-01 -1.71485245e-01 -8.08863580e-01 4.23948497e-01 8.80267620e-02 -1.66849017e-01 1.99947581e-01 5.83954193e-02 1.36419511e+00 6.72251463e-01 -1.20740509e+00 -8.19736898e-01 -1.29857957e-01 1.22041307e-01 1.96304768e-01 -2.23068465e-02 -9.31056142e-02 -5.98808110e-01 -2.85960823e-01 2.44730189e-01 -8.90456796e-01 -4.30031866e-01 4.87086445e-01 -1.00702889e-01 -6.99066669e-02 1.00333107e+00 -2.44246498e-01 7.92615473e-01 -2.22882438e+00 -2.86428154e-01 2.18672574e-01 3.63082141e-01 3.28357220e-01 -1.72095433e-01 5.51162660e-01 1.40164152e-01 4.04037572e-02 -1.71912432e-01 -3.26294899e-01 -8.47252160e-02 3.72725695e-01 -3.75597060e-01 7.03870296e-01 3.72328103e-01 8.89189899e-01 -8.94484043e-01 -3.78510773e-01 6.42148852e-01 5.65695822e-01 -5.27507961e-01 -3.29426788e-02 -2.17597097e-01 3.29767525e-01 -3.69446844e-01 7.81585455e-01 5.01336396e-01 -2.03555390e-01 1.27779335e-01 3.52404304e-02 -6.96135998e-01 3.18607807e-01 -7.98466444e-01 1.78526175e+00 -5.95568299e-01 9.55108345e-01 -6.27822578e-02 -9.51932132e-01 1.20554328e+00 3.98073904e-02 3.10760498e-01 -7.60815561e-01 2.10720509e-01 4.21233267e-01 -9.02905017e-02 -1.03869893e-01 7.32671261e-01 3.10579896e-01 -1.07698385e-02 1.66335717e-01 3.69987756e-01 1.52372628e-01 9.00858641e-02 -1.48524418e-01 1.41917622e+00 5.33752203e-01 4.45410818e-01 -1.96267605e-01 2.80461460e-01 2.20522925e-01 3.03196490e-01 8.44994009e-01 -4.84208614e-01 9.15451944e-01 4.48107980e-02 -9.37064469e-01 -1.24661303e+00 -8.15728486e-01 -8.43428448e-02 1.08748317e+00 4.63006765e-01 -3.49102080e-01 -5.38499415e-01 -5.62888205e-01 6.57618642e-02 4.42739487e-01 -8.96925628e-01 1.34408608e-01 -6.24341667e-01 -2.45550826e-01 6.52439356e-01 7.83086419e-01 8.20592284e-01 -1.34346974e+00 -1.47072566e+00 3.27565432e-01 1.95361167e-01 -8.38911295e-01 5.45712002e-02 7.12437510e-01 -6.49563789e-01 -8.00600350e-01 -7.20253050e-01 -1.03676438e+00 6.74161017e-01 5.70167184e-01 8.78085256e-01 1.52422518e-01 -2.63393760e-01 2.25185588e-01 -4.14573044e-01 -4.06761885e-01 9.42848921e-02 3.04815531e-01 -1.48045551e-02 -9.88772288e-02 4.01987493e-01 -6.61370337e-01 -7.90260792e-01 2.94824541e-01 -6.80463314e-01 1.02775982e-02 7.14881182e-01 7.40239918e-01 7.36591458e-01 -3.77060533e-01 1.17081493e-01 -3.95612925e-01 2.75919259e-01 -4.95981306e-01 -7.37397134e-01 3.70923430e-01 -4.00612861e-01 6.22788891e-02 6.20553911e-01 -3.97133052e-01 -6.54372394e-01 5.55073678e-01 1.11675989e-02 -5.53130507e-01 -2.34759852e-01 3.07217270e-01 1.82412803e-01 -7.05203831e-01 7.83713341e-01 4.75495368e-01 -1.78666100e-01 -2.00022057e-01 3.10807467e-01 7.03628600e-01 6.41362846e-01 -8.67924988e-02 6.48202300e-01 5.47593653e-01 -5.74750490e-02 -8.40372920e-01 -3.47145468e-01 -5.83197594e-01 -7.68912554e-01 -3.10417205e-01 8.52487266e-01 -8.31745863e-01 -7.33565390e-01 2.37985387e-01 -1.12169778e+00 -4.81476396e-01 -6.21685721e-02 2.75553316e-01 -5.95566034e-01 -1.82575166e-01 -1.91749126e-01 -6.58337355e-01 -2.45562211e-01 -1.13718462e+00 1.10742116e+00 6.37249172e-01 -3.19302797e-01 -7.50864387e-01 3.09662968e-01 9.93677042e-03 7.26418495e-01 2.13188216e-01 2.09818587e-01 -7.36062407e-01 -7.44657516e-01 -3.08726102e-01 -3.06305528e-01 -8.86591673e-02 -1.52190521e-01 4.61505502e-02 -1.19349563e+00 -1.62489593e-01 -4.58164155e-01 -3.41329604e-01 9.68199492e-01 1.11203872e-01 1.10147595e+00 -9.04593095e-02 -8.27456713e-01 7.39813685e-01 1.63656509e+00 3.66298467e-01 7.29345560e-01 9.57589507e-01 4.42966342e-01 1.95464164e-01 4.17806923e-01 3.66375774e-01 3.90023589e-01 5.76762021e-01 9.08416748e-01 -1.89294755e-01 -7.46883452e-03 -4.19161290e-01 1.65911630e-01 1.97998166e-01 -8.05966407e-02 -2.98250765e-01 -1.07194197e+00 8.15981507e-01 -2.02279854e+00 -7.86853492e-01 3.75949264e-01 2.07792974e+00 2.87809074e-01 -1.79482564e-01 -3.07235986e-01 -1.61610797e-01 6.03423119e-01 3.74721646e-01 -7.20914483e-01 -4.68638241e-01 9.46244970e-03 4.28634495e-01 8.64444554e-01 -9.69833210e-02 -1.41107047e+00 1.09210956e+00 6.80305529e+00 4.68409181e-01 -1.51285613e+00 -1.69469565e-01 2.99414098e-01 -4.48747650e-02 9.07064080e-02 -9.82600227e-02 -7.26122022e-01 1.82961524e-01 9.46273446e-01 2.03116953e-01 5.56512594e-01 1.26811838e+00 -1.50382951e-01 -3.68649185e-01 -1.01788580e+00 9.78035748e-01 1.99956954e-01 -1.68889725e+00 -2.37970948e-01 1.61907151e-01 5.56413651e-01 6.83352768e-01 1.74110264e-01 1.73443571e-01 3.60853761e-01 -1.29252434e+00 9.70295072e-01 3.10063630e-01 6.53872132e-01 -6.28297091e-01 6.37449503e-01 2.05372304e-01 -1.29595613e+00 -2.38253206e-01 -5.73461771e-01 -1.65106520e-01 -2.96074182e-01 -9.43037570e-02 -1.08407664e+00 2.70726889e-01 9.50142264e-01 6.21189356e-01 -6.84535742e-01 1.39067221e+00 -2.92794883e-01 2.25797027e-01 -5.14633656e-01 -3.87529075e-01 5.69635034e-01 1.52236387e-01 1.73562482e-01 1.07305288e+00 5.17951071e-01 -2.45318696e-01 2.40189433e-02 8.16461504e-01 -1.89997613e-01 1.19965533e-02 -1.01360452e+00 7.72218108e-02 7.44801044e-01 1.51332879e+00 -1.02180135e+00 -2.86180496e-01 -4.19631213e-01 1.06630468e+00 6.70258641e-01 6.14069663e-02 -6.97745919e-01 -5.75811446e-01 7.38238096e-01 -3.23864333e-02 8.36481571e-01 -3.31124514e-01 -3.47933769e-01 -9.43375468e-01 3.74508393e-03 -3.84927124e-01 -4.34272410e-03 -8.44287276e-01 -7.76161432e-01 7.89108634e-01 -4.30122107e-01 -1.45727181e+00 -8.04109275e-02 -8.69117200e-01 -6.77670181e-01 6.76507950e-01 -1.57532883e+00 -1.34850740e+00 -4.01535273e-01 4.65098351e-01 3.08570266e-01 -1.76578909e-01 1.08593953e+00 -2.12276448e-02 -4.23371255e-01 4.06621784e-01 2.53914267e-01 3.36905181e-01 6.29046321e-01 -1.08089113e+00 6.24178827e-01 8.10715795e-01 3.55404794e-01 9.33166027e-01 5.27494431e-01 -4.44750696e-01 -1.31410193e+00 -1.28623593e+00 8.92586291e-01 -3.23601097e-01 5.70774078e-01 -5.64614892e-01 -4.82878953e-01 7.54903913e-01 2.69053012e-01 4.86586928e-01 6.23848200e-01 -1.17084466e-01 -5.73376536e-01 -1.38799250e-01 -1.39942372e+00 8.33546758e-01 9.46179926e-01 -5.40160060e-01 -5.15074611e-01 -3.44743766e-02 3.30899805e-01 -6.31369889e-01 -5.51536918e-01 1.36679173e-01 7.87448823e-01 -1.01068115e+00 8.67774725e-01 -1.79369941e-01 4.91453588e-01 -8.44664752e-01 -2.57894516e-01 -1.14481378e+00 -3.90084475e-01 -2.71813333e-01 -7.18698464e-03 8.56664181e-01 5.02077460e-01 -7.97337294e-01 9.46489692e-01 5.29287398e-01 -1.85696244e-01 -5.50673068e-01 -1.19344246e+00 -6.37292027e-01 -3.44010711e-01 -2.35433385e-01 5.47332644e-01 7.29867697e-01 5.28455824e-02 8.94900039e-03 -2.09304020e-01 2.55676627e-01 3.10631722e-01 2.37885520e-01 6.04647219e-01 -1.01880133e+00 -2.29471792e-02 -3.39616328e-01 -9.60789740e-01 -1.05350530e+00 -8.18171874e-02 -8.83963048e-01 4.84251887e-01 -1.66143751e+00 -1.28896400e-01 -4.78656083e-01 -3.97189885e-01 1.04598546e+00 4.98858094e-01 7.51180708e-01 2.41091460e-01 3.28252345e-01 -8.37415636e-01 4.26845312e-01 6.83751523e-01 -2.53033459e-01 -2.77064562e-01 -3.15312803e-01 -4.61477280e-01 5.36127150e-01 1.30022275e+00 -4.44274157e-01 -2.86876500e-01 -4.94217873e-01 -6.95496574e-02 -4.14896935e-01 4.72267568e-01 -1.70723057e+00 6.59091413e-01 1.26638219e-01 9.91291940e-01 -6.80210948e-01 4.06590492e-01 -8.38790357e-01 2.15186015e-01 5.34601927e-01 -2.17423841e-01 6.98570311e-02 3.54868472e-01 4.64986652e-01 -2.29030624e-01 -1.05781652e-01 7.22449303e-01 -2.88054675e-01 -1.25719988e+00 1.49526462e-01 -6.88667178e-01 -6.25410020e-01 1.21863377e+00 -6.50888383e-01 -4.09641653e-01 -2.42588501e-02 -4.10347611e-01 1.19030796e-01 8.99128854e-01 4.93286878e-01 7.93759525e-01 -1.26623881e+00 -1.45692170e-01 2.41406709e-01 4.96950299e-01 1.04524888e-01 1.56874090e-01 4.01169837e-01 -1.08586335e+00 6.56376004e-01 -6.48046255e-01 -5.53134263e-01 -1.08819246e+00 6.05750620e-01 3.32227409e-01 1.18817789e-02 -7.01633394e-01 8.75378191e-01 3.99406180e-02 -6.99718773e-01 7.23964721e-02 -3.35667431e-01 -3.97650033e-01 -1.34218916e-01 6.17815912e-01 1.21081993e-02 1.74126461e-01 -8.32787097e-01 -6.74908698e-01 2.46602774e-01 -6.43036813e-02 -1.75191864e-01 1.58928740e+00 1.73047483e-01 -1.32822944e-02 1.44869700e-01 1.04084766e+00 -3.21897835e-01 -1.50969231e+00 -2.91329902e-02 -1.01238843e-02 -2.52983630e-01 1.66086331e-01 -6.93318188e-01 -8.61209452e-01 8.29011559e-01 6.49633944e-01 -7.70701021e-02 9.38291252e-01 -1.62209257e-01 5.33555448e-01 5.86836874e-01 8.20161581e-01 -9.67418730e-01 -2.11948082e-01 6.46546602e-01 6.76600277e-01 -9.18087840e-01 -1.59557939e-01 -3.07648256e-02 -2.35381961e-01 1.29997694e+00 6.03078842e-01 -4.05816406e-01 3.62879366e-01 2.90752590e-01 1.75526544e-01 -1.14726633e-01 -6.35968864e-01 -2.52516836e-01 -9.84250288e-03 9.32909012e-01 1.94135442e-01 -6.90430030e-02 1.14976555e-01 1.24077454e-01 -2.24466518e-01 1.32072419e-01 2.59530216e-01 1.38676810e+00 -6.86942577e-01 -9.83689904e-01 -2.32309237e-01 2.57988214e-01 -1.01815134e-01 -2.61782765e-01 -4.91122574e-01 6.82992578e-01 3.36831152e-01 7.12864757e-01 1.66436702e-01 -6.59638524e-01 5.65051660e-02 -1.56580970e-01 4.07535285e-01 -4.88944381e-01 -7.28935063e-01 -3.52726221e-01 -6.72296733e-02 -8.50657880e-01 -4.28228140e-01 -5.14464140e-01 -1.19344258e+00 -1.57540366e-01 5.71091920e-02 -1.85203210e-01 9.73949552e-01 7.27349102e-01 6.39072537e-01 3.20010006e-01 3.64211708e-01 -1.43017876e+00 -2.68585552e-02 -6.90682709e-01 -3.81461501e-01 -2.91808307e-01 3.20903301e-01 -7.44950473e-01 4.53975275e-02 -6.61151037e-02]	[7.683662414550781, -1.828377604484558]
913e5cd7-a5fa-43d0-93c3-8016dec7e9bf	courier-contrastive-user-intention	2306.05001	null	https://arxiv.org/abs/2306.05001v1	https://arxiv.org/pdf/2306.05001v1.pdf	COURIER: Contrastive User Intention Reconstruction for Large-Scale Pre-Train of Image Features	With the development of the multi-media internet, visual characteristics have become an important factor affecting user interests. Thus, incorporating visual features is a promising direction for further performance improvements in click-through rate (CTR) prediction. However, we found that simply injecting the image embeddings trained with established pre-training methods only has marginal improvements. We attribute the failure to two reasons: First, The pre-training methods are designed for well-defined computer vision tasks concentrating on semantic features, and they cannot learn personalized interest in recommendations. Secondly, pre-trained image embeddings only containing semantic information have little information gain, considering we already have semantic features such as categories and item titles as inputs in the CTR prediction task. We argue that a pre-training method tailored for recommendation is necessary for further improvements. To this end, we propose a recommendation-aware image pre-training method that can learn visual features from user click histories. Specifically, we propose a user interest reconstruction module to mine visual features related to user interests from behavior histories. We further propose a contrastive training method to avoid collapsing of embedding vectors. We conduct extensive experiments to verify that our method can learn users' visual interests, and our method achieves $0.46\%$ improvement in offline AUC and $0.88\%$ improvement in Taobao online GMV with p-value$<0.01$.	['Yang Yang', 'Xiaoyi Zeng', 'Qingwen Liu', 'De-Chuan Zhan', 'Ju Huang', 'OU Dan', 'Chenglei Dai', 'Jia-Qi Yang']	2023-06-08	null	null	null	null	['click-through-rate-prediction']	['miscellaneous']	[-1.12768911e-01 -2.81187981e-01 -5.93156517e-01 -5.81948102e-01 -5.24371386e-01 -3.72150689e-01 4.93063778e-01 1.14268787e-01 -5.54948866e-01 3.43628585e-01 4.79558498e-01 -3.59117180e-01 -8.52321163e-02 -9.79069710e-01 -8.01678598e-01 -2.40831807e-01 -2.10419208e-01 -1.73258577e-02 2.78228581e-01 -1.43852830e-01 5.89621842e-01 8.40669051e-02 -1.67600965e+00 5.02160251e-01 8.79835188e-01 1.35408735e+00 3.57025743e-01 4.11776811e-01 -1.74125642e-01 5.70468605e-01 -2.56879270e-01 -5.88859797e-01 3.83211643e-01 -1.43856332e-01 -4.70747143e-01 1.65195540e-01 3.61003608e-01 -4.69940245e-01 -5.63716948e-01 7.62329519e-01 3.25787783e-01 2.28867888e-01 6.22706831e-01 -1.05483305e+00 -1.22954845e+00 3.99222732e-01 -8.00135612e-01 2.30201453e-01 1.09976821e-01 4.62467782e-02 1.49846971e+00 -1.15787685e+00 4.78679121e-01 9.72730339e-01 4.32354599e-01 4.18794811e-01 -1.02552509e+00 -5.91193020e-01 3.97659302e-01 6.27133667e-01 -1.24713790e+00 3.56659219e-02 7.05915093e-01 -3.25371534e-01 5.74432313e-01 4.73352820e-01 6.58220232e-01 1.05928278e+00 -6.52025044e-02 1.15464365e+00 9.18228924e-01 -1.90382525e-01 2.68320683e-02 8.32388997e-01 9.25720930e-02 7.49407709e-01 1.48587197e-01 -1.03864530e-02 -4.51712281e-01 1.36043757e-01 7.38982797e-01 6.57671273e-01 -8.95969644e-02 -4.26308751e-01 -1.00403440e+00 1.23375916e+00 9.26515639e-01 1.96487486e-01 -1.34133816e-01 2.09858827e-02 2.69638211e-01 1.89397737e-01 6.24355435e-01 4.42243099e-01 -3.57465029e-01 7.40628839e-02 -7.42266655e-01 -6.59650043e-02 3.01389545e-01 8.13557923e-01 8.82210910e-01 -2.66241699e-01 -2.81933933e-01 1.08044386e+00 4.53619272e-01 2.54636317e-01 7.37012804e-01 -6.37485504e-01 4.57730114e-01 7.95259953e-01 1.45270184e-01 -1.24486458e+00 -1.08260758e-01 -6.60245597e-01 -4.86755162e-01 -1.71018377e-01 2.63888836e-01 1.76607460e-01 -9.18115437e-01 1.32894874e+00 1.09974779e-01 -1.52108110e-02 -2.74284691e-01 1.01999557e+00 6.57738030e-01 6.32927060e-01 7.01086894e-02 -7.43523315e-02 1.47232378e+00 -1.19018459e+00 -4.00521636e-01 -3.46487075e-01 5.26327670e-01 -7.87208915e-01 1.70897150e+00 2.65473902e-01 -7.28741646e-01 -8.38440239e-01 -9.76862431e-01 1.86507497e-02 -5.07420123e-01 4.55449939e-01 9.01188612e-01 5.73203564e-01 -4.83058125e-01 3.85127902e-01 -3.71652991e-01 -2.14556471e-01 5.51571667e-01 1.92542419e-01 -2.39906553e-02 -1.98257804e-01 -1.08885467e+00 4.84635204e-01 3.08638066e-02 -1.92060307e-01 -6.66324139e-01 -7.20352769e-01 -5.19515514e-01 2.36131281e-01 4.54079568e-01 -2.65031010e-01 9.27006960e-01 -1.09331107e+00 -1.16373742e+00 5.79859078e-01 -1.12616524e-01 -3.60953480e-01 4.10779953e-01 -2.88126469e-01 -6.10174835e-01 8.28004703e-02 5.43070473e-02 6.54819250e-01 9.05371666e-01 -1.47377646e+00 -1.03459477e+00 -4.73132312e-01 2.24037930e-01 2.12778300e-01 -1.04702997e+00 -1.78971052e-01 -1.02040184e+00 -7.65220940e-01 -4.42394763e-02 -8.33199561e-01 -2.40832165e-01 1.25972405e-01 -4.62439656e-02 -2.97066927e-01 8.24174881e-01 -6.98812604e-01 1.38341701e+00 -2.13433790e+00 -4.39515293e-01 4.13581312e-01 2.55345523e-01 2.85649568e-01 -3.02181453e-01 2.42191017e-01 2.88327962e-01 3.76771063e-01 4.11979824e-01 -1.85805976e-01 -4.44288440e-02 -9.59226787e-02 -3.53209525e-01 1.49313852e-01 -3.57380658e-02 1.05295968e+00 -6.79056942e-01 -5.51491082e-01 2.29876056e-01 4.85894501e-01 -8.67619991e-01 2.85545081e-01 -2.26836115e-01 8.78272727e-02 -7.27993429e-01 5.66152334e-01 6.78387761e-01 -8.06085110e-01 1.35382846e-01 -5.20204902e-01 -1.40001610e-01 7.54191428e-02 -9.65517521e-01 1.49984562e+00 -7.56542087e-01 4.61515546e-01 -4.44480181e-01 -1.18182218e+00 7.60284722e-01 -1.24353848e-01 5.79330206e-01 -1.22444272e+00 9.86149833e-02 -1.45226404e-01 -1.96483642e-01 -5.98926485e-01 7.63431311e-01 2.37296373e-01 6.97102845e-02 4.38264489e-01 -1.41887039e-01 4.94594783e-01 7.11270496e-02 3.82774800e-01 8.95539105e-01 -1.49874762e-01 7.47557869e-03 1.76879764e-01 3.00635904e-01 4.89847735e-02 3.87439787e-01 6.75650895e-01 -1.96427539e-01 6.31344497e-01 1.65412933e-01 -2.49099672e-01 -1.09635210e+00 -1.00025904e+00 -1.38893262e-01 1.42089283e+00 4.47187275e-01 -5.11414230e-01 -2.08524033e-01 -1.23547876e+00 -1.52161568e-02 5.67424476e-01 -7.72923410e-01 -1.23818912e-01 -3.77485663e-01 -8.12797844e-01 -1.93397790e-01 6.72306597e-01 4.74002719e-01 -8.55690897e-01 -6.97531253e-02 7.26697966e-03 -1.26101717e-01 -1.03720868e+00 -7.98224628e-01 -2.83264220e-01 -8.73826444e-01 -1.00598478e+00 -9.85832632e-01 -8.67467344e-01 9.19899106e-01 8.46236646e-01 7.92104065e-01 2.22553194e-01 -3.28000844e-01 5.65960228e-01 -7.25976467e-01 -1.86132818e-01 2.74849743e-01 7.64851943e-02 -2.49130875e-01 3.27426106e-01 5.66601336e-01 -2.10080281e-01 -1.35711563e+00 6.53882146e-01 -8.30257118e-01 -9.48758621e-04 8.74657631e-01 8.48682821e-01 6.20641649e-01 -1.59739897e-01 5.02073169e-01 -9.22579944e-01 6.49024665e-01 -6.62969112e-01 -3.79419029e-01 3.87027860e-01 -1.04735756e+00 -5.63747622e-02 7.39130616e-01 -5.38571835e-01 -9.91742790e-01 -9.63929575e-03 -1.48757488e-01 -3.81626308e-01 -2.79743019e-02 5.68888187e-01 7.87830725e-02 6.07106537e-02 5.59707463e-01 2.60754645e-01 -1.56660438e-01 -6.49954557e-01 5.79307735e-01 9.33749199e-01 -8.11293870e-02 -1.37184009e-01 7.98419654e-01 5.48568726e-01 -5.04914224e-01 -7.10062802e-01 -9.17785227e-01 -9.24840748e-01 -1.55760303e-01 -1.91000581e-01 6.49390221e-01 -9.96993124e-01 -9.43910420e-01 -2.77133137e-01 -6.24777675e-01 8.17602277e-02 -8.48120973e-02 7.16353059e-01 -2.79543668e-01 6.17745817e-01 -4.43412751e-01 -6.67180061e-01 -3.58277172e-01 -9.47403371e-01 6.34754419e-01 3.95178586e-01 1.72859967e-01 -8.93663466e-01 1.98164536e-03 7.56259799e-01 5.68834901e-01 -4.98514324e-01 7.43796408e-01 -7.00613201e-01 -7.87571728e-01 -4.51938480e-01 -8.66425753e-01 4.45278019e-01 1.53365016e-01 -2.81996548e-01 -8.25578988e-01 -3.44410986e-01 -3.16727310e-01 -3.33972722e-01 1.04803061e+00 3.02022874e-01 1.86026704e+00 -5.26143730e-01 -4.64610934e-01 4.70463246e-01 1.66674864e+00 2.11400479e-01 7.73790836e-01 3.36337924e-01 7.86375999e-01 5.27650297e-01 9.29543495e-01 6.64775431e-01 5.89049637e-01 7.64438212e-01 5.33451736e-01 -2.59448439e-01 -4.00224328e-02 -6.02435112e-01 2.79216230e-01 6.13585889e-01 -2.90383130e-01 -1.96141571e-01 -3.24031591e-01 5.51069319e-01 -1.79758143e+00 -8.75045002e-01 6.28613681e-02 2.27640343e+00 6.68952346e-01 7.25813434e-02 3.45877230e-01 -1.04740866e-01 5.86213648e-01 1.01349555e-01 -6.17217779e-01 -8.13746974e-02 2.68267274e-01 2.46269330e-01 7.41632104e-01 6.00796901e-02 -9.88947511e-01 9.16995466e-01 5.38672113e+00 1.07931972e+00 -1.18504393e+00 2.02495277e-01 6.06715679e-01 -8.16964060e-02 -5.89496732e-01 -7.21768364e-02 -9.71948802e-01 6.45427585e-01 6.81366503e-01 3.57827656e-02 3.14925253e-01 1.09211540e+00 3.31118107e-01 1.82148218e-01 -5.51947713e-01 9.29923117e-01 3.34133625e-01 -1.48962843e+00 1.42778501e-01 3.53923023e-01 5.96418977e-01 -9.92085710e-02 5.46767294e-01 5.37510037e-01 1.45459235e-01 -8.08695912e-01 3.95632386e-01 3.36075664e-01 6.37825251e-01 -6.30961835e-01 5.28303444e-01 5.68886986e-03 -1.18509078e+00 -3.53985637e-01 -6.69469595e-01 3.73374343e-01 8.89153704e-02 5.66184700e-01 -9.04877007e-01 3.27297837e-01 8.93414497e-01 9.38149691e-01 -8.85750592e-01 1.22862363e+00 -5.55511825e-02 7.32954681e-01 9.10764858e-02 -4.12379503e-01 1.20192327e-01 -7.52985030e-02 4.14600037e-02 9.70251262e-01 4.36557144e-01 -1.26418918e-01 8.75245482e-02 6.06455982e-01 -1.70272291e-01 6.68438196e-01 -3.71093035e-01 -2.50825077e-01 8.09855759e-02 1.44047654e+00 -6.20772004e-01 -2.50135243e-01 -9.92550671e-01 1.06615627e+00 3.06333035e-01 3.95760566e-01 -1.20095432e+00 -4.59633976e-01 5.40624917e-01 5.80676377e-01 6.96582496e-01 -2.22828120e-01 -1.80994630e-01 -1.39051545e+00 -5.21616936e-02 -6.26313984e-01 4.60050106e-01 -4.68296915e-01 -1.45555985e+00 3.09136689e-01 -3.70507568e-01 -1.52912271e+00 1.71131432e-01 -7.68234253e-01 -5.49063683e-01 3.95466983e-01 -1.64895678e+00 -1.29262865e+00 -4.34098661e-01 6.34201586e-01 7.96551526e-01 -1.39291167e-01 3.97768289e-01 5.48074007e-01 -4.94285464e-01 1.02604198e+00 1.76241025e-01 7.29472563e-02 7.77974963e-01 -1.04847777e+00 4.85831834e-02 5.06272018e-01 4.34879273e-01 7.07799017e-01 4.27572578e-01 -4.93659317e-01 -1.38653922e+00 -1.13063812e+00 6.73676789e-01 -2.57204205e-01 6.15321159e-01 -3.45319897e-01 -7.73317397e-01 6.61674440e-01 1.85500327e-02 -2.71032117e-02 1.02419698e+00 5.23036361e-01 -3.61906171e-01 -2.67743409e-01 -8.52793336e-01 6.45350814e-01 1.11775279e+00 -3.45327199e-01 -3.60178649e-01 2.73447931e-01 6.17447197e-01 1.93715170e-01 -8.91209364e-01 3.46923023e-01 6.88045979e-01 -7.44453847e-01 1.35007715e+00 -6.38497770e-01 4.51961011e-01 -4.03017476e-02 -2.78149813e-01 -1.02769077e+00 -4.84770149e-01 1.33521552e-03 -8.89347345e-02 1.15414071e+00 7.17359900e-01 -3.60444427e-01 1.23046744e+00 5.16260445e-01 -2.29341611e-02 -7.57678866e-01 -3.46539944e-01 -5.84453285e-01 -2.33747125e-01 -3.74856353e-01 3.61789584e-01 7.57804871e-01 -3.51799764e-02 4.31382090e-01 -8.14084709e-01 -2.51743048e-02 4.09442037e-01 4.17604715e-01 8.57397795e-01 -1.03259397e+00 -4.56354588e-01 -1.94453508e-01 -1.26205251e-01 -1.56491482e+00 -2.39326537e-01 -8.07891726e-01 -2.92655200e-01 -1.69296443e+00 6.11542225e-01 -7.09230125e-01 -7.24921703e-01 3.95379424e-01 -2.48682812e-01 4.61835802e-01 1.19143486e-01 3.13962132e-01 -9.43533778e-01 6.92428887e-01 1.51016796e+00 -1.98123440e-01 -2.63790339e-01 2.60362267e-01 -1.07498753e+00 3.91132623e-01 8.51038456e-01 -2.54311264e-01 -5.23506582e-01 -1.88410163e-01 3.29102218e-01 -3.44632000e-01 2.46900156e-01 -7.78698623e-01 -5.13933115e-02 -2.40116581e-01 6.27977669e-01 -5.66603959e-01 3.61482143e-01 -7.01647878e-01 -4.27640975e-01 2.48840556e-01 -5.07051289e-01 -1.16808072e-01 -7.84294233e-02 8.59882653e-01 -2.36155912e-01 -2.17042938e-01 4.92927611e-01 -1.50713563e-01 -1.05558538e+00 5.16008735e-01 -2.10410818e-01 -1.22376211e-01 8.49549174e-01 -2.61919320e-01 -2.12435782e-01 -4.62999612e-01 -6.19451702e-01 2.35699579e-01 3.17899793e-01 7.61281788e-01 7.43922055e-01 -1.35789275e+00 -2.45427489e-01 1.69670343e-01 5.25033534e-01 -7.51476169e-01 3.54096144e-01 5.91910005e-01 -1.35232210e-01 5.06529570e-01 -1.07251205e-01 -3.84242713e-01 -1.38437009e+00 8.43883991e-01 -2.45567977e-01 -2.67491817e-01 -3.01256567e-01 8.12541783e-01 4.36320513e-01 -2.09237456e-01 2.77573347e-01 -1.50939837e-01 -5.50266266e-01 1.97113752e-01 5.53159118e-01 2.95027286e-01 -7.52630606e-02 -3.25340658e-01 -1.17528602e-01 6.16894960e-01 -4.47426617e-01 2.00476274e-02 1.37872040e+00 -4.45137054e-01 6.00843370e-01 6.99821785e-02 1.55491972e+00 2.16366082e-01 -1.11280239e+00 -3.82590741e-01 -2.66747653e-01 -9.40499544e-01 2.39942774e-01 -8.09587419e-01 -1.45459008e+00 1.04016626e+00 9.39272881e-01 2.51984924e-01 1.08919871e+00 2.05328837e-01 9.66296852e-01 1.95799455e-01 1.96705848e-01 -1.33873773e+00 6.64856195e-01 1.01251669e-01 7.39531279e-01 -1.59039402e+00 5.92586920e-02 -2.77760029e-01 -1.03793418e+00 8.13144267e-01 8.73657763e-01 -3.26482914e-02 9.23697352e-01 -4.86891776e-01 2.20622122e-02 -1.72125116e-01 -5.93841553e-01 -6.27841711e-01 7.79119194e-01 3.03722322e-01 5.33272684e-01 -2.12638956e-02 -6.33380055e-01 7.17487037e-01 1.86613634e-01 4.09160405e-02 7.35418797e-02 6.20727360e-01 -6.63275599e-01 -1.23787844e+00 -1.19394865e-02 8.47032130e-01 -4.87070143e-01 -9.49584693e-02 -5.41309305e-02 6.13351882e-01 1.28962263e-01 8.26324463e-01 1.26593962e-01 -8.68871987e-01 3.91911685e-01 -2.97443599e-01 3.27053875e-01 -5.74449480e-01 -3.10153455e-01 1.61438644e-01 -1.03970833e-01 -6.55070603e-01 -1.03237927e-01 -3.68796140e-01 -1.04279137e+00 -2.70085156e-01 -4.37210858e-01 2.12997645e-01 7.42418408e-01 6.17711425e-01 5.67274928e-01 2.55263567e-01 1.02719283e+00 -5.01650572e-01 -5.01964211e-01 -7.38129973e-01 -5.23869455e-01 7.64199078e-01 -1.65966392e-01 -6.31468415e-01 -4.89004344e-01 -1.50156915e-01]	[10.145482063293457, 5.444944858551025]
5099bc1b-9c53-4615-8975-70524593dc61	polarized-color-image-denoising-using	2207.00215	null	https://arxiv.org/abs/2207.00215v2	https://arxiv.org/pdf/2207.00215v2.pdf	Polarized Color Image Denoising using Pocoformer	Polarized color photography provides both visual textures and object surficial information in one single snapshot. However, the use of the directional polarizing filter array causes extremely lower photon count and SNR compared to conventional color imaging. Thus, the feature essentially leads to unpleasant noisy images and destroys polarization analysis performance. It is a challenge for traditional image processing pipelines owing to the fact that the physical constraints exerted implicitly in the channels are excessively complicated. To address this issue, we propose a learning-based approach to simultaneously restore clean signals and precise polarization information. A real-world polarized color image dataset of paired raw short-exposed noisy and long-exposed reference images are captured to support the learning-based pipeline. Moreover, we embrace the development of vision Transformer and propose a hybrid transformer model for the Polarized Color image denoising, namely PoCoformer, for a better restoration performance. Abundant experiments demonstrate the effectiveness of proposed method and key factors that affect results are analyzed.	['Yinqiang Zheng', 'Haiyang Jiang', 'Zhuoxiao Li']	2022-07-01	null	null	null	null	['color-image-denoising']	['computer-vision']	[ 4.45997983e-01 -3.33095819e-01 4.42737520e-01 -1.90311503e-02 -6.98289871e-01 -5.86111188e-01 3.25523674e-01 -3.63584310e-01 -1.58437207e-01 8.40008616e-01 -1.41809076e-01 -1.57835037e-01 -1.88175455e-01 -6.29289567e-01 -5.75876892e-01 -1.50016391e+00 3.22958946e-01 -2.56314516e-01 6.53107390e-02 -6.83326623e-04 5.44298351e-01 3.81321788e-01 -1.65470064e+00 1.20915323e-01 1.20390809e+00 9.49660540e-01 2.37230778e-01 3.45390826e-01 -3.28924246e-02 6.91386700e-01 -3.03797275e-01 -5.15406072e-01 3.63923609e-01 -3.48030329e-01 -2.35644728e-01 1.15342559e-02 4.00262386e-01 -3.72623086e-01 -1.33324668e-01 1.54765499e+00 6.27900600e-01 -1.94965228e-01 5.38185656e-01 -9.80092466e-01 -7.84697831e-01 -9.26857889e-02 -7.47995794e-01 1.58793569e-01 9.07380506e-02 4.95127171e-01 3.31081599e-01 -5.85636616e-01 4.11257625e-01 6.80628717e-01 5.09189606e-01 1.08275466e-01 -1.10114622e+00 -4.29107159e-01 -2.96809286e-01 5.06545961e-01 -7.96373785e-01 -5.99211574e-01 1.22503960e+00 -2.77429134e-01 3.09758425e-01 1.53455913e-01 6.61373794e-01 9.19327974e-01 3.92291427e-01 5.48224673e-02 2.14521670e+00 -3.78908455e-01 -2.21957378e-02 2.94155091e-01 2.56573051e-01 6.39094949e-01 4.70854312e-01 2.99457699e-01 -6.95624113e-01 1.89421818e-01 2.65509099e-01 -2.42106184e-01 -6.87738955e-01 -1.87202960e-01 -9.03756499e-01 -1.38887256e-01 1.96116164e-01 -5.72485738e-02 -5.22400677e-01 -3.43308866e-01 6.12214543e-02 1.05090193e-01 3.57965022e-01 3.69791418e-01 1.06429663e-02 1.30163521e-01 -5.44980645e-01 -2.26885393e-01 3.95761430e-01 3.52036506e-01 7.63512373e-01 2.04373598e-01 -1.20171972e-01 8.48143280e-01 3.73788595e-01 1.00693715e+00 -1.67590618e-01 -1.19169450e+00 1.36416748e-01 1.89436108e-01 4.13437366e-01 -1.08424854e+00 -3.93583924e-02 -6.08221292e-01 -7.08457768e-01 5.74591517e-01 3.36584389e-01 -6.11939877e-02 -9.37410951e-01 1.33641136e+00 4.24984127e-01 2.30990604e-01 3.06900293e-01 1.18962824e+00 5.50472379e-01 8.50873291e-01 1.02496520e-03 -7.16583729e-01 1.26927650e+00 -6.34728730e-01 -9.28986669e-01 -2.92822756e-02 -2.40851536e-01 -1.15045500e+00 1.06866980e+00 1.03477466e+00 -9.78178144e-01 -3.33858579e-01 -1.29866052e+00 4.84963693e-03 4.83164266e-02 3.68272245e-01 5.92415571e-01 9.75647449e-01 -7.18541086e-01 3.78711164e-01 -5.04848778e-01 -8.92576426e-02 3.00976008e-01 -2.47762376e-03 -3.43353748e-01 -5.05599439e-01 -7.23689020e-01 7.64028370e-01 6.07289858e-02 6.53517485e-01 -6.80984080e-01 -6.14298284e-01 -1.84913635e-01 -2.19183505e-01 -2.04634406e-02 -4.38732684e-01 4.60187554e-01 -7.50241637e-01 -1.71888590e+00 7.39651501e-01 -1.11984372e-01 7.12676495e-02 2.27645382e-01 -1.92151934e-01 -6.44015610e-01 4.16420758e-01 -2.19827257e-02 -1.84066415e-01 1.16547775e+00 -1.59439147e+00 -4.43967432e-01 -4.50658798e-01 -1.13412566e-01 2.92953461e-01 -1.95697531e-01 -1.11597337e-01 -3.69355202e-01 2.79080812e-02 4.20739174e-01 -5.62866569e-01 1.85618743e-01 -2.50302136e-01 -5.76973140e-01 4.22540992e-01 9.25957859e-01 -9.05577958e-01 6.02677584e-01 -2.28298187e+00 -1.82945803e-01 -1.48142144e-01 -2.06679851e-02 3.75370920e-01 -6.80357590e-02 2.76406050e-01 -3.15216780e-02 -3.56647581e-01 -1.97304070e-01 7.99229443e-02 -4.61526304e-01 -7.10260049e-02 -2.03074262e-01 8.17836523e-01 3.52307670e-02 1.77668646e-01 -6.60120726e-01 -3.76913965e-01 3.27847332e-01 6.05325937e-01 -3.26632172e-01 1.71168357e-01 1.60125539e-01 8.43824029e-01 -2.50544280e-01 8.96605492e-01 1.54515457e+00 1.87110111e-01 1.96003407e-01 -1.10109556e+00 -6.53903961e-01 -1.15342103e-01 -1.11066914e+00 1.16121852e+00 -2.29551733e-01 4.23305064e-01 4.57626820e-01 -1.12161219e+00 8.63675952e-01 1.07723966e-01 3.58280033e-01 -1.17367160e+00 3.05889659e-02 3.60221446e-01 -3.21866333e-01 -1.13574243e+00 2.44284540e-01 -5.57907045e-01 5.20558655e-01 6.23884350e-02 -4.70794626e-02 -5.02204383e-03 -3.73509862e-02 -6.03757426e-02 6.47974849e-01 3.61748070e-01 -3.19786668e-01 -2.48831376e-01 7.87496030e-01 -1.23778004e-02 8.14277291e-01 4.17516232e-01 -2.67875135e-01 5.96034527e-01 5.46396792e-01 -2.73136407e-01 -9.50329602e-01 -1.10426795e+00 -2.04081491e-01 3.51897776e-01 6.91908598e-01 9.73461717e-02 -4.54408079e-01 -1.24927521e-01 -3.99629325e-01 4.79226291e-01 -2.49372683e-02 9.26135033e-02 -3.64749700e-01 -1.28246284e+00 2.80520797e-01 -2.21706644e-01 8.85247827e-01 -5.97672522e-01 -2.14981124e-01 -1.95405617e-01 -3.81223202e-01 -9.89671290e-01 3.29652727e-01 -2.48826984e-02 -6.06772065e-01 -1.50169849e+00 -3.84323776e-01 -5.24669528e-01 7.22269475e-01 6.43067360e-01 7.03904510e-01 -2.84521580e-01 -1.98451132e-01 3.90854925e-01 -2.71728009e-01 -3.28214526e-01 2.03879531e-02 -6.29812241e-01 7.93461408e-03 5.69404006e-01 1.39481738e-01 -7.09445715e-01 -8.93627942e-01 -4.46585231e-02 -6.67928517e-01 1.91239297e-01 7.85981238e-01 9.79664207e-01 5.68059325e-01 3.30080509e-01 3.84778917e-01 -7.39807427e-01 3.96619707e-01 -1.97572812e-01 -9.49856162e-01 3.16613764e-01 -6.82864487e-01 -7.21244141e-02 6.87756181e-01 -1.07978377e-02 -1.91476989e+00 -9.44530889e-02 1.00055657e-01 7.33054429e-02 -1.73121274e-01 3.14654440e-01 -3.46135527e-01 -4.98708397e-01 5.05663335e-01 5.05687892e-01 7.21437335e-02 -5.00289142e-01 8.12043920e-02 6.76761329e-01 7.63705671e-01 -3.55460227e-01 8.61635387e-01 8.08631003e-01 3.22386920e-01 -1.12206674e+00 -6.22641146e-01 -2.10106999e-01 2.67081391e-02 -6.63746238e-01 8.35474253e-01 -1.02339482e+00 -9.78609145e-01 9.27460432e-01 -1.04084909e+00 2.51079202e-01 4.48858410e-01 5.70720494e-01 4.56885668e-03 6.30990922e-01 -5.78946888e-01 -9.72221315e-01 -2.95621872e-01 -1.10012805e+00 6.83681846e-01 6.13170862e-01 9.43881929e-01 -4.16613996e-01 8.05277284e-03 8.21662784e-01 4.15036291e-01 2.13691592e-01 1.03946197e+00 5.64969122e-01 -1.10840929e+00 3.67291495e-02 -5.21171749e-01 8.33100557e-01 -5.54859929e-04 1.76236004e-01 -1.25996220e+00 -1.46184161e-01 4.58792657e-01 -1.66450858e-01 7.20978260e-01 4.63509023e-01 9.04356122e-01 6.64026141e-02 -2.88119838e-02 9.77132022e-01 1.93266261e+00 2.91053444e-01 1.11379671e+00 4.55019951e-01 7.01750278e-01 7.02361107e-01 7.68602788e-01 1.65165335e-01 1.36330798e-01 3.35006356e-01 5.18620014e-01 -2.48920262e-01 -2.53277153e-01 7.22261891e-02 2.56199032e-01 7.87100911e-01 -3.97011191e-01 -2.41264731e-01 -6.07559025e-01 3.30347925e-01 -1.28593910e+00 -8.18298340e-01 -8.26130688e-01 2.00937343e+00 5.30218124e-01 -2.18831301e-01 -7.56281793e-01 2.09604606e-01 6.54593587e-01 2.06693098e-01 -1.80600166e-01 1.17495678e-01 -5.60222507e-01 1.99075148e-01 7.39090800e-01 5.15697539e-01 -8.34348679e-01 5.18472195e-01 5.70839596e+00 4.91981924e-01 -1.88763213e+00 1.16495453e-01 4.99351710e-01 3.24924961e-02 -4.54092920e-01 1.62861794e-01 -2.54138082e-01 7.85299003e-01 3.00500095e-01 2.83519983e-01 6.71916783e-01 2.90556520e-01 4.63933140e-01 -7.02236831e-01 -3.96728039e-01 1.47917056e+00 1.36334509e-01 -9.25485790e-01 -7.90321380e-02 -2.14898676e-01 4.93190438e-01 -1.11972004e-01 4.45726275e-01 -3.40898842e-01 -3.63137394e-01 -5.86589396e-01 4.38822508e-01 9.28500772e-01 6.41259551e-01 -6.14151657e-01 5.67485809e-01 1.95146665e-01 -4.41734165e-01 -1.61140591e-01 -5.63823819e-01 -5.73139638e-02 3.81664813e-01 1.07736802e+00 -3.92244399e-01 9.08805966e-01 1.04024518e+00 6.11784101e-01 -4.29504931e-01 1.07362449e+00 -3.38146508e-01 8.02138746e-01 -1.71795249e-01 5.43390572e-01 -1.66892767e-01 -8.99196684e-01 7.02422261e-01 6.14679396e-01 5.59012651e-01 3.26253891e-01 -3.80866885e-01 6.79326475e-01 2.88657248e-01 -1.37991905e-01 -5.78452170e-01 3.86187981e-04 2.05972955e-01 1.69999838e+00 -5.25159419e-01 4.08671447e-04 -4.03212458e-01 8.52942824e-01 -2.15415210e-01 9.12488103e-01 -6.90950990e-01 -2.71032155e-01 3.86824787e-01 1.08171724e-01 1.40120191e-02 -2.99753487e-01 -5.04736543e-01 -1.33042765e+00 2.85350204e-01 -7.67643392e-01 -1.04097158e-01 -1.12757659e+00 -1.20615172e+00 2.39023134e-01 -4.17187959e-01 -1.19560957e+00 7.76201069e-01 -7.54639208e-01 -5.34382224e-01 1.14273405e+00 -2.13558030e+00 -1.28200161e+00 -6.66811347e-01 6.37979388e-01 -1.53251380e-01 8.52487013e-02 4.67400491e-01 6.60943866e-01 -7.71127582e-01 -1.63294509e-01 4.83797997e-01 -4.09580648e-01 1.14253104e+00 -8.37703288e-01 -6.42204106e-01 1.28535223e+00 -4.57065046e-01 5.78613937e-01 9.19677556e-01 -5.32164335e-01 -1.99291456e+00 -6.53951466e-01 3.17350447e-01 -1.69647887e-01 7.22881481e-02 6.23801313e-02 -6.42498255e-01 1.55045003e-01 5.25653481e-01 7.21532702e-02 4.38643783e-01 -2.51029611e-01 -2.64569312e-01 -8.51967514e-01 -1.12234890e+00 2.40350440e-01 5.53817213e-01 -6.26901567e-01 -3.12447339e-01 2.52878517e-01 5.63668571e-02 -1.76004201e-01 -3.68503660e-01 4.52833712e-01 6.05868816e-01 -1.48541451e+00 1.00318277e+00 -5.93114346e-02 4.10669029e-01 -8.68176401e-01 -6.47096485e-02 -1.11920202e+00 -2.75926083e-01 -4.72285956e-01 5.19007385e-01 1.41587567e+00 9.15193409e-02 -9.13850904e-01 5.21441340e-01 2.63712943e-01 -3.80860597e-01 -2.59069681e-01 -5.81299365e-01 -3.73512775e-01 -4.60157812e-01 4.19722646e-02 8.03721920e-02 1.03592217e+00 -4.55838859e-01 1.60576001e-01 -5.58542728e-01 9.13504601e-01 1.41878974e+00 1.81747884e-01 4.64091301e-01 -1.09597743e+00 -6.44123554e-02 3.05126876e-01 -1.92634821e-01 -5.64259827e-01 -1.69593573e-01 -3.99910390e-01 1.17574543e-01 -1.35500312e+00 2.39110619e-01 -6.11158967e-01 -4.64113116e-01 -1.04972906e-01 -1.74006164e-01 6.19900525e-01 -5.37902601e-02 3.53246361e-01 -2.84087121e-01 4.48008418e-01 1.32061481e+00 -2.32514873e-01 7.83960149e-02 -4.02632654e-01 -7.68185318e-01 4.32785451e-01 5.43507040e-01 -3.05232644e-01 -5.73282480e-01 -6.68651581e-01 5.39419174e-01 -5.22266701e-03 8.05965662e-01 -1.12443960e+00 4.01570559e-01 -1.12147994e-01 4.54311937e-01 -4.51536298e-01 4.11428213e-01 -7.24453986e-01 3.89924616e-01 2.05063298e-01 3.09183240e-01 -4.79958475e-01 -1.56041518e-01 6.60502613e-01 -3.58913094e-01 -8.88353810e-02 1.14903986e+00 -2.07241580e-01 -7.21428633e-01 -2.02233613e-01 -1.82838440e-01 -3.81249964e-01 9.05771732e-01 -2.79088050e-01 -9.55104589e-01 2.72889119e-02 -1.41248658e-01 -1.51532724e-01 6.48990512e-01 -2.92849392e-01 4.39660639e-01 -9.23375189e-01 -4.06083673e-01 1.74499705e-01 -1.12928860e-01 -4.09483194e-01 1.06741691e+00 1.34258080e+00 -9.18306351e-01 1.90225527e-01 -6.36323154e-01 -6.36819661e-01 -1.31245887e+00 3.64107579e-01 4.64186102e-01 4.84907031e-01 -5.77064753e-01 7.54230440e-01 -5.33701815e-02 9.87059809e-03 -2.18132257e-01 -3.15449871e-02 -3.54045838e-01 6.83322735e-03 3.60815972e-01 6.61712348e-01 2.31856793e-01 -3.93904299e-01 -2.20698863e-01 7.09232092e-01 2.37973362e-01 -3.47822979e-02 1.49681950e+00 -5.45598209e-01 -7.56496251e-01 -1.82523672e-02 8.66703808e-01 4.13813114e-01 -1.32035387e+00 1.39802098e-01 -5.20741045e-01 -8.47236097e-01 4.79079604e-01 -1.00738072e+00 -1.05083334e+00 9.09010649e-01 9.69340920e-01 6.77196085e-02 1.48947692e+00 -4.26144719e-01 5.14335811e-01 4.21377838e-01 2.71372348e-01 -1.20528829e+00 -4.38297763e-02 -6.46300800e-03 4.17656690e-01 -1.16909242e+00 2.26070136e-02 -7.57370710e-01 -4.40535784e-01 1.08917403e+00 4.92125869e-01 6.74988553e-02 3.10732007e-01 6.04202375e-02 5.74685276e-01 -3.52457523e-01 -2.35184267e-01 1.80596188e-01 -1.92410246e-01 9.98677909e-01 2.65523523e-01 -2.75764883e-01 -5.94164193e-01 4.12573040e-01 2.35143989e-01 8.17029774e-02 7.75327504e-01 6.81562841e-01 -3.36269826e-01 -1.01812792e+00 -6.97173119e-01 2.10285172e-01 -6.27563417e-01 1.61268841e-02 1.60484076e-01 1.83396280e-01 4.25467938e-01 9.73575532e-01 -5.20730376e-01 -3.53834145e-02 1.83999866e-01 4.08278890e-02 5.82292616e-01 -7.28320703e-02 4.96317446e-02 4.43745293e-02 1.71469212e-01 -5.63797653e-01 -9.52983201e-01 -4.51236457e-01 -7.63468564e-01 -9.40496400e-02 -2.50643730e-01 8.18734765e-02 8.30864251e-01 6.11585855e-01 3.70067865e-01 3.19393963e-01 7.38874078e-01 -6.22170448e-01 -2.64372885e-01 -6.87785983e-01 -9.81683671e-01 3.89651418e-01 4.70580518e-01 -7.74950087e-01 -5.55583239e-01 1.52818322e-01]	[10.572628021240234, -2.607869863510132]
502cfec5-1bd3-4901-97c9-d0b25a8a21e4	consistency-aware-shading-orders-selective	1810.09706	null	http://arxiv.org/abs/1810.09706v1	http://arxiv.org/pdf/1810.09706v1.pdf	Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition	We address the problem of decomposing a single image into reflectance and shading. The difficulty comes from the fact that the components of image---the surface albedo, the direct illumination, and the ambient illumination---are coupled heavily in observed image. We propose to infer the shading by ordering pixels by their relative brightness, without knowing the absolute values of the image components beforehand. The pairwise shading orders are estimated in two ways: brightness order and low-order fittings of local shading field. The brightness order is a non-local measure, which can be applied to any pair of pixels including those whose reflectance and shading are both different. The low-order fittings are used for pixel pairs within local regions of smooth shading. Together, they can capture both global order structure and local variations of the shading. We propose a Consistency-aware Selective Fusion (CSF) to integrate the pairwise orders into a globally consistent order. The iterative selection process solves the conflicts between the pairwise orders obtained by different estimation methods. Inconsistent or unreliable pairwise orders will be automatically excluded from the fusion to avoid polluting the global order. Experiments on the MIT Intrinsic Image dataset show that the proposed model is effective at recovering the shading including deep shadows. Our model also works well on natural images from the IIW dataset, the UIUC Shadow dataset and the NYU-Depth dataset, where the colors of direct lights and ambient lights are quite different.	['Nanning Zheng', 'Badong Chen', 'Zejian yuan', 'Ang Li', 'Yuanliu Liu']	2018-10-23	null	null	null	null	['intrinsic-image-decomposition']	['computer-vision']	[ 4.81478155e-01 -4.90786105e-01 4.63578999e-01 -7.77151287e-01 -6.32511556e-01 -5.14058888e-01 3.21759433e-01 -3.90488774e-01 -7.52537996e-02 5.93762696e-01 4.36249375e-02 1.20668985e-01 -8.22218508e-03 -6.59244001e-01 -4.85591888e-01 -1.28439236e+00 2.94459730e-01 2.29837537e-01 4.78487313e-01 -2.63776660e-01 2.44987175e-01 3.49168211e-01 -1.94106269e+00 3.55223447e-01 1.34056139e+00 1.00980616e+00 5.74184477e-01 6.46174967e-01 -3.58154625e-01 6.48266196e-01 -4.21135992e-01 1.94075376e-01 6.49388313e-01 -6.59959316e-01 -2.85507411e-01 5.05542696e-01 1.05002904e+00 -4.77946043e-01 1.01204574e-01 1.36747360e+00 2.53540188e-01 -1.05218790e-01 4.78608459e-01 -8.65338087e-01 -1.14109263e-01 -2.90732294e-01 -8.50705028e-01 -2.78170794e-01 2.29584590e-01 3.39657329e-02 8.46876800e-01 -9.59613204e-01 2.49538615e-01 1.23284125e+00 4.76129651e-01 5.13662770e-03 -1.07122064e+00 -3.62505049e-01 1.69022039e-01 5.23403026e-02 -1.37368429e+00 -4.56203431e-01 1.05732834e+00 -3.49405915e-01 2.77667671e-01 6.31777346e-01 5.17197669e-01 2.97184229e-01 2.47878488e-02 5.12239993e-01 1.82983077e+00 -5.43278337e-01 1.55868173e-01 9.11304280e-02 2.15323508e-01 7.55050600e-01 2.69279391e-01 1.10631280e-01 -7.41240442e-01 -3.42378914e-01 7.13429153e-01 1.25516191e-01 -9.51270163e-01 -1.57972217e-01 -9.02910590e-01 3.48716080e-01 3.63497287e-01 -4.71356846e-02 -1.74952865e-01 -1.20478503e-01 -4.14952129e-01 1.75560713e-01 4.52138513e-01 -4.23932634e-02 -6.62401617e-01 5.94921947e-01 -6.80011690e-01 -8.11230913e-02 7.39740372e-01 6.41788602e-01 1.56377590e+00 -2.02698946e-01 3.10050994e-01 9.82477844e-01 6.37854874e-01 1.01211584e+00 2.27863938e-02 -1.31057620e+00 2.79533505e-01 6.36957407e-01 4.77092713e-01 -1.08822525e+00 -6.43644258e-02 7.88889602e-02 -7.76473641e-01 6.12894416e-01 6.09872818e-01 6.06279857e-02 -1.06362891e+00 1.55576181e+00 5.07098854e-01 2.46732712e-01 -2.27369126e-02 1.05773103e+00 8.05373549e-01 6.29486918e-01 -7.05950260e-01 -4.50724870e-01 1.22676492e+00 -8.24440718e-01 -8.31260443e-01 -4.82693940e-01 -4.26773615e-02 -1.08981943e+00 8.72510493e-01 3.90077502e-01 -1.04044938e+00 -6.52706981e-01 -1.11233270e+00 -1.68797165e-01 2.24811956e-02 2.82336384e-01 3.94123316e-01 3.90572011e-01 -1.27037477e+00 3.92112821e-01 -5.31353831e-01 -9.38068330e-02 -1.84343234e-01 1.71315938e-01 -1.41638750e-02 -3.94990325e-01 -7.96457887e-01 5.87742150e-01 -1.93366632e-01 6.14777327e-01 -6.42263651e-01 -3.88251334e-01 -5.95105350e-01 -9.51752216e-02 3.41645241e-01 -3.44707489e-01 6.58774912e-01 -1.32942843e+00 -1.37792659e+00 7.38844275e-01 -8.10743093e-01 3.72859359e-01 3.24258983e-01 -3.48207192e-03 -3.59874159e-01 1.02073804e-01 -8.41342211e-02 2.21162766e-01 9.29016531e-01 -2.08391213e+00 -6.76293910e-01 -6.58863187e-01 -1.79589361e-01 7.16370285e-01 1.04994781e-01 -3.25833559e-01 -7.53313184e-01 5.89030161e-02 7.71272540e-01 -8.96363258e-01 -1.76637545e-01 6.90227747e-02 -2.99949229e-01 3.10455948e-01 8.20773005e-01 -7.00189829e-01 7.22611606e-01 -2.36050439e+00 -6.46196231e-02 3.56920242e-01 1.44214258e-01 -1.16641983e-01 -1.61950648e-01 1.51641160e-01 1.62855208e-01 -3.72477084e-01 -5.30151904e-01 -3.19586366e-01 -4.45482731e-01 6.80710554e-01 -4.14987862e-01 6.93407953e-01 -1.46084458e-01 3.85727227e-01 -8.41441214e-01 -5.54864049e-01 3.08048278e-01 5.61320364e-01 7.41173998e-02 5.51102757e-01 -1.29780218e-01 5.88015139e-01 -2.85161465e-01 6.06448293e-01 1.30942667e+00 1.04070447e-01 3.25672090e-01 -4.81328934e-01 -3.61783862e-01 2.45633721e-01 -1.49643779e+00 1.28976321e+00 -2.93950975e-01 5.73348761e-01 5.32560647e-01 -3.12151998e-01 1.07069683e+00 -9.20845345e-02 3.30542654e-01 -6.33285880e-01 -1.97365984e-01 3.87343407e-01 -1.53618947e-01 -3.85570496e-01 4.70399946e-01 3.89602035e-03 5.68740129e-01 1.51730791e-01 -4.99121845e-01 -5.22121549e-01 -4.22677584e-02 6.55430323e-03 6.82650149e-01 1.66245684e-01 8.22597668e-02 -4.72363263e-01 6.80336475e-01 -3.34935158e-01 9.54566181e-01 6.75303638e-01 2.33160071e-02 1.10823977e+00 2.58194417e-01 -3.57050657e-01 -6.50748312e-01 -1.14639544e+00 -3.07530135e-01 7.63409555e-01 7.20696568e-01 -7.97332078e-02 -5.36542773e-01 -3.48379493e-01 2.89478479e-03 3.55408907e-01 -4.66477275e-01 3.89067799e-01 -5.31973839e-01 -8.46999407e-01 -2.34023839e-01 -1.25823198e-02 8.28936875e-01 -6.19357049e-01 -5.25105059e-01 -2.10542008e-01 -4.95718151e-01 -1.13298869e+00 -4.63973641e-01 2.94511110e-01 -8.42682183e-01 -1.10030019e+00 -3.29711765e-01 -5.06730855e-01 1.06617868e+00 1.06629860e+00 1.31227756e+00 4.86233503e-01 -1.61251396e-01 3.05649847e-01 -6.50932491e-02 -1.84754089e-01 -2.99284384e-02 -8.25230062e-01 -2.83001542e-01 5.60142875e-01 -6.61920682e-02 -4.09214675e-01 -7.43626356e-01 8.26372802e-01 -9.09739435e-01 2.49536872e-01 2.18665048e-01 8.04098308e-01 7.71779597e-01 2.39253700e-01 -4.62927699e-01 -9.74378109e-01 -1.65883914e-01 -1.31091010e-02 -9.90508795e-01 4.53839958e-01 -4.53269392e-01 -1.41963184e-01 2.64751107e-01 1.47625417e-01 -1.77294326e+00 2.96689034e-01 4.25404191e-01 -1.82805672e-01 -2.73971885e-01 5.36065688e-03 -6.05720997e-01 -3.35690707e-01 3.58158857e-01 2.02476710e-01 -2.22045630e-01 -5.55857122e-01 1.50433764e-01 6.44169092e-01 7.08910167e-01 -5.86610913e-01 7.84106493e-01 1.20224452e+00 3.01148266e-01 -1.25317073e+00 -9.55711186e-01 -8.10560405e-01 -6.43925667e-01 -2.72188395e-01 6.48576379e-01 -9.86767650e-01 -4.09451336e-01 9.30627286e-01 -1.17224813e+00 -4.24774647e-01 -1.32867564e-02 1.05009414e-01 -8.46400782e-02 9.09694135e-01 -3.43575001e-01 -1.07626712e+00 6.26659468e-02 -1.28233790e+00 1.45727396e+00 4.85778749e-01 4.52928901e-01 -9.23956454e-01 5.19862995e-02 3.59881222e-01 1.59699339e-02 1.16410106e-02 6.78522766e-01 3.74220163e-01 -1.00754404e+00 2.79458433e-01 -4.84027684e-01 5.68185329e-01 4.11354035e-01 4.23514277e-01 -1.42742181e+00 -1.33264825e-01 5.23390412e-01 1.68474298e-02 1.15319014e+00 5.15083015e-01 9.30611670e-01 4.31064405e-02 1.76745206e-02 8.97561073e-01 1.85560310e+00 1.64885715e-01 8.91563416e-01 -6.03752909e-03 1.01502001e+00 9.75402117e-01 7.67418861e-01 3.24994534e-01 3.76603454e-01 6.32289886e-01 7.91793644e-01 -5.23249447e-01 -3.16058457e-01 2.28328452e-01 4.26248848e-01 7.93035209e-01 -1.92386433e-01 -3.61876160e-01 -7.46513069e-01 3.41797620e-01 -1.96584022e+00 -6.83469653e-01 -9.76437867e-01 2.63054585e+00 8.10593367e-01 -2.89255768e-01 -7.09388614e-01 -2.48543873e-01 6.54495001e-01 3.63085121e-01 -3.56075555e-01 -4.57581207e-02 -7.15655804e-01 -9.22259018e-02 7.64839232e-01 1.15837038e+00 -7.17917144e-01 5.91330111e-01 6.10247850e+00 5.25123119e-01 -8.76188874e-01 -1.46722347e-01 6.84336424e-01 2.11862698e-01 -7.96438217e-01 4.60672885e-01 -8.01870406e-01 5.33266902e-01 3.08004320e-01 7.00296283e-01 7.02375114e-01 2.67011195e-01 3.54792178e-01 -9.96718884e-01 -7.70969152e-01 9.69110310e-01 2.18220040e-01 -6.92428708e-01 -2.59383112e-01 1.44925758e-01 1.12163341e+00 3.11937273e-01 -3.76774333e-02 -5.71772516e-01 3.92752141e-01 -7.10841537e-01 5.02338588e-01 9.04894114e-01 6.02085412e-01 -2.09792897e-01 7.07298994e-01 3.19042683e-01 -1.22643101e+00 1.62728861e-01 -5.04421115e-01 -9.13386885e-03 8.72946382e-02 1.25981951e+00 -2.88493901e-01 7.73019731e-01 9.15769994e-01 6.59620106e-01 -4.81331915e-01 6.39669240e-01 -5.96997023e-01 3.11557770e-01 -6.36281550e-01 5.14472067e-01 -2.06865013e-01 -1.15823376e+00 2.89311796e-01 7.36409247e-01 2.21782163e-01 2.84175098e-01 3.52466583e-01 7.52895951e-01 3.47249240e-01 -3.31839591e-01 -3.66439730e-01 6.34017050e-01 2.57240176e-01 1.51464367e+00 -4.77737069e-01 -3.46698314e-01 -5.17632842e-01 1.14664578e+00 4.43123467e-02 8.59825790e-01 -5.32453001e-01 -6.02844805e-02 8.57832491e-01 -4.94534150e-02 1.01265326e-01 -3.59294683e-01 -6.66141927e-01 -1.18516779e+00 2.30340719e-01 -7.31772423e-01 4.31167781e-02 -1.23805988e+00 -1.27370775e+00 4.06495631e-01 -1.68183386e-01 -1.19717133e+00 2.76072532e-01 -5.40597498e-01 -6.76918089e-01 1.25632286e+00 -2.03719091e+00 -8.31639349e-01 -9.62862015e-01 6.39400840e-01 3.73113662e-01 4.37588573e-01 5.73326111e-01 2.19019335e-02 -3.44412625e-01 -2.72129714e-01 4.40163165e-01 -3.56475711e-01 9.25236881e-01 -1.43725288e+00 -1.99013308e-01 1.04049182e+00 8.17345753e-02 4.43174839e-01 7.31817961e-01 -5.77071667e-01 -1.28791392e+00 -6.47585094e-01 7.92939544e-01 -3.08283716e-01 2.54847378e-01 -1.86324954e-01 -1.15311360e+00 2.00094968e-01 3.97885770e-01 2.50943959e-01 3.02569479e-01 -1.51228696e-01 -3.07666004e-01 -6.65507257e-01 -9.74704206e-01 5.30084729e-01 8.73223603e-01 -5.96569896e-01 -1.74849302e-01 4.66419995e-01 2.98205644e-01 -3.95498127e-01 -4.03445959e-01 6.14542484e-01 4.38618392e-01 -1.71891677e+00 9.16046977e-01 3.37758422e-01 2.48638064e-01 -9.48794663e-01 -6.18626535e-01 -1.16835392e+00 -1.93306684e-01 -4.54534203e-01 2.84450293e-01 1.38919020e+00 3.56421024e-02 -7.85286129e-01 4.32521880e-01 6.41063213e-01 -1.43063635e-01 -3.12919915e-01 -6.54099703e-01 -3.47527146e-01 -6.51438773e-01 -2.38277181e-03 5.21435976e-01 8.01860154e-01 -7.68557012e-01 2.81172216e-01 -4.34605718e-01 7.09929049e-01 1.06000602e+00 6.19262815e-01 9.78164196e-01 -1.36956275e+00 -3.85920167e-01 -1.06962793e-01 1.54648677e-01 -1.14876103e+00 -2.86204591e-02 -2.41217434e-01 6.88861132e-01 -1.43320954e+00 4.14680272e-01 -4.16013181e-01 -1.96431994e-01 4.15224969e-01 -4.91668761e-01 1.74713984e-01 1.26484130e-02 5.47713876e-01 -2.74192035e-01 5.64371407e-01 1.26978600e+00 -2.35320795e-02 -1.83484748e-01 -2.67380446e-01 -2.75070101e-01 1.12023473e+00 5.31029940e-01 -2.54106551e-01 -3.23262304e-01 -6.96643353e-01 1.78433016e-01 -4.37352397e-02 3.21045607e-01 -7.70580530e-01 5.76582253e-02 -4.99714315e-01 3.48977059e-01 -7.79215991e-01 5.43547988e-01 -1.19544327e+00 3.18549633e-01 5.89110814e-02 5.33921607e-02 -3.84031415e-01 -3.11109543e-01 6.53847396e-01 -1.95068598e-01 -2.81292498e-01 1.04592943e+00 -1.72042429e-01 -6.68643296e-01 1.49758250e-01 8.37502703e-02 -2.64257610e-01 4.75410759e-01 -2.59292483e-01 -5.76330006e-01 -5.11483192e-01 4.77670133e-03 2.02662215e-01 1.00745678e+00 -6.72991201e-02 5.63622475e-01 -9.43719268e-01 -6.51273549e-01 4.59729880e-01 8.47159475e-02 3.20395112e-01 2.44250342e-01 9.45249438e-01 -6.26343548e-01 -2.26973459e-01 1.85689121e-01 -9.32903767e-01 -1.54997313e+00 -8.06992203e-02 5.56961417e-01 -4.77437936e-02 -3.01314294e-01 7.38407552e-01 9.72692370e-01 -4.50568795e-01 -6.08544648e-02 -3.87849122e-01 3.05228736e-02 -2.35733822e-01 5.31637013e-01 4.21727449e-01 8.88114572e-02 -8.41844797e-01 -3.11119199e-01 1.02824390e+00 3.14584106e-01 -4.85337898e-02 1.13817763e+00 -7.08689272e-01 -8.60844970e-01 7.55928218e-01 1.20018244e+00 4.12160844e-01 -1.54170310e+00 -3.48366678e-01 -4.01664257e-01 -1.10437417e+00 3.41020882e-01 -6.81690335e-01 -1.32795274e+00 8.10590267e-01 6.07118368e-01 1.73004016e-01 1.54141819e+00 -1.99342385e-01 4.87538159e-01 1.24005899e-01 4.02568817e-01 -1.02209425e+00 -2.24125639e-01 5.57213366e-01 7.47422874e-01 -1.41055310e+00 3.83590490e-01 -7.53875315e-01 -5.21054387e-01 1.18724203e+00 5.97167492e-01 5.65215573e-02 4.66895401e-01 3.89738530e-01 4.90547955e-01 -1.98866770e-01 -4.88858432e-01 -4.83784884e-01 4.76323009e-01 3.71728361e-01 1.69779077e-01 1.64966378e-02 -1.83887407e-01 -1.44836798e-01 4.26031351e-01 -5.12369037e-01 5.33428192e-01 5.81034541e-01 -7.20413268e-01 -1.00310814e+00 -9.24687803e-01 1.52382165e-01 1.28840312e-01 -1.17097691e-01 -5.97321749e-01 3.15301031e-01 3.15885037e-01 1.21722043e+00 1.22822009e-01 -1.45073235e-01 -5.64756691e-02 -3.22129339e-01 3.97157699e-01 -3.98965150e-01 -1.12124965e-01 6.26739979e-01 1.76329874e-02 -8.24377954e-01 -7.70055473e-01 -7.85310864e-01 -1.18972003e+00 -5.42546101e-02 -5.84545434e-01 -4.62578759e-02 7.15667427e-01 8.25416565e-01 -5.73568493e-02 1.51777491e-01 1.16050136e+00 -1.06629848e+00 -1.23902306e-01 -6.82745814e-01 -1.21302998e+00 4.70947146e-01 7.83392787e-01 -5.40987968e-01 -1.02857029e+00 1.43762335e-01]	[9.92122745513916, -2.972916603088379]
5c4077d7-fa9c-46dd-9c13-ff71b90135db	detecting-adversarial-faces-using-only-real	2304.11359	null	https://arxiv.org/abs/2304.11359v2	https://arxiv.org/pdf/2304.11359v2.pdf	Detecting Adversarial Faces Using Only Real Face Self-Perturbations	Adversarial attacks aim to disturb the functionality of a target system by adding specific noise to the input samples, bringing potential threats to security and robustness when applied to facial recognition systems. Although existing defense techniques achieve high accuracy in detecting some specific adversarial faces (adv-faces), new attack methods especially GAN-based attacks with completely different noise patterns circumvent them and reach a higher attack success rate. Even worse, existing techniques require attack data before implementing the defense, making it impractical to defend newly emerging attacks that are unseen to defenders. In this paper, we investigate the intrinsic generality of adv-faces and propose to generate pseudo adv-faces by perturbing real faces with three heuristically designed noise patterns. We are the first to train an adv-face detector using only real faces and their self-perturbations, agnostic to victim facial recognition systems, and agnostic to unseen attacks. By regarding adv-faces as out-of-distribution data, we then naturally introduce a novel cascaded system for adv-face detection, which consists of training data self-perturbations, decision boundary regularization, and a max-pooling-based binary classifier focusing on abnormal local color aberrations. Experiments conducted on LFW and CelebA-HQ datasets with eight gradient-based and two GAN-based attacks validate that our method generalizes to a variety of unseen adversarial attacks.	['Ning Yu', 'Jiazhong Chen', 'Ping Li', 'Xiaorui Lin', 'Jinyuan Zhang', 'Hefei Ling', 'Yongqin Xian', 'Qian Wang']	2023-04-22	null	null	null	null	['face-detection']	['computer-vision']	[ 3.65978718e-01 2.32195899e-01 3.49340200e-01 -3.12424451e-01 -4.90368426e-01 -9.91387725e-01 5.87551296e-01 -5.42675912e-01 -9.91199352e-03 5.30677795e-01 -3.67878318e-01 -2.23946780e-01 2.50231624e-01 -1.00382924e+00 -7.44344413e-01 -8.42105567e-01 -2.28321329e-01 2.74613708e-01 1.64328024e-01 -5.30297518e-01 -1.05827758e-02 1.11958075e+00 -1.43512690e+00 4.62306350e-01 4.91036594e-01 8.83525789e-01 -7.94810653e-01 7.38103092e-01 3.26060593e-01 4.93233472e-01 -1.24991345e+00 -8.05755973e-01 7.72920251e-01 -6.88599467e-01 -4.53565419e-01 -1.37173086e-01 7.96409190e-01 -5.20972431e-01 -3.23719859e-01 1.25022709e+00 8.24934661e-01 -2.25006238e-01 6.67050421e-01 -1.54188120e+00 -8.24472189e-01 1.52259991e-01 -5.65727472e-01 2.23478839e-01 4.23340172e-01 6.32041216e-01 1.92387536e-01 -6.25132918e-01 3.03334922e-01 1.57541037e+00 5.45931816e-01 1.50906479e+00 -1.17199063e+00 -1.06740546e+00 -1.14852838e-01 -6.96841162e-03 -1.26465786e+00 -6.65033400e-01 9.88700628e-01 -1.93996653e-01 4.68542814e-01 5.22560477e-01 1.99976340e-01 1.74627650e+00 1.11184016e-01 2.86534160e-01 1.14599633e+00 -2.37675443e-01 3.42359602e-01 1.13134213e-01 -3.76296312e-01 6.38024688e-01 2.78823346e-01 4.85904664e-01 -3.05879295e-01 -5.12111664e-01 6.11746132e-01 -3.59758675e-01 -4.64622200e-01 1.10905103e-01 -2.43781596e-01 8.38915110e-01 3.63925099e-01 1.30966991e-01 -2.78041005e-01 -3.86008509e-02 2.47651368e-01 3.76966655e-01 3.04146141e-01 5.29878378e-01 -1.86143994e-01 3.48206878e-01 -5.78258932e-01 2.85946820e-02 6.23013556e-01 5.00155926e-01 4.45819438e-01 6.81998730e-01 -3.02490860e-01 6.21443689e-01 -8.87859389e-02 7.09379196e-01 4.41244721e-01 -4.39928532e-01 -4.71361876e-02 3.69117290e-01 -2.34811679e-01 -1.09306526e+00 -2.95398951e-01 -2.99368501e-01 -7.58629143e-01 9.31128800e-01 4.56226110e-01 -5.41012526e-01 -1.22927308e+00 1.97629130e+00 5.38906157e-01 3.04535896e-01 2.01989323e-01 6.56610548e-01 5.60280859e-01 4.24183786e-01 -7.33523369e-02 -1.07989952e-01 1.13375509e+00 -3.21159899e-01 -4.10820693e-01 -7.19807968e-02 1.98405713e-01 -6.86853588e-01 1.00299048e+00 5.93348324e-01 -8.37501109e-01 -5.31730533e-01 -1.16125906e+00 6.11151993e-01 -6.19014204e-01 -1.39196694e-01 3.05447012e-01 1.59095502e+00 -1.04885781e+00 4.22547996e-01 -5.26331902e-01 -2.84264922e-01 8.87899220e-01 6.87433064e-01 -5.92520058e-01 9.94309336e-02 -1.11202788e+00 7.10121155e-01 -1.42263472e-02 2.08375588e-01 -1.29908431e+00 -7.86079824e-01 -5.67965150e-01 -8.45612064e-02 1.35324344e-01 -3.13795984e-01 7.13140309e-01 -1.37799799e+00 -1.80371249e+00 9.59081709e-01 2.25630879e-01 -3.72580886e-01 6.40646517e-01 6.53421283e-02 -9.46400464e-01 3.08867335e-01 -3.88020903e-01 3.79988164e-01 1.61277807e+00 -1.26103175e+00 -5.41273579e-02 -4.60850149e-01 8.11484903e-02 -3.60302895e-01 -7.22551167e-01 2.99833149e-01 1.61575094e-01 -7.63698697e-01 -4.86892432e-01 -7.30195165e-01 1.43156514e-01 6.52542105e-03 -6.43492222e-01 1.67415768e-01 1.45608723e+00 -3.62097383e-01 6.41131818e-01 -2.29364800e+00 -2.57018059e-01 4.49861884e-01 1.28939852e-01 1.02900016e+00 -7.18008578e-01 8.42089579e-02 -5.07432699e-01 1.83217615e-01 -1.78662017e-01 3.26056890e-02 -2.74287611e-01 5.86963296e-02 -7.00069368e-01 7.18213797e-01 6.81722164e-01 8.34759653e-01 -5.92987418e-01 1.01560615e-01 -5.25901318e-02 6.52217805e-01 -6.27661109e-01 4.26652789e-01 -1.06834173e-01 4.51349288e-01 -4.05432373e-01 8.76088381e-01 1.24436986e+00 6.44805491e-01 -9.41504613e-02 -1.36118680e-01 5.79030931e-01 -4.57689881e-01 -9.48344707e-01 6.06209159e-01 -1.20181397e-01 3.78427058e-01 3.53021383e-01 -8.85853171e-01 1.02839613e+00 1.83256477e-01 -6.06949404e-02 -5.23132741e-01 4.27263230e-01 4.28241305e-02 2.61379898e-01 -3.09788555e-01 -2.42880642e-01 -2.67649919e-01 1.52505696e-01 1.87925339e-01 2.80530274e-01 2.82387547e-02 -3.14230502e-01 2.38717478e-02 1.43481064e+00 -3.24572980e-01 -1.09658644e-01 -1.40897185e-01 7.76030064e-01 -5.63985348e-01 5.73674321e-01 6.20103955e-01 -2.39466056e-01 6.05043530e-01 7.21323907e-01 -4.35616732e-01 -6.75440133e-01 -1.28540814e+00 -7.90399686e-02 8.18332613e-01 -1.06985115e-01 -6.98791593e-02 -1.18843687e+00 -1.31361425e+00 1.56074911e-01 4.99875277e-01 -9.97604072e-01 -7.00922191e-01 -6.13275826e-01 -8.66891563e-01 1.34420693e+00 3.62738818e-01 5.67904294e-01 -9.82229888e-01 -2.58952558e-01 -2.06710041e-01 4.63064492e-01 -1.15027642e+00 -2.22364888e-01 -1.68801043e-02 -2.57438481e-01 -1.43431771e+00 -5.54194927e-01 -5.30568182e-01 1.03165603e+00 -2.74253935e-01 7.60551631e-01 3.58036101e-01 -8.48260522e-01 4.92653579e-01 -2.53597230e-01 -7.08122253e-01 -8.33004475e-01 -4.97196048e-01 4.51012641e-01 5.90833068e-01 2.52442628e-01 -4.90131348e-01 -4.19674695e-01 4.65899646e-01 -1.02349961e+00 -8.81973028e-01 4.56217170e-01 8.96747947e-01 1.31796315e-01 2.27291837e-01 7.73871124e-01 -1.09755433e+00 6.37712061e-01 -2.89402425e-01 -6.30043268e-01 1.15895003e-01 -2.17800543e-01 -2.17372358e-01 1.18889821e+00 -8.86896193e-01 -1.11928678e+00 -3.86046171e-02 -5.41676521e-01 -7.80927241e-01 -5.99662840e-01 -4.41676408e-01 -8.02281797e-01 -8.20388675e-01 1.23018730e+00 2.56658196e-01 1.40072167e-01 -5.58410287e-02 2.80747116e-01 3.70896816e-01 6.48559988e-01 -6.19580626e-01 1.56792796e+00 5.33135533e-01 3.53390932e-01 -1.06046212e+00 -4.53331500e-01 2.76983619e-01 -2.31131747e-01 -3.59010965e-01 4.89881486e-01 -4.05953974e-01 -8.72885942e-01 1.01134408e+00 -9.80702043e-01 -2.50273108e-01 -3.41186255e-01 -1.58042803e-01 -2.98515648e-01 4.58955795e-01 -5.68937540e-01 -7.88872004e-01 -3.70299399e-01 -1.02228951e+00 8.59034181e-01 3.06726754e-01 1.43619463e-01 -7.00294614e-01 -1.72345024e-02 1.43356264e-01 7.81416655e-01 7.19251275e-01 7.36161470e-01 -9.25370634e-01 -1.12364121e-01 -5.96839190e-01 8.63403305e-02 8.74220431e-01 3.88126373e-01 2.10722089e-01 -1.52626288e+00 -5.30227840e-01 2.84802377e-01 -5.88933289e-01 6.19027674e-01 -2.53801886e-02 1.33885431e+00 -6.10425591e-01 -1.78674817e-01 8.29903483e-01 1.14768744e+00 3.17808121e-01 1.01843989e+00 -1.74870208e-01 4.70508367e-01 6.74102128e-01 6.02391399e-02 2.07482457e-01 -6.03890717e-01 5.69656551e-01 8.35089862e-01 -3.72312784e-01 -2.37005979e-01 -1.66464522e-01 5.91417849e-01 -4.13587391e-01 -6.73188120e-02 -4.48695242e-01 -4.85783249e-01 6.47752509e-02 -9.99374568e-01 -1.09299588e+00 1.59258679e-01 2.12399936e+00 6.99040294e-01 2.16719478e-01 2.59308308e-01 1.94144011e-01 8.26532006e-01 -2.95066554e-02 -7.11654246e-01 -4.76770312e-01 -4.09127086e-01 8.99325967e-01 3.64777058e-01 2.63069928e-01 -1.18173671e+00 1.19379270e+00 6.30749273e+00 9.68727112e-01 -1.50909853e+00 8.73157755e-02 7.98743129e-01 -2.17879295e-01 8.17439929e-02 -3.16636682e-01 -8.37547719e-01 4.08031940e-01 8.35916698e-01 1.86411664e-01 4.21913534e-01 8.87727618e-01 -1.86816737e-01 3.67947340e-01 -9.80361462e-01 8.67491126e-01 4.74349260e-01 -1.10920703e+00 3.40945989e-01 1.24857403e-01 4.19578761e-01 -4.73796278e-01 6.66822374e-01 1.41531751e-01 3.16663027e-01 -1.28196716e+00 3.66132706e-01 2.48723984e-01 1.03310013e+00 -9.42465603e-01 6.26299143e-01 -1.66123658e-02 -6.71731174e-01 -2.29605377e-01 -3.99486184e-01 2.73397446e-01 -3.11040699e-01 3.56263369e-01 -7.47778654e-01 2.68053859e-01 5.58877707e-01 -7.58824572e-02 -7.20690310e-01 4.47966307e-01 -4.20323551e-01 8.13051879e-01 -4.74256158e-01 2.49008432e-01 -3.26160565e-02 2.91455805e-01 6.92031562e-01 1.07795119e+00 1.49206892e-01 2.50080407e-01 -2.64147609e-01 9.30293024e-01 -2.79565722e-01 -2.01694965e-01 -8.09418261e-01 5.52593432e-02 2.20773906e-01 1.46396422e+00 -6.09143317e-01 1.14242546e-01 2.78680492e-02 1.22855961e+00 1.79083005e-01 4.59848702e-01 -8.88041973e-01 -4.80878919e-01 1.11286712e+00 2.24510714e-01 2.00605199e-01 2.63940334e-01 2.03388229e-01 -1.10250580e+00 2.91853603e-02 -1.26958859e+00 4.01474327e-01 -3.77749473e-01 -1.69179630e+00 9.57067072e-01 -2.65936553e-01 -1.01314902e+00 -1.91929415e-01 -9.24508274e-01 -1.13163197e+00 8.75937045e-01 -1.25043023e+00 -1.40559793e+00 -3.14445108e-01 1.07826602e+00 1.91473052e-01 -6.72492325e-01 8.81541848e-01 1.12039156e-01 -7.29270935e-01 1.43335021e+00 -4.00330037e-01 5.46229124e-01 7.70439744e-01 -8.14298332e-01 4.91879314e-01 1.23014891e+00 2.62434874e-02 4.60692644e-01 6.43029809e-01 -5.86120963e-01 -1.38614476e+00 -1.29882681e+00 -1.57925144e-01 -5.03271699e-01 3.80738854e-01 -8.16206694e-01 -1.03167164e+00 4.74633783e-01 1.30466059e-01 4.98385221e-01 6.76012456e-01 -3.21527809e-01 -7.49993265e-01 -2.36626193e-01 -1.95426178e+00 6.43519163e-01 9.11891222e-01 -4.58267868e-01 -2.15139404e-01 3.90511811e-01 2.56991953e-01 -1.94111258e-01 -3.86753201e-01 6.02997780e-01 3.06081772e-01 -1.02627206e+00 1.01003528e+00 -9.18169737e-01 -8.85953754e-02 -3.80897492e-01 1.51801044e-02 -1.36785114e+00 -2.29180098e-01 -9.06862020e-01 -6.81555048e-02 1.49047768e+00 9.43088681e-02 -9.66335475e-01 9.93243635e-01 2.85785109e-01 1.75481454e-01 -5.15618205e-01 -1.11602449e+00 -1.02422404e+00 3.52981001e-01 -1.87578723e-01 7.37236798e-01 1.07450783e+00 -3.49025905e-01 -2.00675026e-01 -4.07606840e-01 7.23370612e-01 8.52492213e-01 -5.99724472e-01 9.43823934e-01 -9.70158935e-01 -3.25556964e-01 -4.36061502e-01 -9.54369903e-01 -2.35336915e-01 3.99149984e-01 -5.61528683e-01 -1.78194657e-01 -3.02235454e-01 -2.79812247e-01 -1.68371245e-01 1.84199102e-02 8.54216695e-01 -1.43425047e-01 9.09108639e-01 -7.77068436e-02 -2.49031976e-01 2.09466800e-01 4.80056047e-01 7.73845971e-01 -2.73514390e-01 1.05369516e-01 4.69560809e-02 -6.49012744e-01 7.53991902e-01 7.16908097e-01 -4.74032432e-01 -3.66626233e-01 1.19227432e-01 -2.96146959e-01 -4.84919488e-01 6.43983603e-01 -1.27227616e+00 -2.65934714e-03 -1.65607873e-02 8.51953566e-01 1.01744525e-01 3.15731376e-01 -6.35913670e-01 -2.16693506e-02 4.78661567e-01 2.46928111e-02 -2.88656116e-01 5.46386063e-01 3.76503646e-01 -5.16683683e-02 -1.19355507e-01 1.46043217e+00 1.30025029e-01 -3.20600301e-01 4.48559344e-01 -3.74269009e-01 5.82600534e-02 1.48802340e+00 -2.69029915e-01 -5.80571055e-01 -3.29530537e-01 -6.92734957e-01 -2.25499451e-01 4.83343005e-01 3.74691397e-01 8.40782523e-01 -1.05741560e+00 -8.59118879e-01 1.01033926e+00 -1.51251275e-02 -5.54119766e-01 3.18064034e-01 1.27875954e-01 -3.83457214e-01 -1.73717573e-01 -6.21936917e-01 -2.43492573e-01 -1.52229130e+00 8.82989109e-01 8.02082419e-01 2.74659365e-01 -3.06443006e-01 1.10121000e+00 4.44744706e-01 -2.07228497e-01 2.95252986e-02 4.87282664e-01 -2.89687999e-02 -2.40263253e-01 7.00505376e-01 5.17200530e-02 2.58320689e-01 -6.48754239e-01 -3.66384774e-01 4.68680739e-01 -1.30357146e-01 3.34977537e-01 9.18666601e-01 5.24165988e-01 -6.33607358e-02 -4.48478878e-01 1.04272354e+00 3.64752620e-01 -1.13746917e+00 2.40446106e-01 -3.84202242e-01 -7.13145614e-01 -2.70166844e-01 -8.43675733e-01 -1.59630620e+00 7.31673002e-01 9.32228863e-01 2.24885777e-01 1.63411152e+00 -9.09328982e-02 5.38671494e-01 2.00436935e-01 2.51836151e-01 -5.02654374e-01 3.80957395e-01 6.22511692e-02 9.40579951e-01 -9.47987735e-01 -3.67637187e-01 -5.37035465e-01 -2.86355734e-01 1.24128485e+00 1.05839705e+00 -2.91299999e-01 6.95713460e-01 5.75950503e-01 2.82670915e-01 -2.63419133e-02 -5.37641346e-01 1.44895047e-01 2.17713296e-01 1.13504243e+00 -1.13008596e-01 -3.11315954e-01 2.05444634e-01 4.65776086e-01 -2.01457992e-01 -4.35079128e-01 6.28012002e-01 7.88969755e-01 1.54238250e-02 -1.33804238e+00 -7.29453325e-01 3.68839324e-01 -6.30097806e-01 2.04030380e-01 -8.47124219e-01 7.63100743e-01 3.68144035e-01 8.91959369e-01 -1.14242777e-01 -5.93565345e-01 4.43165213e-01 1.51163951e-01 5.50126374e-01 -5.10568202e-01 -8.08907568e-01 -2.38409638e-01 -2.53889918e-01 -7.25738108e-01 2.07991097e-02 -4.58503515e-01 -7.99654543e-01 -4.04005021e-01 -3.21369529e-01 -2.49531269e-02 4.05315012e-01 7.52762139e-01 5.17321289e-01 3.11309934e-01 1.03535879e+00 -7.09102631e-01 -7.41427422e-01 -8.54496777e-01 -6.85297191e-01 5.76283932e-01 4.51819688e-01 -6.94445372e-01 -7.93734252e-01 -9.25714821e-02]	[12.792119979858398, 1.0910850763320923]
46add195-5e30-4ba1-ba24-b404307a475c	simf-semantics-aware-interactive-motion	2306.14941	null	https://arxiv.org/abs/2306.14941v1	https://arxiv.org/pdf/2306.14941v1.pdf	SIMF: Semantics-aware Interactive Motion Forecasting for Autonomous Driving	Autonomous vehicles require motion forecasting of their surrounding multi-agents (pedestrians and vehicles) to make optimal decisions for navigation. The existing methods focus on techniques to utilize the positions and velocities of these agents and fail to capture semantic information from the scene. Moreover, to mitigate the increase in computational complexity associated with the number of agents in the scene, some works leverage Euclidean distance to prune far-away agents. However, distance-based metric alone is insufficient to select relevant agents and accurately perform their predictions. To resolve these issues, we propose Semantics-aware Interactive Motion Forecasting (SIMF) method to capture semantics along with spatial information, and optimally select relevant agents for motion prediction. Specifically, we achieve this by implementing a semantic-aware selection of relevant agents from the scene and passing them through an attention mechanism to extract global encodings. These encodings along with agents' local information are passed through an encoder to obtain time-dependent latent variables for a motion policy predicting the future trajectories. Our results show that the proposed approach outperforms state-of-the-art baselines and provides more accurate predictions in a scene-consistent manner.	['Ahmed H. Qureshi', 'Vidyaa Krishnan Nivash']	2023-06-26	null	null	null	null	['motion-prediction', 'autonomous-vehicles', 'motion-forecasting']	['computer-vision', 'computer-vision', 'computer-vision']	[-1.36922702e-01 -2.20641851e-01 -4.71067667e-01 -5.96874475e-01 -6.01367354e-01 -4.32801187e-01 9.50031281e-01 1.52088791e-01 -8.28830063e-01 6.69803679e-01 6.12981498e-01 -9.71195698e-02 9.24772173e-02 -1.00659740e+00 -6.37945354e-01 -7.88175344e-01 -2.45280415e-01 6.20592952e-01 7.53583014e-01 -1.27460450e-01 5.04365623e-01 5.57004094e-01 -1.67977214e+00 1.55408815e-01 1.01906800e+00 7.22636342e-01 8.54805827e-01 7.88419724e-01 -1.53634489e-01 1.13101506e+00 -1.67165130e-01 -7.73692057e-02 1.44075438e-01 -1.96160629e-01 -5.40049255e-01 -1.56360924e-01 1.60151124e-01 -9.13152874e-01 -7.50175595e-01 8.87942970e-01 6.37936145e-02 8.02047431e-01 7.30779707e-01 -1.41698456e+00 -4.43338126e-01 3.75441641e-01 -3.05474162e-01 3.51180345e-01 1.49227723e-01 5.61250925e-01 8.69824827e-01 -7.21756041e-01 8.48774195e-01 1.44177115e+00 2.07538053e-01 5.28709352e-01 -6.08833373e-01 -3.33412677e-01 8.08150887e-01 7.79433608e-01 -1.19467878e+00 -5.64331174e-01 7.93417871e-01 -5.32451928e-01 1.12028134e+00 2.39863932e-01 7.08451807e-01 1.12297094e+00 1.11739628e-01 9.77710068e-01 3.41752887e-01 1.99454561e-01 5.25584221e-01 -1.81906104e-01 1.44731374e-02 7.55113780e-01 -1.29996063e-02 7.59918466e-02 -3.94661576e-01 -6.67911023e-02 5.24475574e-01 3.24277908e-01 1.93823464e-02 -3.58329266e-01 -1.32863581e+00 8.88003588e-01 6.04354262e-01 -1.51948556e-01 -9.05842006e-01 3.23266953e-01 2.07111180e-01 -3.07581455e-01 2.44631976e-01 1.42033130e-01 -2.23299608e-01 -2.03416452e-01 -6.59510970e-01 5.73702991e-01 3.05805773e-01 1.06537783e+00 1.01101875e+00 7.85194263e-02 -4.22077119e-01 5.11823773e-01 5.88473141e-01 6.18032873e-01 4.00744796e-01 -1.43174136e+00 7.09453583e-01 6.17553651e-01 5.63441932e-01 -1.38683891e+00 -4.84687656e-01 -8.43780711e-02 -3.97207260e-01 2.88153589e-01 2.50907987e-01 -1.66551098e-01 -9.91557539e-01 1.79143989e+00 5.10554254e-01 7.63642013e-01 2.41731837e-01 1.35666418e+00 4.02019262e-01 1.06040311e+00 5.22235513e-01 -9.64402966e-03 9.72833097e-01 -1.49060726e+00 -3.04920882e-01 -5.89834750e-01 7.21100748e-01 -3.04446816e-01 6.87090099e-01 -2.00893611e-01 -7.45557606e-01 -5.21816611e-01 -8.83580685e-01 -2.70554889e-02 -2.89470881e-01 8.99772346e-03 4.62339759e-01 7.63190463e-02 -1.04236817e+00 2.70782769e-01 -1.14238071e+00 -3.61302793e-01 4.15304482e-01 2.23634556e-01 -1.93376780e-01 -1.58519328e-01 -9.78750110e-01 1.03719461e+00 3.07170719e-01 3.05773076e-02 -1.23677313e+00 -2.72402376e-01 -1.04124939e+00 -2.21289918e-01 3.07692647e-01 -8.75878990e-01 1.12385619e+00 -7.07261682e-01 -1.36261320e+00 1.07352668e-02 -6.77732646e-01 -6.07053995e-01 4.43314821e-01 -1.38836086e-01 -2.39324734e-01 1.40966788e-01 4.74736989e-01 8.88654292e-01 4.83924389e-01 -1.38567412e+00 -1.42359173e+00 -3.65093440e-01 2.45905876e-01 7.35899806e-01 -2.25329008e-02 -2.78804898e-01 -8.58749568e-01 -2.94152558e-01 1.84344575e-01 -1.02195621e+00 -8.39398742e-01 -1.55710131e-01 -3.33043247e-01 -2.05081537e-01 1.02130008e+00 -5.93349516e-01 1.02299654e+00 -1.72078526e+00 1.64655596e-01 2.04938725e-02 1.54273182e-01 2.17118964e-01 -4.23425406e-01 3.74025494e-01 8.07079971e-01 -2.44741723e-01 6.93226308e-02 -6.78412557e-01 7.90753812e-02 4.70154226e-01 -2.97794580e-01 5.10648310e-01 -5.76804727e-02 9.43134487e-01 -1.23964500e+00 -4.51982945e-01 7.66437292e-01 5.74372232e-01 -6.34521782e-01 1.51077539e-01 -5.64864755e-01 7.32373536e-01 -1.15672755e+00 2.94858158e-01 5.58039248e-01 -1.04204789e-01 -9.41432565e-02 1.89976931e-01 -3.25266242e-01 4.25579160e-01 -8.86374474e-01 1.60516346e+00 -2.89022416e-01 6.22597694e-01 -1.35628894e-01 -8.05579484e-01 6.60041094e-01 -3.80708389e-02 5.02990782e-01 -9.14109647e-01 -2.00826734e-01 -3.82309183e-02 -4.19822186e-01 -6.38525486e-01 8.45237434e-01 4.90684658e-01 1.57715881e-03 9.52647701e-02 -5.93197584e-01 6.11423492e-01 1.05721831e-01 1.95117831e-01 1.10288000e+00 2.79210836e-01 -8.98922309e-02 1.97250783e-01 5.96306741e-01 5.31407058e-01 8.17682862e-01 7.93938577e-01 -5.03553927e-01 3.05057019e-01 -4.52956706e-02 -8.23475182e-01 -1.08909035e+00 -7.50342667e-01 6.82378948e-01 1.27268255e+00 7.81629264e-01 -3.77784818e-01 -6.15771472e-01 -6.25318348e-01 -1.74712211e-01 1.07962370e+00 -5.60555339e-01 -3.09653766e-02 -9.94763076e-01 -5.64179718e-01 -9.70316399e-03 6.01313233e-01 4.97803330e-01 -9.13519382e-01 -1.06696594e+00 4.30759549e-01 -3.98486108e-01 -1.18553185e+00 -3.70103747e-01 -4.09362316e-01 -5.02245069e-01 -8.91193032e-01 -4.14055079e-01 -5.46281338e-01 7.32651770e-01 6.77064478e-01 6.23786032e-01 -1.76916253e-02 2.59343475e-01 -9.88857262e-03 -3.86573970e-01 1.03838183e-01 -2.92933285e-01 1.51526839e-01 -2.81240344e-02 7.50534981e-02 4.38706219e-01 -2.69504517e-01 -1.05304456e+00 2.51473874e-01 -3.02530378e-01 5.58911085e-01 4.59190726e-01 3.72471422e-01 5.71912110e-01 1.05337121e-01 4.01292890e-01 -5.58605909e-01 1.07889675e-01 -8.49556923e-01 -6.62661910e-01 3.13604474e-02 -3.38554025e-01 2.09566981e-01 8.36374581e-01 -2.16960117e-01 -1.12752867e+00 2.77457237e-01 -8.77770558e-02 -3.68471652e-01 -3.08515966e-01 2.46134043e-01 -1.60182774e-01 3.04561853e-01 1.63856134e-01 3.55244309e-01 -4.53098327e-01 -1.02901720e-01 4.28674310e-01 4.09138411e-01 5.38346469e-01 -1.77588239e-01 4.74729270e-01 7.30296791e-01 -3.96523923e-02 -5.66272080e-01 -5.06032467e-01 -5.55349410e-01 -5.01155913e-01 -3.89711380e-01 1.04021430e+00 -1.06572092e+00 -6.75567627e-01 3.24726939e-01 -1.31445014e+00 -5.01358151e-01 2.33909518e-01 7.60782063e-01 -6.44971132e-01 1.46485463e-01 -4.93339956e-01 -1.07088947e+00 7.62056932e-02 -1.55525768e+00 1.21930385e+00 3.70050043e-01 -5.98559342e-02 -9.92993057e-01 -2.00252086e-02 3.02548617e-01 4.11376268e-01 1.29897505e-01 6.20519936e-01 -4.24263299e-01 -1.31055462e+00 -7.45038092e-02 -1.78795606e-01 -5.88527381e-01 -8.23876113e-02 -1.89316541e-01 -6.77615881e-01 -9.96740088e-02 -4.15108621e-01 3.59690458e-01 1.04124939e+00 6.52731061e-01 7.47330070e-01 -6.89612985e-01 -9.06513631e-01 5.54476202e-01 1.33100975e+00 5.53395987e-01 3.89248371e-01 6.34889960e-01 1.00010967e+00 7.58168340e-01 9.66704249e-01 6.44671440e-01 1.34992826e+00 9.32880044e-01 8.62975180e-01 3.58894825e-01 -1.69293731e-02 -5.11744440e-01 3.41412038e-01 4.43145275e-01 -9.16664228e-02 -6.73544466e-01 -8.64333749e-01 7.71744132e-01 -2.45657635e+00 -1.22497106e+00 -1.67997301e-01 1.93106675e+00 5.94478250e-02 -1.41557440e-01 1.45355329e-01 -5.33162951e-01 6.98105991e-01 4.93853301e-01 -8.13971460e-01 1.67457536e-01 -2.07778458e-02 -9.71883118e-01 8.03874969e-01 9.53990877e-01 -1.25883913e+00 1.40651715e+00 5.66534472e+00 6.32147968e-01 -9.75587428e-01 1.57208398e-01 6.67819798e-01 -1.82825938e-01 -5.65440416e-01 1.50992081e-01 -9.49279606e-01 6.54626369e-01 9.10408199e-01 2.16243878e-01 3.65306824e-01 8.47081840e-01 8.72363091e-01 -2.02882424e-01 -7.57243335e-01 7.86563337e-01 -1.20698549e-01 -1.57064927e+00 1.83098078e-01 9.67666041e-03 8.08079660e-01 4.20567155e-01 -8.17314684e-02 2.10836366e-01 6.26638412e-01 -8.96956801e-01 8.44827592e-01 8.56663883e-01 -1.51928395e-01 -8.41674149e-01 4.71872866e-01 6.41811848e-01 -1.38977516e+00 -3.69550854e-01 -4.51733351e-01 -1.76918805e-01 5.96490145e-01 -5.85892936e-03 -1.00321758e+00 3.41313243e-01 4.02996182e-01 8.75932157e-01 -3.37073743e-01 1.02936995e+00 -3.52118462e-02 3.04569006e-01 -2.75100768e-01 -2.19716385e-01 8.25802803e-01 -2.74709851e-01 7.51618624e-01 1.04693294e+00 5.23415625e-01 1.92126036e-01 7.21688032e-01 5.74840903e-01 4.74575937e-01 -5.39534651e-02 -5.01004100e-01 3.53960752e-01 8.53412807e-01 9.22902405e-01 -8.37088287e-01 -6.10436499e-01 -5.54066241e-01 1.02652812e+00 4.02767122e-01 7.10964262e-01 -9.53380823e-01 1.70891464e-01 1.12580752e+00 4.93092835e-02 2.91906834e-01 -6.52350664e-01 -1.60778612e-01 -8.75703931e-01 -1.21219970e-01 -2.54287988e-01 2.03364015e-01 -6.54992580e-01 -6.94563687e-01 6.52680814e-01 -1.39994040e-01 -1.18567777e+00 -6.66899800e-01 -2.07954496e-01 -5.17947495e-01 8.10133100e-01 -1.70046020e+00 -1.34690368e+00 -3.69079232e-01 4.82102305e-01 1.04903781e+00 -2.87738830e-01 4.51759547e-01 1.87229589e-01 -4.51949924e-01 -4.12860774e-02 7.57521093e-02 -6.23982288e-02 1.94041044e-01 -9.58591878e-01 7.87237108e-01 1.07125306e+00 -5.81384338e-02 2.71168739e-01 8.32064986e-01 -7.70555794e-01 -1.52598453e+00 -1.55376470e+00 1.00295913e+00 -5.56578398e-01 2.28429615e-01 1.75218120e-01 -6.62471592e-01 7.83090889e-01 -1.59139588e-01 -4.79992703e-02 1.61140546e-01 -4.54837710e-01 -3.24784704e-02 1.71546370e-01 -7.78869331e-01 1.14916503e+00 1.22827113e+00 -1.39285415e-01 -1.56693637e-01 1.48098946e-01 7.88748503e-01 -3.49741727e-01 -1.70113087e-01 2.83138156e-01 3.99471790e-01 -9.95075285e-01 1.20907056e+00 -4.26947922e-01 1.89078376e-01 -7.27567434e-01 -3.44165415e-01 -1.18718624e+00 -5.02616823e-01 -2.91466296e-01 -1.42297760e-01 7.62866855e-01 3.40169996e-01 -5.51239908e-01 1.00769067e+00 1.00173986e+00 -4.15646046e-01 -6.50208116e-01 -8.48246276e-01 -2.70112425e-01 -3.95565152e-01 -5.62633157e-01 8.92656088e-01 5.89567602e-01 -3.14492375e-01 9.18326154e-02 -6.59330010e-01 7.67882407e-01 4.52017993e-01 2.96228349e-01 9.47964966e-01 -8.26946616e-01 5.66136986e-02 -5.85965157e-01 -6.38027847e-01 -1.65132070e+00 3.84568661e-01 -5.55477738e-01 3.77448559e-01 -2.08748460e+00 2.12304264e-01 -7.05954552e-01 -5.09095788e-02 3.33422542e-01 -2.98470348e-01 -1.27007082e-01 2.50275433e-01 5.37267983e-01 -1.15262067e+00 7.78922439e-01 1.20870090e+00 -1.17545724e-01 -3.75037700e-01 1.16806021e-02 -2.22775459e-01 8.31395328e-01 6.96055293e-01 -2.65328497e-01 -8.21764708e-01 -8.78188908e-01 -1.06484622e-01 3.69693190e-01 6.35798097e-01 -1.08641005e+00 7.62764037e-01 -8.38927031e-01 3.18525612e-01 -9.82323945e-01 8.61251235e-01 -7.44848549e-01 2.71876961e-01 3.24466407e-01 -4.46102530e-01 2.53605127e-01 -1.91304326e-01 8.91610682e-01 -7.48995468e-02 -1.19775862e-01 3.33795637e-01 -1.73326343e-01 -1.55653095e+00 8.07797611e-01 -7.23316491e-01 -2.52772123e-01 1.25584793e+00 -2.76255220e-01 -3.88579875e-01 -6.17476761e-01 -4.25809741e-01 7.63422489e-01 7.27780223e-01 6.42776549e-01 6.73377097e-01 -1.24338961e+00 -6.30168438e-01 1.16047144e-01 -2.15567648e-02 1.24351442e-01 6.09868586e-01 5.68678319e-01 -6.16516232e-01 5.21889985e-01 -1.27813697e-01 -6.05188429e-01 -9.75660086e-01 6.01060867e-01 1.43048793e-01 7.19314069e-02 -7.96381056e-01 7.37472177e-01 4.72808838e-01 -2.07665056e-01 1.04068570e-01 -2.31827989e-01 -5.29514551e-01 -1.43725798e-01 7.24664748e-01 4.68782067e-01 -3.84047240e-01 -1.26909995e+00 -5.27332962e-01 4.65124369e-01 1.61081731e-01 -4.32280928e-01 1.20376551e+00 -7.97858179e-01 3.40587258e-01 2.35123888e-01 1.06403708e+00 -1.49175093e-01 -2.04448605e+00 -1.63575023e-01 2.86250673e-02 -7.08839715e-01 -4.81957980e-02 -4.33101445e-01 -1.01272976e+00 6.47455692e-01 2.42715880e-01 -9.60503221e-02 7.40335286e-01 -1.03558332e-01 1.17877579e+00 2.43649304e-01 6.44485116e-01 -1.10731649e+00 -2.38664776e-01 6.54468715e-01 4.06199306e-01 -1.38563085e+00 -3.51412117e-01 -2.58201540e-01 -1.01558018e+00 8.21774662e-01 8.60837817e-01 -3.50451991e-02 3.07278335e-01 4.37518675e-03 7.35421181e-02 1.09455854e-01 -1.05579877e+00 -4.96211916e-01 1.18967503e-01 8.07311177e-01 -1.97814941e-01 2.14462206e-01 1.99891314e-01 3.18426192e-01 -7.88862258e-02 -3.25389773e-01 1.95556298e-01 7.37918019e-01 -9.09410894e-01 -7.95673549e-01 -1.58197507e-01 2.34900504e-01 8.10441002e-02 2.56272912e-01 1.30967960e-01 2.41479978e-01 1.69799462e-01 1.13893831e+00 2.49880821e-01 -4.48190212e-01 3.21156681e-02 -2.40072235e-01 -2.63778362e-02 -3.16165000e-01 8.75131562e-02 -1.03383586e-01 2.58077919e-01 -7.89366484e-01 -3.74581128e-01 -7.35199094e-01 -1.69192898e+00 -4.52967048e-01 1.58194870e-01 -7.77818263e-02 5.16056895e-01 1.14931726e+00 7.87697673e-01 4.09325510e-01 4.22221184e-01 -1.33313262e+00 -8.38211700e-02 -5.08557022e-01 4.87283580e-02 4.66050208e-01 6.44827664e-01 -7.81266689e-01 5.96239604e-02 -6.74170256e-02]	[5.94264554977417, 0.8018349409103394]
fe6ad8d0-e92e-43c1-a931-760d3f4fc95f	to-pretrain-or-not-to-pretrain-a-case-study	2307.03275	null	https://arxiv.org/abs/2307.03275v1	https://arxiv.org/pdf/2307.03275v1.pdf	To pretrain or not to pretrain? A case study of domain-specific pretraining for semantic segmentation in histopathology	Annotating medical imaging datasets is costly, so fine-tuning (or transfer learning) is the most effective method for digital pathology vision applications such as disease classification and semantic segmentation. However, due to texture bias in models trained on real-world images, transfer learning for histopathology applications might result in underperforming models, which necessitates the need for using unlabeled histopathology data and self-supervised methods to discover domain-specific characteristics. Here, we tested the premise that histopathology-specific pretrained models provide better initializations for pathology vision tasks, i.e., gland and cell segmentation. In this study, we compare the performance of gland and cell segmentation tasks with domain-specific and non-domain-specific pretrained weights. Moreover, we investigate the data size at which domain-specific pretraining produces a statistically significant difference in performance. In addition, we investigated whether domain-specific initialization improves the effectiveness of out-of-domain testing on distinct datasets but the same task. The results indicate that performance gain using domain-specific pretraining depends on both the task and the size of the training dataset. In instances with limited dataset sizes, a significant improvement in gland segmentation performance was also observed, whereas models trained on cell segmentation datasets exhibit no improvement.	['Shireen Elhabian', 'Beatrice Knudsen', 'Tushar Kataria']	2023-07-06	null	null	null	null	['cell-segmentation', 'transfer-learning']	['medical', 'miscellaneous']	[ 3.41187000e-01 1.54618949e-01 -2.14965209e-01 -5.82723558e-01 -8.79967391e-01 -5.02052009e-01 3.44435215e-01 3.90414119e-01 -7.50301540e-01 6.74331129e-01 3.69520305e-04 -3.98224115e-01 -3.99064757e-02 -7.23142326e-01 -7.27676451e-01 -9.25138652e-01 1.98935136e-01 6.71426058e-01 2.86916196e-01 1.09865718e-01 -5.14884070e-02 4.68357235e-01 -1.07284319e+00 5.00836670e-01 8.56460392e-01 6.96144879e-01 3.39933604e-01 6.31269932e-01 -3.06085527e-01 2.98667341e-01 -5.51726520e-01 -2.41757601e-01 1.29461080e-01 -3.33339989e-01 -9.17414963e-01 4.49228168e-01 4.56180930e-01 -1.03864074e-01 1.37461349e-01 1.00904083e+00 4.17341620e-01 -2.78740555e-01 7.61691988e-01 -7.87511587e-01 -4.26046699e-01 5.22490263e-01 -4.12507087e-01 3.23078871e-01 -3.15789938e-01 4.25797373e-01 6.54038072e-01 -3.26346517e-01 9.56090331e-01 7.30340958e-01 7.42192686e-01 6.94703758e-01 -1.53684926e+00 -5.44576585e-01 -2.10637003e-01 -1.79009646e-01 -1.13240933e+00 -1.76621258e-01 5.10214508e-01 -5.82544029e-01 6.56774342e-01 1.02610961e-01 3.77082020e-01 8.84068549e-01 2.44004294e-01 5.51519215e-01 1.47035694e+00 -2.71922380e-01 2.60219514e-01 5.65047920e-01 1.68197334e-01 6.12756491e-01 4.86312747e-01 -5.20237647e-02 1.28161116e-02 -8.29330757e-02 9.31300998e-01 -2.47571602e-01 -1.13553979e-01 -4.67553705e-01 -1.23956561e+00 7.54170835e-01 5.79675972e-01 6.66016221e-01 -1.46349207e-01 -2.88342476e-01 6.03196681e-01 3.11434060e-01 5.08673966e-01 7.28009105e-01 -7.00282037e-01 2.38662958e-01 -9.35197055e-01 -3.29710096e-01 6.89941049e-01 2.99696028e-01 6.62195086e-01 -1.85224116e-01 1.81085821e-02 7.96802878e-01 -2.62546577e-02 3.13986801e-02 9.52746987e-01 -5.50458968e-01 -4.78554219e-02 8.43504250e-01 -4.02331054e-01 -4.37243342e-01 -7.35835612e-01 -7.49063313e-01 -7.08402812e-01 6.08466268e-02 1.02293301e+00 -2.26141304e-01 -1.52918696e+00 1.60957956e+00 2.13748217e-01 1.87790822e-02 2.05590874e-01 9.98853147e-01 7.62633264e-01 1.04456916e-01 4.01111722e-01 2.78913463e-03 1.30180311e+00 -7.10174680e-01 -3.93360883e-01 -2.81496733e-01 1.09907758e+00 -6.61173403e-01 1.09104156e+00 3.83581705e-02 -6.39653802e-01 -3.72735918e-01 -8.04241538e-01 6.57635108e-02 -4.93972510e-01 1.26523256e-01 7.38089502e-01 6.12292051e-01 -9.05864954e-01 3.42511088e-01 -1.00637257e+00 -7.73821712e-01 5.48240125e-01 7.06791997e-01 -5.78136384e-01 -1.34169996e-01 -6.30629361e-01 9.91721272e-01 5.27240813e-01 -3.18240643e-01 -8.55210602e-01 -9.87285316e-01 -4.72337812e-01 -6.59096390e-02 5.53714111e-02 -5.77535808e-01 1.05368912e+00 -1.18956733e+00 -9.84731138e-01 1.44780374e+00 9.20188054e-02 -6.64792657e-01 4.95156527e-01 4.57558692e-01 -1.90286234e-01 1.16754331e-01 1.23220615e-01 1.03045619e+00 4.89666641e-01 -1.27794993e+00 -4.21015084e-01 -5.66350043e-01 -1.35716334e-01 5.70021989e-03 -4.47473437e-01 -2.79763222e-01 -3.63986075e-01 -4.20362920e-01 8.32672790e-03 -1.08518505e+00 -3.74091893e-01 3.79817262e-02 -7.50351930e-03 -1.53791904e-02 7.58664191e-01 -6.24955118e-01 5.26176333e-01 -2.44174814e+00 -2.44660333e-01 3.94884080e-01 1.80420857e-02 2.62752831e-01 -1.57990351e-01 -1.46688566e-01 -1.23556167e-01 2.36384973e-01 -1.89127415e-01 1.01626880e-01 -3.58028591e-01 3.67541462e-01 4.80322003e-01 5.23292124e-01 4.54743087e-01 8.73430312e-01 -7.04712510e-01 -8.19655776e-01 8.31466448e-03 2.98310280e-01 -5.39996862e-01 -5.68594895e-02 -2.84017682e-01 8.43673825e-01 -3.34877670e-01 7.13449895e-01 3.10040355e-01 -6.11201346e-01 3.51515114e-01 -2.79489189e-01 1.99619263e-01 -1.31896451e-01 -5.68428218e-01 1.54646015e+00 -4.91875708e-01 5.56472719e-01 1.79907039e-01 -1.12016916e+00 7.46495903e-01 2.66965270e-01 5.57016790e-01 -7.32129216e-01 2.57129192e-01 3.74133945e-01 5.97854853e-01 -4.14723068e-01 1.24360882e-01 -4.26496655e-01 1.44895300e-01 2.26905614e-01 2.74394691e-01 -1.41171396e-01 2.74208814e-01 -1.40475646e-01 1.18836689e+00 -2.14858681e-01 -8.70075834e-04 -4.91104692e-01 3.77127320e-01 5.40863574e-01 4.71290261e-01 3.92465711e-01 -3.72763753e-01 6.29172266e-01 5.18562019e-01 -3.88049930e-01 -8.39555562e-01 -7.37271488e-01 -5.29063702e-01 1.10122406e+00 -5.71077503e-02 1.47362337e-01 -7.65603960e-01 -9.92094338e-01 1.15949862e-01 4.60653573e-01 -9.57888067e-01 -1.70672685e-01 -3.02185118e-01 -1.22423160e+00 5.59462070e-01 6.04894400e-01 4.60717231e-01 -9.39846933e-01 -4.84503090e-01 -2.56840419e-02 6.15556054e-02 -1.13687217e+00 -2.05829963e-01 6.20868564e-01 -1.31278980e+00 -1.13425398e+00 -9.98317540e-01 -1.06344688e+00 1.34297478e+00 2.37448439e-02 9.60983276e-01 2.43046030e-01 -4.73550349e-01 3.02290648e-01 -1.13469437e-01 -5.19661009e-01 -5.97212970e-01 2.89648801e-01 -4.78170991e-01 -8.46130699e-02 3.72545123e-01 -7.70643130e-02 -5.04390001e-01 4.50408012e-01 -1.11671400e+00 -5.55603839e-02 1.05686784e+00 1.10630250e+00 7.86918998e-01 1.38661414e-01 4.75156128e-01 -1.29696715e+00 5.42355955e-01 -1.61999315e-01 -2.63391078e-01 3.11872989e-01 -5.53778291e-01 1.44890666e-01 3.03584099e-01 -5.92828870e-01 -9.87383604e-01 2.48189822e-01 1.11327179e-01 -1.56932294e-01 -2.88653582e-01 7.69208252e-01 2.49822482e-01 -3.66627902e-01 9.96689558e-01 -6.87894896e-02 4.35665369e-01 -1.63954303e-01 -2.85827339e-01 3.45412254e-01 3.45751822e-01 -5.00956237e-01 4.91563499e-01 5.59676349e-01 -1.99078619e-02 -5.94088972e-01 -6.71281338e-01 -5.43687642e-01 -6.31358862e-01 8.05073045e-03 1.12554371e+00 -7.71254241e-01 -2.68832296e-02 3.36875439e-01 -4.99719501e-01 -9.13344204e-01 -3.72314125e-01 5.84816933e-01 -2.86461771e-01 7.35024586e-02 -5.47349393e-01 -9.46335346e-02 -1.56338990e-01 -1.31884158e+00 8.28727841e-01 2.80463576e-01 -3.19183946e-01 -1.31317139e+00 -5.95647879e-02 5.35127342e-01 4.14383292e-01 2.52357185e-01 1.15973353e+00 -1.02921581e+00 -2.99673736e-01 -3.55769545e-01 -3.50704879e-01 3.06688607e-01 3.31229836e-01 -1.10836737e-01 -8.40282440e-01 -2.61279702e-01 -3.12162548e-01 -4.74707991e-01 9.10605490e-01 4.89340127e-01 1.19194102e+00 2.21803606e-01 -4.80348617e-01 4.55732256e-01 1.30688012e+00 2.66417414e-02 4.38648045e-01 5.16492009e-01 3.22854936e-01 7.67695427e-01 4.61074710e-01 -1.13044344e-01 2.17575580e-01 3.08994681e-01 1.97619587e-01 -6.16667092e-01 -3.53740126e-01 7.43245780e-02 -2.07674518e-01 2.30604216e-01 2.30027493e-02 6.19137995e-02 -1.34162641e+00 8.07117760e-01 -1.28791916e+00 -2.58739531e-01 3.75171192e-02 2.06244254e+00 1.10642004e+00 3.67966413e-01 8.66960660e-02 -7.79170617e-02 5.99811196e-01 -5.06487012e-01 -6.30838215e-01 -1.62803352e-01 -3.60542387e-02 2.28950292e-01 7.97066629e-01 5.58868609e-02 -1.02665317e+00 7.54196465e-01 6.27151966e+00 6.17971599e-01 -1.63833666e+00 1.60773441e-01 1.03993356e+00 1.63618892e-01 -4.88119051e-02 -2.28928149e-01 -4.50737566e-01 3.27903509e-01 9.31205869e-01 1.18583910e-01 -1.00321732e-01 7.15097129e-01 1.79574080e-02 -3.27025622e-01 -1.17810023e+00 5.01030445e-01 -1.27105460e-01 -1.19419682e+00 -8.73588473e-02 4.43678558e-01 9.06930029e-01 4.36129868e-02 1.57234401e-01 4.43191409e-01 7.67519400e-02 -9.99277949e-01 -2.44587567e-02 1.12069383e-01 7.38997936e-01 -3.41799349e-01 1.34065962e+00 1.79108679e-01 -4.54975635e-01 2.39818007e-01 -2.83003598e-01 3.56164515e-01 -3.55281800e-01 5.49853504e-01 -1.45534050e+00 1.62957564e-01 6.09253883e-01 1.99198171e-01 -9.05048490e-01 1.16594481e+00 1.96787894e-01 8.81748855e-01 -1.77635685e-01 5.41548021e-02 3.19547325e-01 1.69670954e-01 -5.88591844e-02 1.25695634e+00 3.80196832e-02 -1.44404501e-01 2.18899116e-01 4.39916402e-01 -3.86653990e-02 7.68408626e-02 -1.92457005e-01 -2.68023461e-01 -7.35686102e-04 1.34878182e+00 -1.38930595e+00 -2.65112251e-01 -4.29503292e-01 4.83603239e-01 1.61591008e-01 2.22519889e-01 -7.20554411e-01 1.45273581e-01 2.79554158e-01 3.64558905e-01 2.77366251e-01 8.55261981e-02 -7.82502294e-01 -7.28756309e-01 -4.52035397e-01 -7.82943070e-01 5.93954325e-01 -3.79259884e-01 -1.39329314e+00 3.13753724e-01 -1.63522914e-01 -9.43680108e-01 -1.33822281e-02 -7.55957067e-01 -4.91612703e-01 6.21705413e-01 -1.50367260e+00 -1.16429031e+00 -4.62467074e-01 4.60337460e-01 2.80108035e-01 3.54906097e-02 9.14785326e-01 2.06547901e-01 -4.42702085e-01 7.93864191e-01 1.15141802e-01 4.62765515e-01 1.10892069e+00 -1.32367134e+00 -3.09973180e-01 3.45739484e-01 -1.66573599e-01 4.72113878e-01 5.48307359e-01 -6.47146165e-01 -9.95812058e-01 -1.14040685e+00 4.54510272e-01 -1.66783601e-01 6.59676254e-01 -4.27282677e-04 -9.84449089e-01 5.74970186e-01 -3.90148163e-02 2.86219865e-01 1.11925876e+00 2.81793118e-01 -9.06098932e-02 -6.85195401e-02 -1.60194123e+00 4.21694815e-01 5.82937658e-01 -3.92584026e-01 -3.26329559e-01 4.70375508e-01 2.88665414e-01 -5.88071048e-01 -1.20063615e+00 6.21348083e-01 4.50494826e-01 -5.26998580e-01 6.99009001e-01 -5.65142512e-01 4.29433763e-01 -1.84981301e-02 1.24297075e-01 -1.15770626e+00 -3.27582926e-01 3.41974199e-01 4.74232703e-01 1.01811755e+00 8.18807542e-01 -6.74929380e-01 1.27398431e+00 8.09717894e-01 -2.34992489e-01 -6.64339244e-01 -6.18402123e-01 -6.94347858e-01 3.74416083e-01 5.17015271e-02 2.03878835e-01 1.08470225e+00 -2.13150352e-01 6.64880092e-04 5.69215536e-01 1.58089235e-01 3.66328329e-01 3.46056819e-02 6.22560263e-01 -1.18155670e+00 -1.89853802e-01 -4.11279738e-01 -5.93608260e-01 -1.96673930e-01 2.38772169e-01 -1.16861248e+00 9.90007669e-02 -1.48822081e+00 3.19202513e-01 -6.66963339e-01 -5.15616953e-01 7.18610168e-01 -1.87921032e-01 4.94468838e-01 -3.46343545e-03 2.17610881e-01 -4.60251391e-01 -3.01180154e-01 1.52859414e+00 -3.77125293e-01 -3.01345408e-01 2.09368635e-02 -7.34963000e-01 4.99885708e-01 1.08470213e+00 -4.15148497e-01 -3.40365052e-01 -3.96208882e-01 -3.72432381e-01 -1.09697491e-01 4.42044079e-01 -1.12333643e+00 2.18488201e-01 6.23315610e-02 7.51034558e-01 -2.59544820e-01 1.19786836e-01 -7.22946465e-01 7.86381587e-02 7.42339015e-01 -3.76959413e-01 -4.77857411e-01 5.75118721e-01 3.79792601e-01 -2.70572633e-01 -3.88920605e-01 8.03088009e-01 -4.07684237e-01 -6.92901075e-01 -3.52930985e-02 -4.86150891e-01 -1.54442498e-02 1.02365196e+00 -5.45628667e-01 -3.01775664e-01 3.67850438e-02 -9.48191762e-01 1.63781509e-01 5.86538136e-01 7.89614022e-02 1.15654133e-01 -7.54040360e-01 -8.22032988e-01 2.06074882e-02 2.47284144e-01 1.52073935e-01 2.46768266e-01 1.06340468e+00 -6.34975135e-01 4.75833595e-01 -4.06483799e-01 -9.70778823e-01 -1.36732006e+00 2.40901902e-01 4.17030066e-01 -7.48161674e-01 1.11031802e-02 9.79022443e-01 5.00309825e-01 -6.40178680e-01 1.32002532e-01 -4.71565902e-01 6.44088769e-03 -5.97335286e-02 2.12236121e-02 -1.34224920e-02 5.20536125e-01 -3.07669759e-01 -3.75255376e-01 2.26504385e-01 -4.93553191e-01 1.89177051e-01 1.19181275e+00 3.96969408e-01 9.69060361e-02 2.29639396e-01 1.07669532e+00 -3.62541348e-01 -1.11757100e+00 -8.29429850e-02 1.91058800e-01 -5.01456670e-02 3.40654016e-01 -1.19132721e+00 -1.20232260e+00 5.94170094e-01 8.85516107e-01 -1.22652046e-01 1.04260862e+00 7.80417919e-02 4.15094346e-01 2.50183433e-01 2.99306512e-01 -9.73068297e-01 -5.18964045e-02 1.65816173e-01 4.09117550e-01 -1.53348613e+00 -8.35921317e-02 -5.26158631e-01 -6.37433290e-01 8.85391831e-01 9.30512846e-01 7.63280466e-02 5.10969937e-01 2.58892119e-01 3.74433547e-01 -2.44032085e-01 -5.28450429e-01 -3.17344457e-01 2.73468167e-01 7.46803045e-01 6.27603590e-01 1.46459535e-01 -4.66013879e-01 4.80005562e-01 -1.43818945e-01 2.93260574e-01 3.84094715e-01 1.10911310e+00 -2.16949508e-01 -1.10135376e+00 -3.90736759e-01 9.36912477e-01 -6.13700509e-01 1.76097125e-01 -6.68287039e-01 1.07411397e+00 1.85809553e-01 5.73570073e-01 2.76064396e-01 -1.34453222e-01 -2.71030068e-02 9.97059420e-02 5.23859739e-01 -8.75853240e-01 -8.52499962e-01 3.00657842e-02 5.28586581e-02 -3.99512351e-02 -4.73443151e-01 -5.18237352e-01 -1.50582623e+00 -1.14919338e-02 -4.83336419e-01 1.30893618e-01 7.06256449e-01 8.06114972e-01 2.24543527e-01 6.50356352e-01 2.00777367e-01 -3.52411509e-01 -3.20315152e-01 -1.04690278e+00 -3.10441583e-01 5.04640162e-01 -1.48452232e-02 -4.09261376e-01 -2.48279035e-01 2.89377183e-01]	[15.047077178955078, -2.6620988845825195]
6f898422-8361-4225-95a3-dddd66832774	clipcrop-conditioned-cropping-driven-by	2211.11492	null	https://arxiv.org/abs/2211.11492v1	https://arxiv.org/pdf/2211.11492v1.pdf	ClipCrop: Conditioned Cropping Driven by Vision-Language Model	Image cropping has progressed tremendously under the data-driven paradigm. However, current approaches do not account for the intentions of the user, which is an issue especially when the composition of the input image is complex. Moreover, labeling of cropping data is costly and hence the amount of data is limited, leading to poor generalization performance of current algorithms in the wild. In this work, we take advantage of vision-language models as a foundation for creating robust and user-intentional cropping algorithms. By adapting a transformer decoder with a pre-trained CLIP-based detection model, OWL-ViT, we develop a method to perform cropping with a text or image query that reflects the user's intention as guidance. In addition, our pipeline design allows the model to learn text-conditioned aesthetic cropping with a small cropping dataset, while inheriting the open-vocabulary ability acquired from millions of text-image pairs. We validate our model through extensive experiments on existing datasets as well as a new cropping test set we compiled that is characterized by content ambiguity.	['Imari Sato', 'Yoichi Sato', 'Stephen Lin', 'Han Hu', 'Ji Li', 'Yinqiang Zheng', 'Yuhui Yuan', 'Zhirong Wu', 'Mingxi Cheng', 'Zhihang Zhong']	2022-11-21	null	null	null	null	['image-cropping']	['computer-vision']	[ 7.65494585e-01 -1.09723739e-01 -6.98734000e-02 -3.07202220e-01 -8.45902920e-01 -6.58183277e-01 5.50851226e-01 -2.59716541e-01 -2.00595677e-01 1.63540885e-01 2.71357954e-01 -2.50573277e-01 5.49778223e-01 -7.15412736e-01 -1.10972285e+00 -3.28340471e-01 6.85277522e-01 1.29772112e-01 9.55263823e-02 -3.97568405e-01 1.95923775e-01 -1.79285601e-01 -1.78540695e+00 6.15827918e-01 1.02439940e+00 8.85213435e-01 9.84757483e-01 4.29427177e-01 -1.04415558e-01 6.18243635e-01 -2.87002802e-01 -6.02522433e-01 6.35502398e-01 -3.97667825e-01 -3.49968940e-01 6.03185117e-01 8.76515806e-01 -5.03867149e-01 -1.93606183e-01 1.09334517e+00 2.06791729e-01 -3.70903671e-01 4.47316319e-01 -1.33635104e+00 -1.17541265e+00 6.06776416e-01 -6.27371609e-01 -5.22089481e-01 2.68789411e-01 3.75920027e-01 1.22884691e+00 -1.23890185e+00 9.07545984e-01 9.16357279e-01 5.27013183e-01 4.91686881e-01 -1.15208972e+00 -7.93401718e-01 2.41598234e-01 -2.95631103e-02 -1.18291652e+00 -4.78554755e-01 6.66619301e-01 -5.07105827e-01 6.39879882e-01 -1.64550301e-02 8.22501779e-01 1.44401789e+00 -1.40083805e-01 1.06557655e+00 1.01875722e+00 -6.52620971e-01 -2.87881475e-02 3.67982775e-01 -2.55962849e-01 7.40712821e-01 1.88749954e-01 2.46234126e-02 -6.97349608e-01 2.58414179e-01 7.19670713e-01 -6.37292042e-02 -2.36267090e-01 -8.43064785e-01 -1.30881619e+00 6.43707275e-01 3.07835370e-01 1.02720391e-02 -4.01432902e-01 6.89564571e-02 3.08916196e-02 3.35336417e-01 3.45346153e-01 5.01170516e-01 -3.65286350e-01 1.39638364e-01 -1.29914129e+00 3.13924283e-01 6.56594694e-01 1.50276935e+00 6.38645947e-01 -1.28749102e-01 -9.47514325e-02 5.68183661e-01 1.37054354e-01 9.21348095e-01 9.01037827e-02 -8.63955081e-01 7.32394516e-01 5.65993667e-01 3.06081265e-01 -8.18036437e-01 -1.18468748e-03 -3.07890147e-01 -5.57974279e-01 3.02078605e-01 4.88683939e-01 -1.33526209e-03 -1.10720980e+00 1.78321671e+00 -5.60229868e-02 -2.33790740e-01 8.12348910e-03 9.03096795e-01 4.47821915e-01 5.08256018e-01 4.95771319e-02 6.94951639e-02 1.48943794e+00 -1.04527020e+00 -6.73215628e-01 -6.18305683e-01 5.09373188e-01 -1.01161504e+00 1.62797248e+00 6.04105294e-01 -9.10972536e-01 -4.88128603e-01 -1.08251953e+00 -2.95932621e-01 -4.08916324e-01 3.85403246e-01 4.49640065e-01 4.84677583e-01 -9.88052070e-01 1.07873023e-01 -3.36091012e-01 -6.91165507e-01 5.20993829e-01 -2.19000190e-01 -4.04329717e-01 -4.78430212e-01 -1.02242947e+00 8.87817383e-01 3.83804739e-01 -1.83268249e-01 -9.18243170e-01 -7.35455930e-01 -9.40477431e-01 -5.61944731e-02 5.94292641e-01 -6.36412978e-01 1.26400983e+00 -1.34192204e+00 -1.04427910e+00 9.83846247e-01 -1.75366864e-01 -4.22398835e-01 7.69263983e-01 -3.69103402e-01 -2.53666759e-01 6.51237220e-02 3.06626290e-01 1.22569120e+00 1.42131317e+00 -1.35728431e+00 -7.04664588e-01 -2.21050277e-01 2.29410961e-01 5.29972792e-01 -5.78742743e-01 -1.79613531e-01 -8.24234307e-01 -7.45880127e-01 -2.03229070e-01 -9.88754153e-01 -7.89288431e-02 3.76558900e-01 -4.04930413e-01 3.44055593e-01 9.24717605e-01 -8.78398716e-01 1.03363299e+00 -2.43238997e+00 7.27723613e-02 -2.44955979e-02 2.58844136e-03 7.20813870e-02 -3.96615058e-01 6.56570017e-01 1.31125286e-01 1.00506559e-01 -4.57485080e-01 -3.54315937e-01 -1.06811812e-02 8.21500644e-02 -6.02737486e-01 -8.48746300e-03 6.12390876e-01 1.14679134e+00 -8.89258146e-01 -6.21935546e-01 3.71431082e-01 2.70758063e-01 -8.03872347e-01 3.10443342e-01 -7.98555434e-01 2.16671512e-01 -2.55227268e-01 9.07636583e-01 6.56200230e-01 -4.19853419e-01 9.25098509e-02 -5.42870760e-01 -1.34066924e-01 -2.20012516e-01 -8.63048315e-01 2.34243631e+00 -5.82590342e-01 7.97622979e-01 -9.20643136e-02 -6.19549990e-01 7.71267474e-01 1.41764492e-01 2.19531342e-01 -9.83070016e-01 -5.56383422e-03 7.31039792e-02 -4.16748643e-01 -7.52334833e-01 9.89507675e-01 1.65663153e-01 -2.95735180e-01 5.91664493e-01 -6.23008236e-02 -5.37300169e-01 3.16041321e-01 3.61192793e-01 9.44915056e-01 6.04715168e-01 9.20733809e-02 3.91399935e-02 4.57077399e-02 4.56255794e-01 1.07429169e-01 8.68154764e-01 -1.19872298e-02 1.05399203e+00 2.03450680e-01 -1.81914106e-01 -1.44572353e+00 -9.12311137e-01 -8.59834924e-02 1.39217567e+00 3.36427599e-01 -3.86907130e-01 -1.08377206e+00 -5.13571560e-01 -2.13963449e-01 9.62401628e-01 -6.53708100e-01 7.96101019e-02 -3.11389953e-01 -5.38762748e-01 3.39265227e-01 4.37239379e-01 5.49842238e-01 -1.13351059e+00 -6.71047866e-01 5.95669933e-02 -7.41960347e-01 -1.51860356e+00 -8.23187292e-01 -7.73526281e-02 -2.65414327e-01 -1.12499130e+00 -6.75898612e-01 -1.05692697e+00 7.81669855e-01 7.38483191e-01 1.24948120e+00 1.94108170e-02 -3.95221472e-01 4.42369759e-01 -5.62654734e-01 -6.09942257e-01 -5.91199636e-01 1.08925633e-01 -3.13898951e-01 -6.31508743e-03 4.98163968e-01 -1.66840881e-01 -5.18621385e-01 2.92943895e-01 -1.22158182e+00 8.19254518e-01 8.88194859e-01 8.16445768e-01 4.04199988e-01 -8.11925679e-02 3.47918749e-01 -7.80107558e-01 3.93889666e-01 -3.08620125e-01 -6.64704502e-01 5.34874737e-01 -5.64525127e-01 -5.82635030e-02 4.00168777e-01 -6.15248263e-01 -1.22661436e+00 5.04443288e-01 2.79853702e-01 -4.50667262e-01 1.38189662e-02 3.73099864e-01 -1.46781549e-01 1.90530613e-01 6.30600691e-01 3.82608145e-01 -1.63677353e-02 -2.71641880e-01 8.67074192e-01 8.51640940e-01 7.60534406e-01 -3.90724719e-01 9.63204741e-01 4.82872397e-01 -4.93127167e-01 -7.72254646e-01 -9.99332249e-01 -1.09815598e-01 -6.20591640e-01 -2.36519337e-01 8.79759550e-01 -1.34903693e+00 -9.30680409e-02 6.67681992e-01 -1.10700524e+00 -3.84136081e-01 -2.09208146e-01 2.93611940e-02 -5.19921541e-01 3.14849257e-01 -2.94343978e-01 -5.88038385e-01 -4.38472927e-01 -1.34045672e+00 1.30107069e+00 -4.30044532e-02 -1.07273348e-01 -3.38966936e-01 -4.95615840e-01 6.38662398e-01 5.01097262e-01 -1.24610607e-02 8.80324006e-01 -1.27923012e-01 -9.54486072e-01 -2.54894525e-01 -7.27564454e-01 3.16886187e-01 -7.06307292e-02 -2.00785082e-02 -9.82412934e-01 -1.67565212e-01 -3.42734635e-01 -5.50973713e-01 6.97862208e-01 9.94178578e-02 9.79752004e-01 1.57354191e-01 -1.39803708e-01 5.35175920e-01 1.39645815e+00 -2.12938398e-01 5.97965539e-01 3.05949271e-01 8.00763726e-01 6.85808480e-01 9.63648736e-01 3.39843452e-01 5.70945501e-01 4.86089557e-01 7.58805454e-01 -1.65407911e-01 -3.09650779e-01 -8.07602346e-01 4.18202192e-01 4.21582252e-01 3.39758843e-01 -4.50541764e-01 -7.44444788e-01 6.87297404e-01 -1.66607642e+00 -8.22345614e-01 9.80810151e-02 2.02617645e+00 9.63582337e-01 6.17525987e-02 -2.19236135e-01 -1.88327640e-01 7.11981237e-01 1.98043928e-01 -6.83730721e-01 3.94529104e-02 -3.07058603e-01 -6.49033859e-03 7.22020924e-01 1.62800953e-01 -1.12953699e+00 1.29564106e+00 6.22443724e+00 6.33897662e-01 -1.04494441e+00 -3.31708305e-02 2.72640258e-01 -4.66522947e-02 -3.74983251e-01 7.98883140e-02 -6.80734098e-01 3.91080558e-01 4.83628243e-01 -5.18883206e-02 7.07992852e-01 6.98445976e-01 2.00185120e-01 -1.63016438e-01 -1.13519859e+00 1.02381170e+00 4.30864930e-01 -1.08957505e+00 9.49071795e-02 5.21890782e-02 5.63044548e-01 1.30054563e-01 2.22774327e-01 2.12788448e-01 4.05212343e-01 -9.05168712e-01 1.18619311e+00 2.76206106e-01 1.14681578e+00 -1.18924625e-01 1.03025600e-01 3.20360124e-01 -1.00332427e+00 -1.10360704e-01 -1.66564852e-01 1.05999462e-01 1.80138707e-01 3.91688406e-01 -7.83661604e-01 2.43207306e-01 7.19644547e-01 9.09921706e-01 -6.30832195e-01 6.31566405e-01 -2.68081486e-01 4.05721992e-01 -2.52655178e-01 1.86357424e-01 1.39447138e-01 -2.08387554e-01 3.69873911e-01 1.03707814e+00 5.04124165e-01 -3.68959874e-01 2.01067463e-01 1.01054156e+00 -2.54903287e-01 2.22357735e-01 -7.56838918e-01 -3.05560380e-01 5.61662257e-01 1.30215991e+00 -3.95474583e-01 -2.28853568e-01 -7.76355267e-01 1.27607572e+00 2.76809752e-01 2.25558177e-01 -9.03580844e-01 -1.10442191e-01 4.43157583e-01 9.12649184e-02 4.25133914e-01 -1.42260566e-01 -1.50914565e-01 -1.39771402e+00 3.74355853e-01 -1.16644025e+00 -1.19229108e-01 -1.39883709e+00 -1.13531733e+00 3.75636011e-01 -2.08474696e-01 -1.45639157e+00 -6.26938269e-02 -5.49887240e-01 -2.38528103e-01 6.56525373e-01 -1.50693321e+00 -1.82631052e+00 -6.92004144e-01 4.38958704e-01 8.98273051e-01 7.66513962e-03 7.24090099e-01 3.33511770e-01 -4.07656878e-01 4.43776220e-01 -2.74319232e-01 2.92213559e-01 1.05984807e+00 -1.08041906e+00 7.15939522e-01 1.12261081e+00 3.76252800e-01 3.14800858e-01 9.21577513e-01 -6.43240690e-01 -1.68485808e+00 -1.30309403e+00 6.51674986e-01 -5.28801680e-01 7.61895895e-01 -7.67001450e-01 -8.22653234e-01 7.64924943e-01 4.15810317e-01 -2.18333200e-01 3.87631565e-01 -2.15579271e-01 -7.07724869e-01 1.71654820e-01 -8.72413576e-01 8.79350483e-01 1.31254148e+00 -5.11449635e-01 -5.54974437e-01 4.19738352e-01 9.44475949e-01 -5.97085536e-01 -4.86661166e-01 1.45453230e-01 8.32368433e-01 -7.55955517e-01 9.95272279e-01 -2.75362670e-01 8.17292988e-01 -2.09604964e-01 -3.50874096e-01 -1.20593572e+00 -1.03814535e-01 -3.60889941e-01 2.07568407e-01 1.28466713e+00 5.28275847e-01 -2.26378113e-01 7.13844955e-01 6.90276265e-01 1.40402630e-01 -2.23813668e-01 -2.17593312e-01 -4.23934996e-01 -1.38312206e-01 -7.15195715e-01 6.44339740e-01 9.06885684e-01 -9.90921482e-02 2.60696262e-01 -8.39167953e-01 1.10629521e-01 6.48045063e-01 3.03534478e-01 1.04299402e+00 -8.06677818e-01 -2.58904010e-01 -1.26622692e-01 -3.71834077e-02 -1.04223990e+00 -3.00543290e-02 -7.51460493e-01 2.72044986e-01 -1.41080284e+00 2.86427498e-01 -4.63068992e-01 -3.90712777e-03 6.87061608e-01 -1.24895856e-01 4.26084131e-01 4.41184670e-01 2.97784299e-01 -4.60552037e-01 3.34559172e-01 1.33063567e+00 -2.37380147e-01 -4.82542217e-02 -5.43406487e-01 -9.85502779e-01 6.16442621e-01 7.54327953e-01 -2.69071609e-01 -5.57141900e-01 -8.35735559e-01 4.43981707e-01 -1.20215140e-01 4.83701259e-01 -9.25056934e-01 1.47340745e-01 -2.29926527e-01 2.78505057e-01 -7.09359527e-01 4.35811937e-01 -1.15131700e+00 4.12238277e-02 8.20984468e-02 -5.82104743e-01 -9.47732851e-02 -2.05458459e-02 6.62897110e-01 -1.91243384e-02 -1.24269180e-01 5.07618666e-01 -1.14103355e-01 -1.13218856e+00 2.37011850e-01 -1.05343774e-01 1.89691752e-01 1.03719139e+00 1.85565762e-02 -4.38041568e-01 -4.18140948e-01 -2.67789274e-01 3.08702260e-01 1.02252865e+00 9.84659374e-01 5.07746160e-01 -1.05320787e+00 -7.05520034e-01 4.47117180e-01 8.39451730e-01 -3.62768546e-02 4.18666266e-02 5.92070341e-01 -4.95281100e-01 1.41653746e-01 -2.53994197e-01 -6.58944547e-01 -1.23294151e+00 7.77682602e-01 -4.20948630e-03 1.18416257e-01 -7.96315014e-01 4.88640010e-01 4.61166859e-01 -2.79816270e-01 1.61475390e-01 -2.61517316e-01 1.47135779e-01 8.28309581e-02 5.58331251e-01 -3.61236900e-01 -1.15432315e-01 -6.14053011e-01 9.26694423e-02 4.09241945e-01 -2.22279981e-01 -2.38285691e-01 1.02607918e+00 -4.55089152e-01 2.10488394e-01 1.36408687e-01 8.96736503e-01 -2.15455100e-01 -1.38947475e+00 -6.68446600e-01 -2.18521744e-01 -5.62532961e-01 6.01832345e-02 -9.80161130e-01 -9.46686149e-01 8.52531672e-01 4.57295150e-01 -6.15757331e-02 1.16396129e+00 -1.98089704e-01 8.18635345e-01 3.95963162e-01 5.58811367e-01 -1.19872701e+00 9.59632546e-02 2.67182052e-01 9.29567873e-01 -1.71539295e+00 -3.00153494e-01 -5.29350340e-01 -9.88562942e-01 9.30500329e-01 5.93949437e-01 9.92274061e-02 2.97604501e-01 4.26309377e-01 4.60961699e-01 1.46141658e-02 -7.41913974e-01 -4.11870152e-01 5.41408025e-02 6.93273365e-01 1.78795755e-01 8.41164812e-02 1.89645380e-01 2.69929230e-01 -2.99519807e-01 4.37868208e-01 5.33241034e-01 9.54959691e-01 -4.27348942e-01 -1.08507359e+00 -2.52211004e-01 4.06191647e-01 -8.66181552e-02 -5.18225193e-01 -3.46894026e-01 7.16823816e-01 7.74793327e-02 8.71667325e-01 -7.41428975e-03 -3.53252739e-01 2.33042508e-01 1.62460297e-01 4.87896383e-01 -5.81490159e-01 -1.70915499e-01 -4.24659885e-02 -1.13978446e-01 -5.33006251e-01 -3.49245101e-01 -7.17863560e-01 -7.73382723e-01 3.69174010e-03 -3.52450788e-01 -4.15557712e-01 8.80514622e-01 9.20229495e-01 5.21359742e-01 2.55161881e-01 4.20990050e-01 -8.65430236e-01 -4.04764831e-01 -7.99395263e-01 -4.63752955e-01 7.02583075e-01 4.49396148e-02 -3.52767587e-01 -2.46065706e-02 5.98584533e-01]	[11.244884490966797, -0.07275836914777756]
8194e975-e1c4-404b-a649-3c9f1d94c93e	mosi-multimodal-corpus-of-sentiment-intensity	1606.06259	null	http://arxiv.org/abs/1606.06259v2	http://arxiv.org/pdf/1606.06259v2.pdf	MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos	People are sharing their opinions, stories and reviews through online video sharing websites every day. Studying sentiment and subjectivity in these opinion videos is experiencing a growing attention from academia and industry. While sentiment analysis has been successful for text, it is an understudied research question for videos and multimedia content. The biggest setbacks for studies in this direction are lack of a proper dataset, methodology, baselines and statistical analysis of how information from different modality sources relate to each other. This paper introduces to the scientific community the first opinion-level annotated corpus of sentiment and subjectivity analysis in online videos called Multimodal Opinion-level Sentiment Intensity dataset (MOSI). The dataset is rigorously annotated with labels for subjectivity, sentiment intensity, per-frame and per-opinion annotated visual features, and per-milliseconds annotated audio features. Furthermore, we present baselines for future studies in this direction as well as a new multimodal fusion approach that jointly models spoken words and visual gestures.	['Louis-Philippe Morency', 'Eli Pincus', 'Rowan Zellers', 'Amir Zadeh']	2016-06-20	null	null	null	null	['subjectivity-analysis']	['natural-language-processing']	[ 1.69557482e-01 -3.28185171e-01 -4.33746934e-01 -7.41636395e-01 -1.00191331e+00 -8.64790559e-01 6.09420002e-01 1.45983025e-01 -5.36514342e-01 3.99768263e-01 8.08128178e-01 2.64017552e-01 3.26375037e-01 2.96711270e-02 -4.52313393e-01 -6.93236530e-01 1.15522794e-01 -3.12163174e-01 2.79310904e-02 -2.21755430e-01 5.46329618e-01 -1.03716739e-01 -1.87413955e+00 7.98430622e-01 -1.23865912e-02 1.21384001e+00 -2.59968966e-01 9.50603604e-01 -1.32215291e-01 1.30942750e+00 -7.25377083e-01 -6.03232741e-01 -2.01885432e-01 -5.73095620e-01 -7.21582353e-01 2.95121759e-01 8.86395097e-01 -1.72034219e-01 3.96564323e-03 9.46875155e-01 8.58938515e-01 7.73640350e-02 5.94649255e-01 -1.70363712e+00 -4.04191315e-01 3.88463289e-01 -7.41304398e-01 2.47954264e-01 9.31414008e-01 -1.11025825e-01 8.76124442e-01 -9.65844989e-01 1.04671741e+00 1.37449515e+00 2.93797493e-01 3.64031315e-01 -4.69319582e-01 -6.56121254e-01 2.20368490e-01 2.49912634e-01 -9.52233076e-01 -6.07434928e-01 5.97989678e-01 -5.78174770e-01 8.38953495e-01 2.34395579e-01 6.91273510e-01 1.45082724e+00 1.25963530e-02 1.02204549e+00 9.59677339e-01 -5.48503220e-01 1.64709747e-01 6.15872383e-01 3.59104201e-02 3.97556245e-01 -4.28335428e-01 -4.10176426e-01 -1.40350878e+00 2.40955293e-01 2.31028199e-01 -7.43788807e-03 -2.40060836e-01 -2.01530695e-01 -1.45012379e+00 8.21109891e-01 -9.75395963e-02 3.95287693e-01 -2.34193072e-01 2.96727836e-01 8.23093057e-01 5.68262041e-01 7.49958515e-01 -1.23217598e-01 -5.67735314e-01 -8.46617877e-01 -1.05016148e+00 1.90070793e-02 7.73738444e-01 8.94766629e-01 4.10665512e-01 -3.80084664e-02 1.27369136e-01 7.72553742e-01 5.95965326e-01 8.93375516e-01 3.46893698e-01 -1.24818134e+00 4.03654158e-01 5.03199518e-01 6.77191243e-02 -1.30187786e+00 -6.23284519e-01 3.66565228e-01 -1.37381986e-01 1.50733024e-01 4.36241359e-01 -6.17472827e-01 -4.14269239e-01 1.56609821e+00 2.86508769e-01 -3.43851954e-01 5.61174229e-02 1.11516392e+00 1.28067803e+00 7.57278860e-01 -1.45456463e-01 -3.75656486e-01 1.70000303e+00 -8.67004395e-01 -1.04748273e+00 6.20569363e-02 5.38340747e-01 -1.19953120e+00 1.01175523e+00 7.58487940e-01 -1.29123366e+00 -4.45652276e-01 -7.57989585e-01 -7.27398023e-02 -4.58867401e-01 -6.87176958e-02 4.80480164e-01 1.00688541e+00 -1.07228649e+00 -1.35739937e-01 -6.59912765e-01 -8.12783659e-01 3.27145994e-01 2.50677139e-01 -5.77297866e-01 -1.57044306e-02 -8.45756650e-01 6.61604524e-01 -3.15883338e-01 -8.97573456e-02 -5.66452801e-01 -4.71799374e-01 -9.71047759e-01 -5.87125719e-01 3.77933353e-01 -4.56531122e-02 1.43937266e+00 -1.84588575e+00 -1.62601972e+00 9.75943983e-01 -5.25367737e-01 -5.03837410e-03 1.33411575e-03 -3.65199149e-01 -7.35389769e-01 6.94895089e-01 4.44487073e-02 8.92352998e-01 1.00180995e+00 -1.06440985e+00 -9.06999171e-01 -4.46742535e-01 3.79962385e-01 4.16615248e-01 -6.98637247e-01 7.44197130e-01 -7.06368804e-01 -5.99585116e-01 -1.72125563e-01 -1.03735387e+00 3.03282708e-01 -6.08909428e-02 -1.53587330e-02 -5.46614900e-02 1.07218575e+00 -5.15556991e-01 1.06728911e+00 -2.29108453e+00 3.17290425e-01 -7.12265521e-02 1.66557487e-02 -3.25337827e-01 -1.48573563e-01 4.70264971e-01 1.96246058e-02 2.12123454e-01 4.67175364e-01 -2.55664796e-01 3.81300459e-03 -2.09754750e-01 -6.89411759e-02 7.77164698e-01 -8.44094604e-02 6.53632402e-01 -8.11704040e-01 -7.71658421e-01 3.02937597e-01 7.91915357e-01 -7.61693478e-01 -7.11735487e-02 7.52435476e-02 6.55869126e-01 -3.48768502e-01 1.13963962e+00 4.01983380e-01 -1.67832434e-01 3.19745168e-02 -6.88915312e-01 -4.42585349e-01 -2.40604818e-01 -1.18984413e+00 1.75948679e+00 -5.64392805e-01 1.38615441e+00 3.82191300e-01 -8.91678393e-01 4.85611588e-01 7.14791000e-01 7.18336284e-01 -7.23044217e-01 5.86447835e-01 1.24583066e-01 -3.83954138e-01 -1.00695491e+00 8.44666779e-01 -1.67896375e-01 -3.94044757e-01 3.88631433e-01 3.88081759e-01 -3.01336378e-01 4.53111202e-01 3.72069478e-01 5.70711017e-01 1.22679882e-01 -3.63609493e-02 9.57828909e-02 6.30672514e-01 9.95134041e-02 1.13634281e-02 2.62672871e-01 -4.49087292e-01 8.42074811e-01 7.25455165e-01 -1.53070748e-01 -6.86207592e-01 -4.94457066e-01 -1.07585877e-01 1.69522333e+00 2.54295975e-01 -4.62056637e-01 -7.41845369e-01 -3.58873814e-01 -4.62676376e-01 1.77156985e-01 -4.54482198e-01 4.40747619e-01 -1.04014724e-01 -4.48650092e-01 2.56782949e-01 4.87415344e-01 1.81303039e-01 -1.18102980e+00 -6.85096085e-01 -2.44546309e-01 -6.29791915e-01 -1.40594232e+00 -3.93762290e-01 -1.43368110e-01 -4.57146674e-01 -1.15100348e+00 -1.02940726e+00 -7.82584786e-01 4.23524112e-01 4.09739733e-01 1.25962353e+00 -3.01817894e-01 2.55481713e-02 1.30829418e+00 -9.26433921e-01 -7.20979214e-01 -3.79824080e-02 -1.73645124e-01 1.44903257e-01 2.18964830e-01 6.63028419e-01 9.46962237e-02 -7.26975799e-01 6.89386427e-01 -9.53159928e-01 -4.41695780e-01 1.15593545e-01 3.62124622e-01 3.23033571e-01 -1.94471210e-01 4.38908100e-01 -4.12021488e-01 3.92291993e-01 -6.28927052e-01 -2.57596344e-01 -1.85330987e-01 1.52709752e-01 -7.52755642e-01 2.63486356e-02 -3.01348656e-01 -1.09164429e+00 -4.73620696e-03 8.57069567e-02 -1.47486538e-01 -2.21105173e-01 5.79310775e-01 4.83078882e-02 -6.39038626e-03 5.16112983e-01 -4.30656552e-01 1.50137231e-01 1.04499601e-01 4.69518781e-01 9.50993299e-01 3.76513451e-01 -1.41962871e-01 1.14089258e-01 9.67115343e-01 -4.90278274e-01 -1.42359662e+00 -1.01523864e+00 -9.36506689e-01 -5.11534572e-01 -9.35307562e-01 1.27338564e+00 -1.30389059e+00 -1.06235230e+00 5.62816858e-01 -9.39663410e-01 5.94884418e-02 -4.63858619e-02 7.56502688e-01 -6.40432656e-01 3.46344411e-01 -5.23785651e-01 -1.02828789e+00 -2.61642020e-02 -1.36018515e+00 1.34132361e+00 2.69301832e-01 -5.79736233e-01 -9.62982714e-01 3.58342379e-02 1.02669358e+00 3.62776339e-01 2.19788387e-01 -5.74387275e-02 -2.77440310e-01 -2.03961909e-01 -4.84046459e-01 -1.85485154e-01 5.65302551e-01 -2.55537778e-01 3.41367126e-01 -1.11217713e+00 -1.28845170e-01 -5.56505136e-02 -1.02183950e+00 6.58042550e-01 8.43128085e-01 7.37072766e-01 -1.58884019e-01 -1.92191619e-02 2.68012118e-02 1.11593795e+00 1.79790705e-01 5.32193303e-01 3.38659853e-01 5.18888891e-01 1.00352037e+00 9.08438504e-01 6.23923600e-01 4.98913735e-01 6.34172320e-01 5.27434886e-01 -4.82502654e-02 1.49246797e-01 4.18500453e-01 1.00994420e+00 9.92689550e-01 -3.76373559e-01 -6.48658156e-01 -6.17316842e-01 7.94765294e-01 -1.55520177e+00 -1.29564941e+00 -2.69823164e-01 1.80017471e+00 4.44623500e-01 -2.01254532e-01 4.87629086e-01 3.88558060e-01 5.80787838e-01 2.73819000e-01 -2.17964783e-01 -6.00874186e-01 -4.19969112e-01 -2.18930781e-01 2.95459479e-01 3.55885118e-01 -1.24893594e+00 5.82107604e-01 6.26103640e+00 7.07861960e-01 -1.30845535e+00 1.91980764e-01 5.25368392e-01 -7.21710205e-01 -5.86896166e-02 -2.39187941e-01 -7.77134836e-01 2.50124782e-01 1.09755564e+00 5.24223387e-01 2.37126470e-01 7.33172357e-01 5.35834372e-01 -6.23139501e-01 -8.43396306e-01 1.08674085e+00 7.37129271e-01 -1.13164139e+00 -5.26796460e-01 -1.10214785e-01 9.63384986e-01 1.58496469e-01 3.42759311e-01 2.64867730e-02 -4.46120977e-01 -7.31947362e-01 1.11413753e+00 5.19011259e-01 8.31249475e-01 -6.49616718e-01 1.06433988e+00 -3.91825974e-01 -8.62451732e-01 6.63560582e-03 1.73419118e-01 -6.38014898e-02 5.90660810e-01 3.19440156e-01 -7.42048025e-02 1.82294752e-02 1.25013971e+00 1.19087553e+00 -4.75916862e-01 4.46416795e-01 3.99761721e-02 7.35971391e-01 -1.95992410e-01 -3.96643937e-01 1.65811986e-01 2.11485308e-02 3.67014170e-01 1.52680445e+00 2.34356239e-01 -9.73163024e-02 -7.24476129e-02 -9.77502689e-02 1.27354801e-01 2.97752827e-01 -5.74362278e-01 -6.05611324e-01 -1.48378269e-04 1.56787443e+00 -1.02531326e+00 -2.79924691e-01 -1.03599465e+00 9.42267954e-01 -5.91709495e-01 4.23127323e-01 -7.90677249e-01 -2.39576250e-01 5.86819947e-01 -1.58683479e-01 3.01124930e-01 -2.13644236e-01 2.90604904e-02 -1.24370790e+00 -4.95389998e-02 -1.17982721e+00 2.18610868e-01 -1.04277003e+00 -1.07373190e+00 3.41237068e-01 -5.87622337e-02 -1.48982263e+00 -2.94785827e-01 -7.91096449e-01 -1.72643185e-01 1.28012568e-01 -1.38201988e+00 -9.91762161e-01 -4.73781526e-01 8.61744940e-01 7.87661195e-01 -2.44346663e-01 5.75997114e-01 5.89556038e-01 -3.54006499e-01 3.65631342e-01 -8.76811966e-02 -1.26326621e-01 1.11750805e+00 -8.89562964e-01 -6.40252531e-01 2.36146450e-01 8.70951787e-02 3.25298101e-01 9.60170984e-01 -9.54916850e-02 -1.82501483e+00 -4.01164055e-01 8.14195991e-01 -8.72022271e-01 9.80016053e-01 -2.11018085e-01 -1.76294535e-01 4.50899959e-01 7.46024430e-01 -2.49072462e-01 1.10605466e+00 6.82318211e-02 -7.44499415e-02 1.01825267e-01 -9.15497124e-01 4.25500095e-01 5.68577647e-01 -7.41353691e-01 -1.80623770e-01 4.99903977e-01 4.95052904e-01 -3.12539399e-01 -9.84741211e-01 8.17591250e-02 1.00836599e+00 -1.17868543e+00 8.00195098e-01 -1.21880464e-01 9.61029768e-01 -2.70578831e-01 -5.69058359e-01 -9.49893951e-01 6.76607251e-01 -4.72738147e-01 2.16352075e-01 1.45228601e+00 4.52130914e-01 -1.90839767e-02 6.71684682e-01 4.88011926e-01 6.76389411e-02 -2.32439011e-01 -5.96598864e-01 -1.11874782e-01 -2.97366738e-01 -1.01357198e+00 -2.16327295e-01 8.59512866e-01 5.80240905e-01 6.27457738e-01 -6.35821640e-01 -2.01753974e-01 7.52373934e-02 -1.20967515e-01 1.02250087e+00 -7.71535635e-01 2.23009288e-01 -3.69818121e-01 -7.31531382e-01 -5.96820474e-01 6.98404983e-02 -4.31725383e-01 -1.08669572e-01 -1.36170149e+00 2.44110286e-01 4.87362176e-01 1.82169285e-02 1.73803717e-01 4.18219924e-01 9.39352036e-01 2.74616778e-01 -8.76788720e-02 -1.24829006e+00 2.05828696e-01 1.05480790e+00 -4.76140939e-02 -2.08362445e-01 -3.47458750e-01 -4.88515884e-01 1.07033002e+00 5.00298500e-01 -1.80556864e-01 -3.65692675e-01 -2.40875721e-01 1.00849724e+00 2.41407573e-01 2.23973319e-01 -7.99278557e-01 1.69748038e-01 7.30062947e-02 1.71875045e-01 -1.02942336e+00 6.18914723e-01 -9.08725977e-01 -4.38386798e-01 -1.28676862e-01 -3.84900212e-01 1.67939752e-01 2.43684590e-01 5.18843830e-01 -7.97807813e-01 -5.11669070e-02 4.69211280e-01 5.24553545e-02 -9.73641396e-01 -1.75534755e-01 -9.76069510e-01 2.10714832e-01 8.86398375e-01 -3.55684251e-01 -2.26114556e-01 -1.08871531e+00 -8.01995993e-01 2.03500226e-01 4.12737489e-01 7.81133175e-01 4.56287205e-01 -1.02315438e+00 -5.53777099e-01 -1.61323652e-01 3.66875291e-01 -6.42790675e-01 5.26144624e-01 1.18720520e+00 -2.48358101e-01 3.49624515e-01 -1.59132212e-01 -9.13759291e-01 -1.49689519e+00 3.59356523e-01 -1.70867413e-01 4.85320061e-01 2.88208090e-02 8.93244982e-01 -6.67863190e-02 -3.40996534e-01 4.00750667e-01 -1.06410630e-01 -6.54862702e-01 1.06102026e+00 8.32051218e-01 5.88021219e-01 -3.27610597e-03 -1.33240879e+00 -5.38760543e-01 9.22736049e-01 2.79154778e-01 -5.67884922e-01 1.17544413e+00 -8.32949221e-01 -5.98556921e-02 9.60578382e-01 1.60768616e+00 2.41585404e-01 -7.75928855e-01 2.62586594e-01 -2.61074901e-01 -3.36157084e-01 2.44265780e-01 -6.63957775e-01 -1.27938759e+00 8.89127672e-01 7.73116052e-01 3.88544410e-01 1.14735806e+00 1.63947895e-01 4.70566928e-01 1.65506393e-01 3.63030769e-02 -1.54005861e+00 6.60658717e-01 4.66269463e-01 9.07168567e-01 -1.73958218e+00 4.04135995e-02 -1.64154753e-01 -1.24609315e+00 1.00019526e+00 1.98707268e-01 1.41610265e-01 8.79603624e-01 2.68767208e-01 7.10256577e-01 -5.04601657e-01 -5.72530329e-01 -1.38993815e-01 3.77605259e-01 4.89057928e-01 1.07317400e+00 -3.05506676e-01 -3.51880282e-01 4.14750010e-01 -1.93245500e-01 1.43905610e-01 7.22260356e-01 1.04856265e+00 -2.57355571e-01 -6.46494925e-01 -5.71669340e-01 1.33569106e-01 -1.13775253e+00 3.09661892e-03 -3.13409388e-01 7.03937531e-01 -7.92604610e-02 1.72790468e+00 1.52647212e-01 -2.83876240e-01 2.86264330e-01 -1.13477267e-01 3.22549939e-01 -3.62214386e-01 -7.05766499e-01 4.79663551e-01 2.61527508e-01 -8.69262040e-01 -1.60213971e+00 -9.30746794e-01 -1.07824326e+00 -3.99230719e-02 -3.75958264e-01 -1.31410077e-01 1.32721257e+00 8.30596983e-01 1.65751219e-01 4.76413131e-01 5.38536370e-01 -1.36618936e+00 4.44111764e-01 -8.31468761e-01 -6.05652690e-01 4.04583901e-01 4.78010118e-01 -4.84418035e-01 -7.12187290e-01 5.61250329e-01]	[13.064153671264648, 5.238861083984375]
6be2dfdb-c698-4b23-ad67-9423fa0cc59b	selective-pre-training-for-private-fine	2305.13865	null	https://arxiv.org/abs/2305.13865v1	https://arxiv.org/pdf/2305.13865v1.pdf	Selective Pre-training for Private Fine-tuning	Suppose we want to train text prediction models in email clients or word processors. The models must preserve the privacy of user data and adhere to a specific fixed size to meet memory and inference time requirements. We introduce a generic framework to solve this problem. Specifically, we are given a public dataset $D_\text{pub}$ and a private dataset $D_\text{priv}$ corresponding to a downstream task $T$. How should we pre-train a fixed-size model $M$ on $D_\text{pub}$ and fine-tune it on $D_\text{priv}$ such that performance of $M$ with respect to $T$ is maximized and $M$ satisfies differential privacy with respect to $D_\text{priv}$? We show that pre-training on a {\em subset} of dataset $D_\text{pub}$ that brings the public distribution closer to the private distribution is a crucial ingredient to maximize the transfer learning abilities of $M$ after pre-training, especially in the regimes where model sizes are relatively small. Besides performance improvements, our framework also shows that with careful pre-training and private fine-tuning, {\em smaller models} can match the performance of much larger models, highlighting the promise of differentially private training as a tool for model compression and efficiency.	['Huishuai Zhang', 'Jian Yin', 'Tomasz Lukasz Religa', 'Saurabh Naik', 'Zinan Lin', 'Janardhan Kulkarni', 'Sivakanth Gopi', 'Da Yu']	2023-05-23	null	null	null	null	['model-compression']	['methodology']	[ 3.05223405e-01 3.98440987e-01 -3.15583855e-01 -6.66463375e-01 -1.36139679e+00 -6.66736007e-01 1.01148985e-01 2.55981740e-03 -6.02400362e-01 7.15266287e-01 -3.39932084e-01 -6.45366609e-01 -2.92380482e-01 -1.07816303e+00 -1.14945257e+00 -8.12363148e-01 -6.63667172e-02 7.95766175e-01 -2.70392627e-01 1.85289949e-01 -5.72580360e-02 4.29705858e-01 -1.25570369e+00 4.06127483e-01 3.83317143e-01 1.26836562e+00 6.35834336e-02 7.47604668e-01 6.35504574e-02 3.77684772e-01 -4.00014222e-01 -1.09872949e+00 7.35450029e-01 -1.96081638e-01 -9.93974149e-01 -2.78030604e-01 1.76492229e-01 -5.11044562e-01 -9.06813323e-01 1.25359082e+00 4.80458796e-01 4.37472276e-02 6.70632541e-01 -1.22726238e+00 -5.16967893e-01 9.38136160e-01 -4.43756223e-01 -1.07383709e-02 -2.71036148e-01 1.95297986e-01 1.25870323e+00 -1.13205612e-01 3.90274167e-01 1.00207210e+00 4.87335980e-01 6.30150080e-01 -1.70328617e+00 -1.35802698e+00 -1.72329947e-01 -2.99270809e-01 -1.52244222e+00 -5.57721317e-01 3.48193944e-01 -3.54761362e-01 8.08279634e-01 6.27051651e-01 -1.87131792e-01 9.85131264e-01 -2.26886291e-02 7.98026860e-01 7.87964404e-01 -4.51136500e-01 2.68026054e-01 5.60363233e-01 1.85355440e-01 5.95563829e-01 3.12894285e-01 -1.03356075e-02 -6.12969279e-01 -7.40793824e-01 3.60195905e-01 8.08270052e-02 -1.88647851e-01 -3.48618537e-01 -5.70433438e-01 1.01820517e+00 -7.41300434e-02 -2.09936369e-02 -9.04816296e-03 4.96938676e-01 5.30205727e-01 5.64487636e-01 5.08658767e-01 1.04847021e-01 -1.09953475e+00 -7.03950375e-02 -7.60794580e-01 4.95415688e-01 9.13449228e-01 1.36323237e+00 1.00037849e+00 -5.07653773e-01 -1.02591209e-01 5.73617995e-01 -2.13185325e-02 7.14431167e-01 3.92593116e-01 -1.08335364e+00 1.03944314e+00 1.88677087e-01 1.24009550e-01 -6.21263623e-01 1.23186462e-01 -2.39097342e-01 -9.32233930e-01 -2.93456852e-01 7.35263169e-01 -4.92263794e-01 -3.92283976e-01 2.25132799e+00 7.52924532e-02 -2.53709137e-01 -3.38780433e-02 3.01682148e-02 -4.28277347e-03 7.77349412e-01 1.87542632e-01 -1.81368545e-01 1.25256276e+00 -2.55432010e-01 -1.10925056e-01 -2.29957476e-01 1.42833245e+00 -4.84463811e-01 1.05766535e+00 1.57071590e-01 -1.31885386e+00 -1.25548750e-01 -5.69372594e-01 -1.36141673e-01 -3.15809995e-01 -1.32703170e-01 4.91403401e-01 1.30526125e+00 -9.01984930e-01 6.39662325e-01 -5.61932981e-01 8.12808871e-02 9.54091728e-01 8.05888534e-01 -4.73478913e-01 -1.28112689e-01 -1.23334730e+00 3.28860015e-01 1.66993603e-01 -6.06248319e-01 -6.34166241e-01 -8.14698637e-01 -4.42962795e-01 4.51395810e-01 2.20910367e-03 -6.64325774e-01 1.36401081e+00 -5.59790671e-01 -1.20456624e+00 1.31699896e+00 -1.83343291e-01 -7.56675601e-01 6.23523057e-01 3.41568649e-01 3.80184762e-02 4.34327275e-02 -2.77324617e-01 2.05225393e-01 8.89103949e-01 -9.49528754e-01 -9.73020077e-01 -9.91376460e-01 -8.77835676e-02 -1.70049712e-01 -7.44105101e-01 2.67311186e-02 -3.06623876e-01 -4.78883266e-01 -6.59749284e-02 -1.09959173e+00 -7.33167306e-02 -9.60147381e-02 -4.83240277e-01 -5.50706796e-02 9.05467570e-01 -6.29025936e-01 1.28404200e+00 -2.25925326e+00 -2.38007665e-01 7.52425551e-01 3.32480490e-01 2.46627346e-01 1.03791527e-01 3.27024817e-01 4.43833731e-02 3.49336952e-01 -2.85850495e-01 -7.28343904e-01 5.02726197e-01 1.22082457e-01 -5.42044163e-01 6.12094760e-01 -6.53871655e-01 5.89215577e-01 -3.03910915e-02 -3.99364293e-01 -2.41744578e-01 2.80306339e-01 -1.00338912e+00 2.15079635e-01 -6.58261955e-01 1.84728503e-01 -8.35629582e-01 3.03829089e-02 1.00348365e+00 -6.03119612e-01 3.00361276e-01 4.04721290e-01 6.24323010e-01 3.38148862e-01 -1.12637615e+00 1.17965162e+00 -2.31736317e-01 3.79291177e-01 5.48860967e-01 -1.26004100e+00 6.50672615e-01 2.70721555e-01 6.78268135e-01 -5.50222993e-01 3.54337931e-01 9.35392156e-02 -3.83054018e-01 -2.66278237e-01 4.15684581e-01 -3.89895320e-01 -1.90136299e-01 1.15388632e+00 -5.06397821e-02 1.54854730e-01 -5.97955287e-01 2.31627792e-01 1.17554104e+00 -6.15258694e-01 -4.06519413e-01 -2.02660039e-01 2.30492488e-01 -5.07709444e-01 2.99315244e-01 9.93847251e-01 -9.15083885e-02 2.10127786e-01 7.68885911e-01 -7.22617060e-02 -1.30742991e+00 -7.24439919e-01 -2.94151396e-01 1.60276520e+00 -1.97097361e-01 -2.87024319e-01 -1.19658530e+00 -9.50306237e-01 4.41364288e-01 8.54542375e-01 -5.96763372e-01 -1.72797456e-01 -5.21643519e-01 -9.01913822e-01 7.91985154e-01 1.98401645e-01 6.07502401e-01 -6.14023805e-01 -1.86356008e-01 -1.44343793e-01 -9.72271413e-02 -8.08778167e-01 -7.56448984e-01 5.49944699e-01 -7.43357122e-01 -6.73063755e-01 -5.61769009e-01 -7.79368997e-01 6.41965389e-01 6.66275844e-02 6.41163290e-01 -8.98059830e-02 -6.55387193e-02 2.91993827e-01 1.02597363e-01 -4.78745818e-01 -5.97824395e-01 5.14721513e-01 -2.99900770e-01 7.67544657e-02 7.59341896e-01 -8.47148418e-01 -7.39208341e-01 1.83714896e-01 -1.08167303e+00 -2.46519133e-01 3.08880985e-01 7.69745290e-01 4.53972518e-01 4.14114445e-01 2.26365432e-01 -1.47192061e+00 2.83823103e-01 -4.31061119e-01 -7.70266831e-01 1.97848409e-01 -8.45047593e-01 1.81694224e-01 7.44276881e-01 -3.64382714e-01 -7.51466751e-01 1.18888086e-02 -1.85618058e-01 -4.01641071e-01 1.67756200e-01 -3.36185321e-02 -4.35177922e-01 8.67391995e-04 7.03958511e-01 4.11197603e-01 3.94826770e-01 -6.22079432e-01 3.21550250e-01 1.08231759e+00 1.50510043e-01 -9.04317081e-01 5.46888113e-01 4.10837024e-01 6.85391054e-02 -5.20237863e-01 -4.54922974e-01 -9.76645201e-02 -3.23840052e-01 7.30048060e-01 4.85857934e-01 -7.92751849e-01 -1.40209198e+00 2.60616392e-01 -6.85122311e-01 -6.32259130e-01 -5.81489682e-01 2.56970257e-01 -1.08931363e+00 3.53210628e-01 -6.87004328e-01 -9.02360737e-01 -5.08203626e-01 -1.17175889e+00 9.45753217e-01 -2.98545510e-01 -1.33880945e-02 -8.76223326e-01 -3.88818085e-01 5.27630210e-01 3.74010742e-01 -3.82578373e-01 1.45310605e+00 -1.13966310e+00 -6.68681026e-01 -7.41149604e-01 -3.31949979e-01 5.98533154e-01 -2.69168049e-01 -5.04319489e-01 -1.37724519e+00 -6.30966902e-01 2.93541312e-01 -2.85870582e-01 7.37464964e-01 3.67281526e-01 2.11602974e+00 -9.56795871e-01 -6.30770683e-01 8.20293784e-01 1.13581216e+00 1.48357928e-01 6.02640450e-01 -1.00513123e-01 2.36424059e-01 5.14304399e-01 2.74850652e-02 8.98876369e-01 2.63496131e-01 3.72281641e-01 4.14458923e-02 2.01679215e-01 8.00221562e-01 -5.36714971e-01 1.21120341e-01 1.56572208e-01 6.97243333e-01 -3.85058999e-01 -6.36619985e-01 1.28667429e-01 -1.50270164e+00 -9.09558713e-01 4.59777296e-01 2.71034789e+00 1.22922122e+00 9.74293649e-02 4.31332551e-02 -4.81161736e-02 6.13164961e-01 4.26065512e-02 -6.60712600e-01 -2.98746258e-01 -3.47801186e-02 7.43379653e-01 1.27240777e+00 4.75116044e-01 -9.47522223e-01 6.36540532e-01 5.57112122e+00 1.34491360e+00 -9.69833314e-01 3.31029803e-01 1.31117845e+00 -2.76421487e-01 -5.61270177e-01 -1.20012630e-02 -1.12335253e+00 9.42288518e-01 1.59360647e+00 -5.05600452e-01 6.30675137e-01 1.18485224e+00 -2.79343247e-01 1.25633672e-01 -1.56766605e+00 1.15910864e+00 -4.49797064e-01 -1.54622555e+00 -1.19906612e-01 6.96571112e-01 5.08048534e-01 -9.56686437e-02 6.72047794e-01 4.99129325e-01 8.19219887e-01 -1.18751979e+00 2.26728603e-01 1.64883822e-01 1.15599072e+00 -9.81992781e-01 2.45715126e-01 8.97081614e-01 -4.91699100e-01 -3.39523256e-01 -5.78622341e-01 3.95608902e-01 -3.60555738e-01 3.45421195e-01 -5.92872262e-01 1.84524469e-02 7.43973076e-01 -1.41764387e-01 -6.68339208e-02 2.08231494e-01 6.36279583e-01 5.97032666e-01 -6.17192507e-01 4.03208919e-02 -9.24158916e-02 -7.73137584e-02 8.09955373e-02 1.17619407e+00 4.25888181e-01 4.24035817e-01 -1.23332851e-01 6.59836054e-01 -7.93997705e-01 2.45795846e-01 -6.44670367e-01 -1.47710964e-01 6.81861877e-01 4.82788920e-01 5.39751723e-02 -3.88695270e-01 -1.55198783e-01 9.76828933e-01 3.30817491e-01 2.97558933e-01 -5.91530085e-01 -3.77620429e-01 9.97471392e-01 4.06846315e-01 5.07261515e-01 -6.38972074e-02 -3.90437782e-01 -9.98450518e-01 -2.28680838e-02 -9.14548814e-01 9.85131025e-01 -2.60701805e-01 -1.41796720e+00 1.37419134e-01 -5.21107726e-02 -6.97755575e-01 -1.72748446e-01 -5.23583531e-01 8.09655413e-02 1.15034175e+00 -1.18074715e+00 -1.01569211e+00 6.22530043e-01 9.67477024e-01 -1.47546515e-01 -3.00002843e-01 1.24108636e+00 2.99145818e-01 -3.97882938e-01 1.78612030e+00 1.10716891e+00 1.47618085e-01 6.14712596e-01 -8.01575005e-01 1.56014085e-01 3.28785151e-01 -2.01005563e-02 7.21258223e-01 5.48278093e-01 -3.43925923e-01 -1.58804274e+00 -1.10231376e+00 9.93894815e-01 -5.89726388e-01 3.05869907e-01 -6.52350724e-01 -7.68544316e-01 1.51678133e+00 -3.12223464e-01 -3.76130524e-03 1.06120968e+00 7.17950612e-02 -6.47492468e-01 -4.10481840e-01 -1.91696632e+00 3.45305085e-01 8.53556991e-01 -9.33765233e-01 1.31284431e-01 6.67078614e-01 9.55287397e-01 -3.91139507e-01 -1.02192497e+00 -5.29718362e-02 4.43224519e-01 -6.97508693e-01 8.75783145e-01 -9.86065388e-01 7.02034086e-02 6.33893311e-01 -6.57267570e-01 -6.31675303e-01 3.56231965e-02 -1.23442876e+00 -1.89662799e-01 1.10635638e+00 6.08872294e-01 -9.67415214e-01 1.48938668e+00 1.57907355e+00 6.87238812e-01 -4.07597929e-01 -1.37523198e+00 -4.16945875e-01 9.45545375e-01 -5.64147949e-01 9.01406646e-01 8.50731015e-01 -5.19347601e-02 -1.17315173e-01 -3.80176514e-01 6.04281947e-02 7.83633113e-01 6.91005662e-02 1.09421468e+00 -1.06319642e+00 -7.41361201e-01 -2.51665622e-01 7.69983381e-02 -1.38082862e+00 4.24409062e-01 -1.10190332e+00 -3.75092983e-01 -5.28412938e-01 4.67918813e-01 -1.18141329e+00 -2.41424888e-01 4.04587299e-01 2.02683553e-01 -2.26285815e-01 8.03707819e-03 2.68302947e-01 -1.45966783e-01 4.08172697e-01 9.65409696e-01 4.28738706e-02 1.08445147e-02 5.90198934e-01 -1.08049464e+00 2.20267788e-01 6.49743438e-01 -6.34881556e-01 -2.51421273e-01 -2.44997025e-01 1.17807396e-01 4.63090360e-01 9.18250531e-02 -3.71762633e-01 3.68960977e-01 -1.60309851e-01 1.64707989e-01 -3.21495950e-01 4.09350425e-01 -1.14582455e+00 1.97223946e-01 3.52344275e-01 -8.66307080e-01 -2.88793325e-01 -7.55231455e-02 6.20528221e-01 4.66576576e-01 -2.79678553e-01 1.10966384e+00 -6.23036735e-02 3.26569527e-01 7.62931406e-01 -1.03187531e-01 1.33303404e-01 1.09060383e+00 2.50846017e-02 -1.61047295e-01 -6.47225082e-01 -5.90299249e-01 1.41513750e-01 4.91225362e-01 -3.02942514e-01 -2.49159336e-02 -7.49936640e-01 -4.11239862e-01 6.52766705e-01 2.79159397e-02 1.50649369e-01 5.14123857e-01 3.42807740e-01 -9.93599445e-02 5.81346929e-01 3.46076131e-01 -3.42842191e-01 -1.21983600e+00 7.39727914e-01 3.85118634e-01 -4.83674139e-01 -4.92959410e-01 1.34221280e+00 3.79162908e-01 -5.27575314e-01 6.87726557e-01 -6.80480227e-02 7.95576394e-01 -3.58333826e-01 5.28121471e-01 2.64578760e-01 1.00993112e-01 -3.80258650e-01 2.65099317e-01 -1.31634697e-01 -3.77092749e-01 -2.42870510e-01 1.28458905e+00 -2.90595263e-01 -3.77929769e-02 -2.20435753e-01 2.02094531e+00 -3.60799697e-03 -1.19762361e+00 -7.66408265e-01 -3.22155744e-01 -7.96226442e-01 -1.69791937e-01 -3.63102883e-01 -1.27953315e+00 1.10323775e+00 5.97164154e-01 1.44919887e-01 8.32273602e-01 8.43655989e-02 1.17027521e+00 4.91677284e-01 6.58133805e-01 -1.18401539e+00 -1.81518719e-01 2.31033385e-01 1.38232142e-01 -8.36831152e-01 -2.57754862e-01 -3.27802114e-02 -4.79150265e-01 6.41104996e-01 2.01605499e-01 2.74048895e-01 1.24360251e+00 4.37175184e-01 -4.29322243e-01 6.94999993e-02 -8.05624723e-01 4.73086894e-01 -3.98194671e-01 4.06908751e-01 -5.65041043e-02 1.54800072e-01 6.66681081e-02 1.01220083e+00 -5.04672825e-01 9.64365248e-03 -8.16435665e-02 1.03318489e+00 -4.61779356e-01 -1.60434210e+00 -1.30219236e-01 9.45860505e-01 -9.63123381e-01 2.07193778e-03 -1.32683571e-02 4.62385774e-01 -2.56976485e-02 6.19715095e-01 1.59146830e-01 -4.70983744e-01 -1.34759113e-01 6.08792961e-01 2.60487258e-01 -3.99101824e-01 -7.60857105e-01 -1.59108922e-01 -1.47112250e-01 -3.06991190e-01 4.49270695e-01 -7.09466517e-01 -1.15990162e+00 -1.20811653e+00 -2.22353607e-01 2.18843937e-01 6.17600322e-01 6.68662131e-01 7.48739064e-01 -5.42350531e-01 1.08789349e+00 -6.40564635e-02 -1.36502147e+00 -6.67347848e-01 -1.09246302e+00 4.55915898e-01 1.81636497e-01 1.39237866e-01 -4.86420006e-01 1.37527838e-01]	[5.90421724319458, 6.842350959777832]
6e07dfd3-546a-4c88-88f2-90d1d3b08e2e	semeval-2021-task-1-lexical-complexity	2106.00473	null	https://arxiv.org/abs/2106.00473v1	https://arxiv.org/pdf/2106.00473v1.pdf	SemEval-2021 Task 1: Lexical Complexity Prediction	This paper presents the results and main findings of SemEval-2021 Task 1 - Lexical Complexity Prediction. We provided participants with an augmented version of the CompLex Corpus (Shardlow et al 2020). CompLex is an English multi-domain corpus in which words and multi-word expressions (MWEs) were annotated with respect to their complexity using a five point Likert scale. SemEval-2021 Task 1 featured two Sub-tasks: Sub-task 1 focused on single words and Sub-task 2 focused on MWEs. The competition attracted 198 teams in total, of which 54 teams submitted official runs on the test data to Sub-task 1 and 37 to Sub-task 2.	['Marcos Zampieri', 'Gustavo Henrique Paetzold', 'Richard Evans', 'Matthew Shardlow']	2021-06-01	null	https://aclanthology.org/2021.semeval-1.1	https://aclanthology.org/2021.semeval-1.1.pdf	semeval-2021	['lexical-complexity-prediction']	['natural-language-processing']	[-4.46789622e-01 1.17737278e-01 -6.90044016e-02 -2.75707126e-01 -8.97121012e-01 -7.34851301e-01 3.24604839e-01 5.36917984e-01 -1.03934360e+00 8.59424353e-01 5.44377029e-01 -1.98672086e-01 1.79822743e-01 -4.30384785e-01 -2.17329130e-01 3.48939270e-01 1.00369053e-02 5.31977057e-01 1.17009908e-01 -5.32850802e-01 6.75864756e-01 -1.90841615e-01 -1.32146835e+00 8.65074396e-01 7.59035826e-01 8.63679528e-01 4.89746213e-01 7.15774953e-01 -2.44807824e-01 5.28613806e-01 -6.30364478e-01 -8.25541914e-01 1.94693878e-01 -1.61553547e-02 -1.11493134e+00 -2.81291544e-01 2.48677418e-01 3.07639927e-01 3.30851197e-01 8.94735336e-01 5.40640056e-01 3.70101750e-01 5.23018539e-01 -9.64852452e-01 -6.52583361e-01 8.54994535e-01 4.76995297e-02 2.82840908e-01 8.11978996e-01 -1.21399127e-02 1.55080926e+00 -1.74722505e+00 9.20213401e-01 1.22339952e+00 8.00036132e-01 4.56251353e-01 -1.16071832e+00 -9.01134729e-01 2.46058881e-01 4.29897249e-01 -1.47310865e+00 -5.04302263e-01 1.92922801e-01 -7.33028173e-01 1.84364760e+00 3.22741605e-02 5.69903374e-01 1.32604671e+00 -7.60647207e-02 6.08830571e-01 1.64159954e+00 -6.29468262e-01 2.17539147e-01 2.05005676e-01 5.79959154e-01 2.41112068e-01 2.74042457e-01 -1.91103071e-02 -8.79267931e-01 -5.43967634e-02 1.47298381e-01 -9.31974530e-01 1.93665221e-01 4.38543737e-01 -1.15864778e+00 1.08066952e+00 -3.78788590e-01 5.48262835e-01 -4.21258211e-01 -5.71787000e-01 8.39846671e-01 8.81717980e-01 7.30264664e-01 9.13932562e-01 -9.15336907e-01 -6.27029121e-01 -5.01367807e-01 7.85403371e-01 8.28420103e-01 8.85519087e-01 3.88478607e-01 -3.39426100e-01 -1.61188394e-01 1.37743187e+00 9.16172415e-02 9.73501205e-02 1.04492772e+00 -6.51675403e-01 7.59586632e-01 4.79080200e-01 2.95139641e-01 -7.06425905e-01 -9.02980387e-01 -2.28733703e-01 -2.73913383e-01 -1.26195848e-01 2.35841379e-01 -3.65493268e-01 -3.12180042e-01 1.96731627e+00 -1.09040931e-01 -6.15797997e-01 -7.90533274e-02 5.13896108e-01 1.11107230e+00 4.96629447e-01 5.00615835e-01 -4.95302737e-01 1.61991119e+00 -8.38179290e-01 -9.05691564e-01 -4.35277820e-01 1.07331324e+00 -1.08047378e+00 1.73933530e+00 7.85880744e-01 -1.33357370e+00 -9.04545665e-01 -8.86209607e-01 -6.13373667e-02 -8.27191472e-01 1.76149532e-02 2.71030307e-01 6.60525084e-01 -1.07224381e+00 1.82467028e-02 -9.52815861e-02 -2.43944272e-01 -3.19088310e-01 -5.84864467e-02 -5.77702284e-01 1.66681081e-01 -1.89536536e+00 1.51650512e+00 6.44828677e-01 -3.78293365e-01 -2.85744786e-01 -6.02506399e-01 -9.77646530e-01 -3.56748194e-01 3.69134575e-01 -2.12831706e-01 1.53354859e+00 -8.54452848e-01 -1.48016536e+00 1.49685335e+00 -1.92776567e-03 -6.84937909e-02 1.02059342e-01 -4.59808677e-01 -8.61615896e-01 -5.30158401e-01 6.10816300e-01 4.66034412e-01 3.18745017e-01 -6.28219724e-01 -9.05131757e-01 -1.66686714e-01 5.79602905e-02 4.24112767e-01 -5.17193019e-01 5.65500915e-01 -4.22272086e-02 -1.15505743e+00 -6.72245741e-01 -6.19825959e-01 6.76653683e-02 -8.37322414e-01 -1.87164530e-01 -9.05969381e-01 9.49696526e-02 -7.02176929e-01 1.97618341e+00 -1.93718088e+00 2.50125080e-01 -1.90166607e-01 2.51254141e-01 1.95758432e-01 -6.45459414e-01 7.58011222e-01 -4.39103395e-01 5.65204322e-01 3.23218942e-01 -6.83967471e-01 2.90803313e-01 -3.16602618e-01 1.76044866e-01 -8.44798461e-02 -1.53038073e-02 9.01228368e-01 -7.55170822e-01 -3.92766356e-01 -9.83118340e-02 -3.58700752e-01 -3.91128272e-01 2.53305137e-01 -2.17174187e-01 -2.42063627e-01 5.99813983e-02 4.68855858e-01 5.57662666e-01 5.73894903e-02 2.91519370e-02 -5.92661686e-02 -5.83490252e-01 6.62759483e-01 -1.24903846e+00 1.45481431e+00 -8.92460525e-01 4.59013671e-01 7.81947002e-02 -5.79639256e-01 5.52961588e-01 3.73105079e-01 8.15369412e-02 -1.01065028e+00 -4.00154144e-02 3.01550239e-01 1.67986587e-01 -5.82493722e-01 8.35558832e-01 -3.66665065e-01 -9.01349068e-01 3.91917408e-01 2.21561089e-01 -3.72262746e-01 7.23874569e-01 -1.33131266e-01 1.09269905e+00 -1.92166835e-01 1.02452898e+00 -8.13061953e-01 6.17396116e-01 -1.71510518e-01 4.78705078e-01 3.55176419e-01 -3.92054021e-01 7.94964731e-02 3.76640737e-01 -5.80601275e-01 -1.02494442e+00 -9.08353150e-01 -1.42351389e-01 1.73317111e+00 -2.28111267e-01 -1.09536052e+00 -5.46703339e-01 -4.06593204e-01 -2.38039151e-01 1.07015431e+00 -9.04942632e-01 1.96495086e-01 -3.10403824e-01 -2.37302512e-01 6.96733177e-01 3.85870665e-01 2.99695492e-01 -1.45187819e+00 -6.22891963e-01 4.57585275e-01 -7.12764978e-01 -1.42490876e+00 -7.92293072e-01 2.90692776e-01 -1.11139946e-01 -8.01079333e-01 -3.04888040e-01 -1.12410295e+00 -1.19351812e-01 -2.21906051e-01 1.60213339e+00 -1.00363150e-01 -3.32749575e-01 2.90471651e-02 -9.14449275e-01 -6.97134733e-01 -2.34975994e-01 4.17409956e-01 2.18745172e-01 -5.44084668e-01 7.70242572e-01 -4.64519374e-02 1.20824901e-02 3.12845767e-01 -4.76919174e-01 1.67861387e-01 5.29683411e-01 7.57006228e-01 3.62005979e-01 -2.02000037e-01 7.67927885e-01 -8.02768588e-01 1.38003111e+00 -3.94888699e-01 -3.48915964e-01 1.51853874e-01 -5.73410273e-01 -4.00546610e-01 5.07631600e-01 -4.60472435e-01 -7.31949151e-01 -1.40703797e-01 -5.41929603e-01 2.91489542e-01 4.86945622e-02 9.78404164e-01 -1.68444201e-01 2.37815648e-01 8.48466158e-01 -1.50354072e-01 -4.39905763e-01 -2.56672740e-01 2.40705833e-01 7.83296585e-01 3.50699782e-01 -8.83269012e-01 5.57165146e-01 -6.65958107e-01 -5.53632200e-01 -1.17836273e+00 -1.19983542e+00 -6.28593862e-01 -5.76595008e-01 -3.27950984e-01 1.09200716e+00 -1.17787254e+00 -5.74383616e-01 5.60472250e-01 -1.37095118e+00 -6.22757196e-01 -1.18811049e-01 3.43595386e-01 -3.38262200e-01 1.27323672e-01 -6.33875787e-01 -6.05937541e-01 -3.27984601e-01 -8.26209426e-01 8.76403451e-01 -2.87552416e-01 -1.17208278e+00 -1.03920889e+00 3.41064990e-01 2.50744194e-01 5.54912150e-01 2.36614537e-03 1.19550478e+00 -1.09122038e+00 6.41412318e-01 -1.18952483e-01 1.80106923e-01 3.30740869e-01 -1.81626052e-01 -2.75887907e-01 -5.10968924e-01 -1.55704720e-02 -3.65748741e-02 -1.27777243e+00 4.09543037e-01 6.46928698e-02 1.18520594e+00 -1.37703598e-01 2.51579165e-01 -5.50593324e-02 1.17525721e+00 -1.38595894e-01 3.37709278e-01 6.91461444e-01 2.27461755e-01 6.25937045e-01 8.42479944e-01 6.44748390e-01 7.10758030e-01 8.59219670e-01 4.57940325e-02 4.59564835e-01 9.58894342e-02 -1.50344372e-01 6.73164308e-01 1.41800690e+00 -4.58629653e-02 -3.53260845e-01 -1.06324530e+00 6.26634896e-01 -1.38540602e+00 -7.86635876e-01 -3.37152809e-01 2.05726504e+00 1.24342716e+00 5.57754755e-01 6.34117663e-01 5.12681343e-02 6.42225266e-01 2.20403552e-01 -1.26261160e-01 -8.52270603e-01 -4.20178831e-01 6.19449377e-01 -9.75131392e-02 9.54197586e-01 -9.78240132e-01 1.37088096e+00 6.53369999e+00 1.13599038e+00 -5.22590935e-01 2.84078330e-01 4.48766589e-01 -3.73759447e-03 -2.19197646e-01 -3.08205932e-01 -9.86150086e-01 4.71767843e-01 1.32642436e+00 -6.23898685e-01 3.48785281e-01 6.94336951e-01 2.29320582e-03 -2.07068712e-01 -1.06318557e+00 8.28460515e-01 1.14125438e-01 -7.17884362e-01 1.02986053e-01 -6.98722452e-02 3.73739123e-01 7.98696205e-02 2.37182099e-02 1.06289649e+00 1.11734666e-01 -1.24023259e+00 1.01134169e+00 3.78852218e-01 1.25615203e+00 -7.09640622e-01 9.60939825e-01 6.65680885e-01 -1.35674798e+00 8.52157101e-02 -2.57639468e-01 -7.07613826e-01 1.94212273e-01 3.47847134e-01 -3.97550404e-01 1.94946706e-01 5.02364397e-01 2.39223376e-01 -6.57251120e-01 4.51656669e-01 -2.13818952e-01 5.23405194e-01 8.38578492e-02 -5.06070852e-01 8.32014382e-02 4.32484150e-02 4.68116134e-01 1.74232149e+00 1.57674775e-01 1.21878892e-01 4.05563653e-01 2.98781097e-01 -2.25879803e-01 7.60428071e-01 -3.89757812e-01 -3.65068793e-01 9.75810349e-01 1.32449818e+00 -5.15277207e-01 -3.68391633e-01 -7.23764181e-01 8.46472561e-01 8.62174451e-01 -1.10141434e-01 -4.28727150e-01 -7.34929383e-01 5.98315716e-01 1.11565508e-01 8.62958059e-02 -3.92542839e-01 -7.01006770e-01 -9.65859830e-01 -4.19247337e-02 -1.17174494e+00 3.94716382e-01 -5.03715098e-01 -1.86155748e+00 9.43109751e-01 5.60812280e-02 -8.29608798e-01 -1.27062127e-01 -9.67053711e-01 -2.30274141e-01 1.24977160e+00 -1.12686217e+00 -8.89740109e-01 -2.53108621e-01 5.01450896e-01 1.17413926e+00 -3.35910082e-01 1.41431999e+00 1.69887975e-01 -2.34236076e-01 7.62938321e-01 -4.90473330e-01 -1.71967551e-01 1.08915985e+00 -1.42737055e+00 5.79132795e-01 2.93292731e-01 -1.24883927e-01 6.99934542e-01 6.76575899e-01 -9.11337554e-01 -6.72495425e-01 -8.18187833e-01 1.88257658e+00 -5.49347758e-01 1.09518099e+00 -7.11257815e-01 -6.81289434e-01 4.82516646e-01 4.93797839e-01 -3.32373828e-01 1.16110337e+00 4.02077138e-01 -2.35542536e-01 5.23487151e-01 -7.87084699e-01 4.88427848e-01 1.07686090e+00 -9.23407555e-01 -1.17629468e+00 3.77763242e-01 8.51572037e-01 -6.43692672e-01 -1.05100524e+00 3.56072187e-01 4.98157293e-01 -7.55407155e-01 4.45638597e-01 -7.23510325e-01 8.57422411e-01 3.47276211e-01 -5.31235218e-01 -1.80675972e+00 -6.55857861e-01 -5.29955447e-01 2.75205523e-01 7.93417513e-01 8.37315440e-01 -2.06973612e-01 1.45454764e-01 3.23288620e-01 -4.39294547e-01 -6.38796091e-01 -1.13082886e+00 -8.31684649e-01 5.82422853e-01 -7.70590723e-01 7.53025115e-02 1.03337097e+00 3.81672591e-01 9.68355179e-01 2.07730290e-02 -4.08052564e-01 3.96241136e-02 -4.38050151e-01 4.11097735e-01 -1.39017820e+00 -1.53071433e-01 -8.77274632e-01 8.87481123e-02 -6.51949763e-01 5.61361074e-01 -9.36166763e-01 -2.01773807e-01 -1.22370887e+00 1.51547700e-01 1.51173666e-01 -1.25480115e-01 4.33514237e-01 -5.60929418e-01 1.03299938e-01 1.52236074e-01 -1.86394319e-01 -8.25525224e-01 4.76673245e-01 6.60661936e-01 3.65379483e-01 -3.77364755e-02 -8.60370919e-02 -7.78626144e-01 6.90243185e-01 6.78244710e-01 -2.95107633e-01 -1.56771928e-01 -3.49085838e-01 7.53315032e-01 -1.43059671e-01 -1.29806072e-01 -7.27051973e-01 3.12944263e-04 -2.73888081e-01 1.75738677e-01 -4.38255310e-01 3.40393424e-01 -3.18426460e-01 -8.48526657e-02 3.83909762e-01 -5.74499786e-01 8.22693944e-01 6.17575586e-01 -1.84413418e-02 -5.23052752e-01 -5.78133643e-01 6.18709922e-01 -3.88301641e-01 -9.35346305e-01 -9.76765305e-02 -9.77084279e-01 6.84609711e-01 1.20708132e+00 -1.52276456e-01 -1.25346884e-01 -1.27751261e-01 -9.78361249e-01 2.82459587e-01 1.14550695e-01 7.47828722e-01 6.24101758e-01 -1.47091532e+00 -1.00634503e+00 -9.73078385e-02 5.92433929e-01 -5.21257281e-01 7.00442716e-02 4.41319078e-01 -2.79996663e-01 6.94207847e-01 -4.32307333e-01 2.97925085e-01 -1.41070640e+00 3.92328680e-01 -1.33388618e-03 -6.58027530e-01 -7.56692812e-02 1.16987300e+00 -2.00485989e-01 -5.76990783e-01 9.68865827e-02 -2.18139008e-01 -5.35070181e-01 5.89618921e-01 6.43515587e-01 3.81534934e-01 3.11125070e-01 -8.13711166e-01 -3.46337378e-01 4.08198059e-01 -2.69013494e-01 -5.53674221e-01 1.27676225e+00 -1.23520404e-01 -2.48196393e-01 1.21373367e+00 1.18814588e+00 3.19898665e-01 -6.34206384e-02 -3.50528866e-01 7.05537379e-01 -6.77411407e-02 -6.61419779e-02 -1.33967936e+00 -1.07595570e-01 6.61222756e-01 1.75846577e-01 1.76537216e-01 9.23373938e-01 -1.36591688e-01 6.55119717e-01 4.75819796e-01 3.98138463e-01 -1.95210564e+00 3.77045751e-01 1.37366629e+00 1.34843838e+00 -1.01964951e+00 -3.16682667e-01 -4.33079243e-01 -1.03409028e+00 1.26290798e+00 1.10240602e+00 6.61024973e-02 6.27484262e-01 3.48965228e-01 -6.56159669e-02 -2.23889217e-01 -1.23507595e+00 -1.16392732e-01 3.72041762e-01 4.79551196e-01 1.10843992e+00 4.65854853e-01 -1.26577961e+00 1.62703800e+00 -6.59211576e-01 -9.51225385e-02 3.66474777e-01 7.27402449e-01 -5.26412308e-01 -1.21607184e+00 -3.38302292e-02 4.57287043e-01 -4.56520915e-01 -5.28268039e-01 -7.75962412e-01 1.03439605e+00 3.16740394e-01 1.01209772e+00 -5.32967187e-02 -8.13644350e-01 8.47737074e-01 3.13851148e-01 2.19380170e-01 -1.09455955e+00 -1.01879930e+00 -1.98370650e-01 8.61849248e-01 -5.63936532e-01 -3.60581949e-02 -7.59390712e-01 -8.51086557e-01 -1.52248845e-01 -8.28622580e-02 3.36500585e-01 4.89480913e-01 1.01481581e+00 -2.68586371e-02 2.64727920e-01 4.92495477e-01 -5.60878098e-01 -7.53334165e-01 -1.74447775e+00 -6.00987732e-01 3.60371292e-01 -1.60206690e-01 -7.68259466e-01 -3.62156898e-01 -2.29159728e-01]	[10.645464897155762, 10.480134963989258]
2d08f446-4baf-4104-880b-c4480cc07740	interactive-mobile-app-navigation-with	2202.02312	null	https://arxiv.org/abs/2202.02312v3	https://arxiv.org/pdf/2202.02312v3.pdf	A Dataset for Interactive Vision-Language Navigation with Unknown Command Feasibility	Vision-language navigation (VLN), in which an agent follows language instruction in a visual environment, has been studied under the premise that the input command is fully feasible in the environment. Yet in practice, a request may not be possible due to language ambiguity or environment changes. To study VLN with unknown command feasibility, we introduce a new dataset Mobile app Tasks with Iterative Feedback (MoTIF), where the goal is to complete a natural language command in a mobile app. Mobile apps provide a scalable domain to study real downstream uses of VLN methods. Moreover, mobile app commands provide instruction for interactive navigation, as they result in action sequences with state changes via clicking, typing, or swiping. MoTIF is the first to include feasibility annotations, containing both binary feasibility labels and fine-grained labels for why tasks are unsatisfiable. We further collect follow-up questions for ambiguous queries to enable research on task uncertainty resolution. Equipped with our dataset, we propose the new problem of feasibility prediction, in which a natural language instruction and multimodal app environment are used to predict command feasibility. MoTIF provides a more realistic app dataset as it contains many diverse environments, high-level goals, and longer action sequences than prior work. We evaluate interactive VLN methods using MoTIF, quantify the generalization ability of current approaches to new app environments, and measure the effect of task feasibility on navigation performance.	['Bryan A. Plummer', 'Kate Saenko', 'Ranjitha Kumar', 'Sanjna Agrawal', 'Deniz Arsan', 'Andrea Burns']	2022-02-04	null	null	null	null	['vision-language-navigation']	['computer-vision']	[ 4.05291229e-01 -1.45656794e-01 -3.38202924e-01 -4.46964115e-01 -1.00967705e+00 -9.09385204e-01 3.72666836e-01 -2.48746514e-01 -5.93806088e-01 6.82922721e-01 2.33614355e-01 -8.90622675e-01 -5.75881964e-03 -3.11254412e-01 -9.30760562e-01 4.21992270e-03 6.00704700e-02 4.88420337e-01 3.52673560e-01 -3.03426057e-01 3.94455820e-01 -1.66025564e-01 -1.82749593e+00 3.94182593e-01 8.34636390e-01 9.22787130e-01 8.71560812e-01 8.99770141e-01 -2.25579023e-01 6.38157904e-01 -4.01828617e-01 -8.14948007e-02 1.50921941e-01 3.29707824e-02 -1.01316035e+00 -1.40894249e-01 4.23143297e-01 -4.98094350e-01 1.19838342e-01 1.04631150e+00 3.02216619e-01 5.97257674e-01 4.21281427e-01 -1.63166416e+00 -3.01868379e-01 6.87712371e-01 1.48076974e-02 -3.51346917e-02 1.15864027e+00 6.49303496e-01 9.63814795e-01 -8.46388280e-01 8.00158441e-01 1.24955058e+00 5.19699275e-01 7.44641244e-01 -1.01396823e+00 -2.42481738e-01 6.79782927e-01 4.98099923e-01 -1.05604553e+00 -4.95128989e-01 2.71549612e-01 -5.21427751e-01 1.27371895e+00 3.24841321e-01 4.36629087e-01 1.49088275e+00 2.46885136e-01 8.70291650e-01 7.88299859e-01 -2.87527382e-01 5.38440943e-01 -6.84157088e-02 2.71002591e-01 7.45191693e-01 -2.25426570e-01 1.42850488e-01 -8.81327391e-01 -1.07650630e-01 2.34598741e-01 -6.98992098e-03 -4.58615363e-01 -6.25938296e-01 -1.25514483e+00 5.35319746e-01 -5.44615556e-03 -2.22948357e-01 -3.08122367e-01 2.82645738e-03 2.96545118e-01 2.88740486e-01 -4.17664319e-01 7.43159473e-01 -6.61160827e-01 -1.10534298e+00 -3.63743037e-01 4.21598375e-01 9.82106209e-01 1.38416266e+00 7.60745049e-01 -2.26739228e-01 -1.76858008e-01 5.65960169e-01 2.09038049e-01 4.33313936e-01 7.42390394e-01 -1.68280661e+00 7.96237528e-01 4.35717762e-01 3.94592643e-01 -5.87063372e-01 -5.53536832e-01 2.03303918e-01 -2.49537397e-02 3.18024993e-01 6.34189367e-01 -1.65586397e-01 -8.13501656e-01 1.95513153e+00 1.85157329e-01 -1.87306911e-01 2.74920046e-01 7.79224932e-01 8.39156508e-01 3.27849925e-01 -1.36194974e-01 -2.32017025e-01 1.29359031e+00 -1.09277964e+00 -9.26166832e-01 -4.29899424e-01 9.22943234e-01 -6.20548010e-01 2.10944176e+00 7.21954584e-01 -7.26913929e-01 -5.34569085e-01 -6.31634295e-01 -2.53933929e-02 -3.95687580e-01 -2.15541750e-01 6.20905638e-01 5.03350437e-01 -1.01930726e+00 -2.53123008e-02 -8.17533970e-01 -2.91091323e-01 2.27812361e-02 2.40244061e-01 -2.97005236e-01 -4.05006617e-01 -1.00998950e+00 6.52375579e-01 1.68118581e-01 9.14742798e-02 -1.15850091e+00 -5.25248706e-01 -1.39474034e+00 -1.62473515e-01 1.32147324e+00 -5.69171846e-01 1.79917407e+00 -3.44173700e-01 -1.49222386e+00 1.87718749e-01 -4.36911732e-01 -1.65954173e-01 5.25585473e-01 -2.74688780e-01 -5.89404516e-02 -4.81071383e-01 4.06166881e-01 8.80681396e-01 7.24586427e-01 -1.21264172e+00 -9.03443158e-01 -3.55772793e-01 5.48956990e-01 5.64904630e-01 1.94442496e-01 -4.63139147e-01 -7.87810028e-01 8.14071968e-02 2.92139500e-02 -1.22070003e+00 -2.39488199e-01 -4.15198237e-01 -5.06530464e-01 -3.43404889e-01 7.22928584e-01 -4.55050170e-01 1.27051663e+00 -2.19065881e+00 2.27961525e-01 -4.20158468e-02 1.05419718e-01 -3.86226565e-01 -4.47180629e-01 1.65342256e-01 5.24283767e-01 1.64229527e-01 -1.17075697e-01 -2.74832517e-01 1.80840939e-01 4.76495713e-01 -3.89641762e-01 -5.01943052e-01 -2.37293690e-01 9.84874904e-01 -9.08935547e-01 -4.98322368e-01 5.57559356e-02 -5.16855046e-02 -9.44057465e-01 2.22618520e-01 -7.31635690e-01 3.39091927e-01 -2.45752692e-01 8.72260273e-01 2.77436465e-01 -4.65457328e-02 1.36595756e-01 -7.35066831e-02 -2.06531897e-01 3.49993527e-01 -1.23004019e+00 2.02304578e+00 -8.19383740e-01 7.29306757e-01 9.32338312e-02 -3.54158789e-01 3.24339330e-01 -2.51171768e-01 6.26670057e-03 -7.88499296e-01 -3.69228095e-01 -2.45246682e-02 7.51999915e-02 -1.05925906e+00 8.53528976e-01 6.78218842e-01 -4.03343827e-01 2.33066216e-01 -3.20674896e-01 -4.39522028e-01 2.52010316e-01 2.17320129e-01 1.45657361e+00 4.60087866e-01 1.90958366e-01 2.35639408e-01 1.53584167e-01 3.26070070e-01 3.59959632e-01 1.43787909e+00 -5.72829664e-01 2.49223635e-01 5.23016810e-01 -1.82649806e-01 -4.80573535e-01 -1.06326950e+00 2.93403745e-01 1.76641369e+00 3.40934932e-01 -5.45830727e-01 -6.68332398e-01 -9.33277428e-01 -3.12850028e-01 1.03149319e+00 -4.07514781e-01 1.31509408e-01 -5.24614215e-01 -1.23252310e-01 2.90936828e-01 4.84413832e-01 3.85104716e-01 -1.25779760e+00 -1.01248074e+00 -3.30363773e-02 -7.81981409e-01 -1.44415629e+00 -9.75598514e-01 3.18323642e-01 -5.92888296e-01 -1.24081802e+00 -4.65561785e-02 -8.40834200e-01 4.46917892e-01 1.33238524e-01 1.24714947e+00 -1.77431583e-01 2.00496595e-02 1.04170763e+00 -3.61593664e-01 -1.01880431e-01 -3.46360087e-01 -2.19241474e-02 3.11839908e-01 -6.26706064e-01 2.83680618e-01 -4.15617153e-02 -1.86749771e-01 5.20916164e-01 -6.51996076e-01 2.53118277e-02 4.57386672e-01 9.99846399e-01 7.43679285e-01 6.74187988e-02 1.44846126e-01 -7.22370982e-01 1.18305039e+00 -2.70855963e-01 -5.94436467e-01 4.60101724e-01 -7.22029924e-01 2.66796201e-01 3.22452188e-01 -6.45868301e-01 -1.13300586e+00 3.94218624e-01 -8.66890252e-02 -1.77951708e-01 -4.84709442e-01 7.41433501e-01 -3.81552488e-01 2.57723778e-01 7.76842475e-01 4.62407649e-01 -3.01429313e-02 -1.69905514e-01 5.33272445e-01 6.09859109e-01 7.86202669e-01 -8.52781236e-01 1.45182535e-01 2.62495745e-02 -2.24191785e-01 -7.20576227e-01 -3.23403299e-01 -2.98406243e-01 -3.01390976e-01 -1.50848299e-01 7.55726337e-01 -7.21885324e-01 -1.26280475e+00 1.53584883e-01 -1.15421796e+00 -9.96322811e-01 -1.44804046e-01 5.02033532e-01 -8.97351265e-01 4.48663414e-01 -2.57128000e-01 -8.45343590e-01 3.32354277e-01 -1.89982378e+00 1.13571620e+00 1.53792873e-01 -5.78555584e-01 -5.89367449e-01 -3.27672899e-01 4.52445418e-01 2.33296707e-01 -5.30189097e-01 1.14776242e+00 -5.72389364e-01 -7.07547843e-01 3.36372167e-01 -8.71239579e-04 -2.07022429e-01 1.82017133e-01 -2.70223022e-01 -4.67086613e-01 1.21592851e-02 5.62613979e-02 -5.56306064e-01 5.07104278e-01 3.53043050e-01 1.31180942e+00 -4.62010980e-01 -3.52282137e-01 3.65380168e-01 1.06356478e+00 6.15234196e-01 3.30699533e-01 3.92770141e-01 6.94185078e-01 7.69451380e-01 1.05987108e+00 3.38573873e-01 8.50995362e-01 9.82706487e-01 7.55967438e-01 7.18545794e-01 1.77683339e-01 -4.09217209e-01 7.08134711e-01 3.15712899e-01 1.24071673e-01 -3.51578414e-01 -1.08535075e+00 2.20269889e-01 -2.00048423e+00 -6.33127272e-01 1.30414993e-01 2.17390132e+00 8.22804630e-01 3.79377425e-01 4.33388911e-02 -2.98328936e-01 1.98451698e-01 -1.64614215e-01 -9.49779689e-01 -4.27183956e-01 3.46346229e-01 -3.77802968e-01 1.15241431e-01 1.06295979e+00 -7.98168421e-01 1.03180456e+00 6.08030462e+00 7.06306934e-01 -7.73889840e-01 -3.52794938e-02 1.91670910e-01 -3.84802371e-02 -5.37860632e-01 -2.19854891e-01 -9.93614912e-01 4.97841120e-01 5.32161534e-01 3.20680261e-01 7.97731459e-01 1.02767169e+00 3.08003366e-01 -7.85087287e-01 -1.65747070e+00 1.17448497e+00 3.92665118e-02 -9.96017396e-01 -1.06877662e-01 -1.59637392e-01 2.69661903e-01 -6.14959560e-02 5.12626410e-01 8.73126149e-01 5.23562551e-01 -1.04325187e+00 4.81445760e-01 5.64771295e-01 9.02044237e-01 -2.53116310e-01 4.63321030e-01 8.26079309e-01 -1.00486946e+00 -3.37237030e-01 1.46581456e-01 -3.55725497e-01 2.04204112e-01 -2.21785754e-01 -1.26988888e+00 1.20753080e-01 9.60997224e-01 3.17939758e-01 -6.28995836e-01 6.22484326e-01 -1.14824697e-01 2.15474084e-01 -3.06021273e-01 -4.51492637e-01 1.13323852e-01 7.58214816e-02 6.47682548e-01 6.95184827e-01 4.38788623e-01 -1.58831179e-01 4.65747565e-01 8.11980009e-01 3.02041054e-01 -1.64130777e-01 -9.90883887e-01 8.85987878e-02 7.13089168e-01 7.28552699e-01 -3.84048969e-01 -1.19917266e-01 -4.08127874e-01 1.05393267e+00 1.08234353e-01 7.48273790e-01 -7.75140107e-01 -1.30863309e-01 9.00568724e-01 -9.23537165e-02 6.48511425e-02 -5.75076938e-01 -2.69268900e-01 -9.07297909e-01 3.25390041e-01 -1.11312413e+00 1.36848748e-01 -1.09349847e+00 -8.21813524e-01 5.13815045e-01 7.04345703e-02 -1.12757993e+00 -8.48723054e-01 -7.71010399e-01 -2.58081347e-01 5.90290129e-01 -1.24569666e+00 -5.39143682e-01 -6.23487353e-01 5.37035704e-01 1.36930084e+00 -2.05165982e-01 8.25775862e-01 -1.80261493e-01 -4.60207373e-01 5.51006198e-01 -4.07435149e-01 -4.12347168e-01 8.10323000e-01 -1.20808268e+00 2.45641619e-01 6.08022273e-01 9.43667293e-02 7.75062263e-01 8.28163922e-01 -9.87908065e-01 -1.67928851e+00 -7.55387187e-01 5.25236428e-01 -1.11867821e+00 4.04651612e-01 -3.35356086e-01 -6.48747683e-01 8.83960962e-01 -4.60725315e-02 -2.48443440e-01 5.86243689e-01 1.93238690e-01 -1.83382750e-01 3.99953693e-01 -8.68334770e-01 1.06806695e+00 1.61830676e+00 -5.39052486e-01 -7.67296433e-01 2.30632335e-01 1.19395769e+00 -9.33047950e-01 -1.91420063e-01 4.67557073e-01 7.63534844e-01 -8.71274054e-01 8.15505445e-01 -6.85575902e-01 4.24703419e-01 -4.04943556e-01 -6.37694001e-01 -1.22364676e+00 9.84950066e-02 -5.65447867e-01 -2.47099131e-01 6.77241802e-01 8.35018158e-01 -2.60687888e-01 8.26793075e-01 9.59204018e-01 -3.73666406e-01 -8.53765666e-01 -9.33618367e-01 -7.50220418e-01 -6.38052523e-01 -1.23630011e+00 6.08043373e-01 3.91473800e-01 1.21927336e-01 3.81018698e-01 -2.23805740e-01 1.63469210e-01 2.02355579e-01 -9.41200182e-02 9.07129765e-01 -8.71642411e-01 -3.21680218e-01 -4.20064360e-01 1.15945905e-01 -1.71856916e+00 4.90698963e-01 -5.23493826e-01 7.49543667e-01 -1.38526511e+00 -6.89775050e-02 -4.94871229e-01 2.17945904e-01 4.59894150e-01 -4.73190024e-02 -2.04970911e-01 2.93635637e-01 2.16683835e-01 -1.21855223e+00 2.71623582e-01 1.12312174e+00 -3.38095129e-01 -8.78323793e-01 4.33332533e-01 -6.34822071e-01 8.58398080e-01 5.01340210e-01 1.57328650e-01 -8.56212497e-01 -4.37654078e-01 7.16731429e-01 3.37227523e-01 1.76689640e-01 -8.37911189e-01 4.77037996e-01 -4.86908227e-01 -4.20529656e-02 -5.80004811e-01 5.59329689e-01 -1.04270089e+00 -6.52915761e-02 2.74937510e-01 -6.72520161e-01 3.18097144e-01 1.73575610e-01 7.51555979e-01 -3.93329449e-02 -4.17737782e-01 -1.84743851e-01 -1.17460899e-01 -1.58054757e+00 1.82371009e-02 -7.61482656e-01 2.43790060e-01 8.79518807e-01 -4.85908538e-01 -3.37942868e-01 -7.17493355e-01 -1.06912935e+00 6.56827748e-01 4.25922960e-01 7.20809460e-01 9.91164565e-01 -1.06739318e+00 6.02163486e-02 3.72817606e-01 4.64905173e-01 2.95884162e-01 2.34973133e-01 8.01256120e-01 -3.75824869e-02 3.91585022e-01 -1.13692880e-01 -8.97853613e-01 -1.40452099e+00 4.94913727e-01 1.35495052e-01 3.36416662e-02 -9.64998305e-02 1.00213313e+00 2.40845472e-01 -7.64473736e-01 7.72555590e-01 -8.26475739e-01 -3.88520569e-01 -1.78562418e-01 2.83374012e-01 2.26699665e-01 -6.00350760e-02 -1.12208538e-01 -4.46830273e-01 4.16981399e-01 2.64806077e-02 -3.69124860e-01 4.92565423e-01 -5.11306405e-01 2.80175418e-01 7.93218732e-01 6.27341092e-01 1.03592739e-01 -1.41409242e+00 -3.94720100e-02 5.20244204e-02 -3.87510628e-01 -4.52286035e-01 -1.12765181e+00 -2.76486397e-01 6.77395821e-01 7.63487697e-01 6.11915849e-02 8.11896741e-01 1.51523516e-01 4.80382115e-01 1.21538615e+00 6.30726337e-01 -1.18935430e+00 4.35898364e-01 1.05194747e+00 8.63193393e-01 -1.87067413e+00 -5.20563900e-01 -3.62305641e-01 -8.84978414e-01 7.92412758e-01 1.40581274e+00 1.06288373e+00 2.87359864e-01 3.08958471e-01 1.20327175e-01 6.06329255e-02 -9.76521134e-01 -1.81900129e-01 5.51165007e-02 1.12697101e+00 9.33169276e-02 1.47347212e-01 3.37564275e-02 9.08065438e-01 -5.97321570e-01 4.82931267e-03 7.79781222e-01 9.09352183e-01 -3.22550297e-01 -8.82900536e-01 -2.82386869e-01 6.06629848e-01 1.01460479e-01 -1.97978720e-01 -2.36165941e-01 5.89552879e-01 1.03031188e-01 1.15828335e+00 -2.14433391e-02 -7.75465012e-01 4.99952853e-01 3.06867480e-01 3.19527030e-01 -9.83194113e-01 -1.32953361e-01 -2.80858696e-01 3.12055796e-01 -1.06242323e+00 1.12270117e-01 -6.57126069e-01 -1.49859583e+00 2.30539382e-01 -1.82778865e-01 -2.99962945e-02 7.83004224e-01 1.01177120e+00 4.04887974e-01 6.18035913e-01 7.87537843e-02 -8.94748926e-01 -6.23044431e-01 -6.65415883e-01 9.95122194e-02 1.31193712e-01 5.64720154e-01 -7.33112395e-01 -2.30263665e-01 3.10985055e-02]	[4.451298713684082, 0.7181888222694397]
c2d93b05-a70b-41d0-b3a5-0b78076a6c91	domain-adaptation-for-head-pose-estimation	null	null	https://ieeexplore.ieee.org/document/10021684	https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10021684	Domain Adaptation for Head Pose Estimation Using Relative Pose Consistency	Head pose estimation plays a vital role in biometric systems related to facial and human behavior analysis. Typically, neural networks are trained on head pose datasets. Unfortunately, manual or sensor-based annotation of head pose is impractical. A solution is synthetic training data generated from 3D face models, which can provide an infinite number of perfect labels. However, computer generated images only provide an approximation of real-world images, leading to a performance gap between training and application domain. Therefore, there is a need for strategies that allow simultaneous learning on labeled synthetic data and unlabeled real-world data to overcome the domain gap. In this work we propose relative pose consistency, a semi-supervised learning strategy for head pose estimation based on consistency regularization. Consistency regularization enforces consistent network predictions under random image augmentations, including pose-preserving and pose-altering augmentations. We propose a strategy to exploit the relative pose introduced by pose-altering augmentations between augmented image pairs, to allow the network to benefit from relative pose labels during training on unlabeled data. We evaluate our approach in a domain-adaptation scenario and in a commonly used cross-dataset scenario. Furthermore, we reproduce related works to enforce consistent evaluation protocols and show that for both scenarios we outperform SOTA.	['Jörn Ostermann', 'Felix Kuhnke']	2023-01-19	null	null	null	ieee-transactions-on-biometrics-behavior-and-2	['head-pose-estimation']	['computer-vision']	[ 2.31772438e-01 3.59843582e-01 -1.70288429e-01 -9.10823107e-01 -7.19322085e-01 -4.30997401e-01 4.51826334e-01 -1.73855156e-01 -5.63490570e-01 7.49837458e-01 -4.97167872e-04 1.68538243e-01 1.24884814e-01 -4.73532975e-01 -8.85000110e-01 -6.23264194e-01 4.53536697e-02 6.45137489e-01 -8.23071748e-02 2.98786163e-02 -1.35449260e-01 6.91409290e-01 -1.67066586e+00 -2.13209718e-01 5.16825140e-01 9.85722363e-01 -3.91261876e-02 2.68227071e-01 1.46508604e-01 2.25744426e-01 -5.11789083e-01 -4.63023245e-01 5.07141888e-01 -2.30758250e-01 -5.91177225e-01 5.05047500e-01 9.72902834e-01 -4.30796832e-01 -8.53595063e-02 1.05706000e+00 8.41716826e-01 -3.87366042e-02 5.54418325e-01 -1.59491253e+00 -5.87321669e-02 2.51784116e-01 -6.31174982e-01 -3.52449894e-01 4.88951445e-01 1.00610562e-01 5.36276102e-01 -7.89388955e-01 6.46795392e-01 1.14464402e+00 8.88893723e-01 1.03608191e+00 -1.30091166e+00 -8.16964984e-01 1.21829085e-01 9.29717347e-03 -1.58854663e+00 -8.43538404e-01 1.09866023e+00 -2.27019981e-01 2.67856032e-01 1.67134970e-01 5.24953425e-01 1.24061227e+00 -4.22712892e-01 7.63659239e-01 1.21250701e+00 -4.86362994e-01 3.69765580e-01 1.52987689e-01 3.55090685e-02 5.98830760e-01 2.56991297e-01 6.66071549e-02 -7.45591044e-01 -1.86649546e-01 6.34695530e-01 -2.02150717e-01 -4.83029097e-01 -8.13301563e-01 -7.86421180e-01 4.84019279e-01 4.04507995e-01 -1.12407049e-02 -3.05140913e-01 -2.03134507e-01 2.64621556e-01 5.64002506e-02 4.45685506e-01 1.68873161e-01 -5.21757543e-01 3.10559809e-01 -1.07691264e+00 3.09735239e-01 8.44129920e-01 1.04278362e+00 8.52574825e-01 1.99733712e-02 6.70701042e-02 8.78863990e-01 6.13832474e-01 6.98021352e-01 5.30846298e-01 -9.18784976e-01 3.13156366e-01 5.46337485e-01 -1.01354063e-01 -9.33811367e-01 -6.10510886e-01 -2.69441903e-01 -7.61770248e-01 5.16001396e-02 8.68265212e-01 -3.30282599e-02 -1.06412268e+00 2.34637761e+00 5.98353148e-01 2.71082252e-01 -1.89589411e-01 9.19262648e-01 7.71330833e-01 -2.07712844e-01 3.92146781e-02 -3.46750528e-01 1.32526839e+00 -4.47407067e-01 -6.66094661e-01 -4.48289424e-01 5.38873911e-01 -5.38770556e-01 1.01486361e+00 2.06843004e-01 -9.07459199e-01 -2.81548142e-01 -9.96439219e-01 2.17452988e-01 -2.39525422e-01 1.70143440e-01 2.54502565e-01 1.05423272e+00 -1.06498885e+00 3.24088335e-01 -8.04508686e-01 -4.54241455e-01 3.52408051e-01 8.03097129e-01 -8.30578446e-01 -1.10653795e-01 -9.49826002e-01 7.74827540e-01 2.33935773e-01 3.78665775e-01 -4.81812000e-01 -4.79561329e-01 -1.08924496e+00 -3.62310082e-01 3.24788302e-01 -3.38177949e-01 1.29540205e+00 -8.62222314e-01 -1.49043107e+00 1.25970733e+00 -1.91587970e-01 -3.92615139e-01 7.19053447e-01 -3.28088850e-02 -2.45972246e-01 -1.23460643e-01 -2.26474479e-02 9.32431638e-01 9.88675237e-01 -1.42675710e+00 -2.46603321e-02 -9.60976064e-01 -2.14951262e-01 1.59133613e-01 -4.98662800e-01 -1.82785794e-01 -7.22977519e-01 -2.79253840e-01 4.64794219e-01 -1.31928170e+00 -7.71092176e-02 2.64056295e-01 -5.99474669e-01 1.88261956e-01 7.86320031e-01 -6.54048145e-01 6.74139798e-01 -1.95211923e+00 -1.80453673e-01 4.63987947e-01 1.48084030e-01 2.61822075e-01 -1.39103547e-01 -2.54177272e-01 -2.19165996e-01 -3.11756551e-01 -2.92589456e-01 -8.61693740e-01 -9.75429788e-02 3.48556697e-01 6.91286922e-02 8.19223940e-01 -3.60910199e-03 6.43221736e-01 -6.61529541e-01 -6.48379922e-01 1.27648920e-01 5.71952522e-01 -5.79924285e-01 2.51092702e-01 -1.55856073e-01 9.19792235e-01 -2.24559367e-01 6.60071194e-01 1.04640627e+00 -9.00546759e-02 4.58945543e-01 -4.29367930e-01 4.21937495e-01 -1.01273218e-02 -1.32863092e+00 1.72934222e+00 -4.33525234e-01 3.56520981e-01 2.14721099e-01 -7.97443449e-01 8.82625103e-01 4.29681391e-01 4.87185597e-01 -5.11409998e-01 4.31882381e-01 2.02814832e-01 -8.84084925e-02 -2.90238082e-01 2.53755540e-01 -1.52838320e-01 8.09486136e-02 3.33157986e-01 3.50061134e-02 -1.01085469e-01 -1.24981396e-01 -2.47932285e-01 6.90202832e-01 1.66174695e-01 2.06185713e-01 -7.08458573e-02 5.89743078e-01 -4.82525885e-01 6.54603899e-01 3.34205776e-01 -4.63812232e-01 9.40598667e-01 2.46495098e-01 -4.01990831e-01 -9.21995044e-01 -6.82562768e-01 -3.29058290e-01 9.71919298e-01 -9.39955637e-02 -1.61704980e-02 -1.17316234e+00 -8.75707567e-01 -2.49246862e-02 3.31855565e-01 -7.16002166e-01 -7.59119019e-02 -7.05701113e-01 -7.97067523e-01 6.91988409e-01 5.74925900e-01 5.56688190e-01 -8.26275527e-01 -4.13199961e-01 -1.31330892e-01 -4.99330685e-02 -1.43713844e+00 -6.15251184e-01 -1.21043203e-03 -6.90262735e-01 -1.19501126e+00 -8.32146585e-01 -6.64677620e-01 1.10875356e+00 -5.33091687e-02 9.02009547e-01 -6.92177936e-02 2.95321327e-02 4.39388633e-01 6.11183420e-02 -2.48528555e-01 -3.19547176e-01 5.01941554e-02 5.53251326e-01 2.88648605e-01 3.72698903e-01 -7.07307160e-01 -6.23938501e-01 5.06956279e-01 -7.42613614e-01 -8.03525820e-02 4.74837571e-01 9.00234520e-01 4.83294934e-01 -6.05056643e-01 4.67845082e-01 -9.37296331e-01 3.66133362e-01 -8.49359259e-02 -6.14768922e-01 2.57893085e-01 -6.34286642e-01 2.65363395e-01 3.53789657e-01 -5.86366415e-01 -1.00164914e+00 6.78656340e-01 -2.03063011e-01 -6.27824306e-01 -4.37030524e-01 3.42394292e-01 -7.47487307e-01 -3.26440394e-01 9.00776505e-01 4.02259082e-02 3.49619895e-01 -4.78002191e-01 2.72536367e-01 7.01448739e-01 8.01721752e-01 -7.64621794e-01 8.33120108e-01 4.99328256e-01 2.50212401e-01 -8.57891500e-01 -6.58747554e-01 -2.49187663e-01 -8.99695992e-01 -1.87756673e-01 4.89687264e-01 -7.68612385e-01 -6.93433285e-01 6.83853090e-01 -1.10843050e+00 -1.15037113e-01 -2.29071770e-02 4.74789858e-01 -6.01485431e-01 3.97227407e-01 -1.98008254e-01 -8.94621432e-01 -2.04737470e-01 -1.18806612e+00 1.34007502e+00 1.54217944e-01 -2.09196135e-01 -8.01123738e-01 7.84760527e-03 3.25673789e-01 1.31285742e-01 2.54208058e-01 3.42532337e-01 -9.53402996e-01 -3.15159678e-01 -5.73169410e-01 -1.07643083e-01 2.97422379e-01 1.92992955e-01 -4.17277753e-01 -1.37898886e+00 -4.60686415e-01 -6.70672432e-02 -5.10373592e-01 2.83682883e-01 3.39384973e-01 1.10878062e+00 -2.42196411e-01 -2.52547115e-01 5.39522886e-01 8.87740314e-01 -1.15074374e-01 4.94138688e-01 9.13384743e-03 7.75897026e-01 1.03412163e+00 2.96187133e-01 3.61378849e-01 5.13085246e-01 1.01733887e+00 3.12251419e-01 7.36619486e-03 -1.58449262e-01 -4.73484993e-01 -7.71503383e-03 4.30047333e-01 7.13282377e-02 -6.87076971e-02 -9.71379220e-01 2.83183426e-01 -1.54755449e+00 -4.89571124e-01 2.14382127e-01 2.63169909e+00 9.58566427e-01 -4.78253737e-02 3.03581625e-01 3.64666253e-01 8.27820301e-01 -1.60406023e-01 -6.42241478e-01 3.07530075e-01 3.89281139e-02 7.03740120e-02 5.35654664e-01 4.26174432e-01 -1.13562274e+00 7.17350960e-01 5.90000343e+00 3.40306491e-01 -1.44157863e+00 1.09777838e-01 6.31748080e-01 4.02117111e-02 6.24071062e-03 -4.52948749e-01 -9.22477663e-01 3.60855281e-01 8.94550443e-01 1.54592335e-01 1.03288047e-01 9.75031078e-01 1.51229024e-01 9.18757841e-02 -1.42961550e+00 1.18719339e+00 3.04741353e-01 -7.14676917e-01 -2.58906484e-01 2.45942414e-01 4.22025234e-01 -2.78839409e-01 1.85475305e-01 9.13582966e-02 -9.39139575e-02 -9.00844336e-01 5.79411507e-01 1.26130283e-01 1.00667489e+00 -5.03364742e-01 6.62945569e-01 3.62230539e-01 -1.02945352e+00 2.71079004e-01 9.86906961e-02 2.74804860e-01 4.24713641e-02 3.07051897e-01 -1.20934987e+00 3.26254189e-01 4.30191070e-01 3.77261907e-01 -5.97488046e-01 9.21424091e-01 -1.94770455e-01 3.02099645e-01 -6.07475221e-01 3.55498314e-01 -4.46131319e-01 1.06894344e-01 3.80346477e-01 7.23223090e-01 9.63895097e-02 -2.16824457e-01 8.49636197e-02 4.85725731e-01 -2.61479050e-01 4.51408587e-02 -6.49442911e-01 4.85852957e-01 6.93753779e-01 9.80978727e-01 -6.22956216e-01 3.02687902e-02 -3.16555113e-01 9.40933883e-01 2.51805931e-01 2.34307781e-01 -6.61274731e-01 1.21206567e-01 5.29002726e-01 3.46651256e-01 -1.88008040e-01 -1.97935533e-02 -3.17764163e-01 -1.10093975e+00 2.20181704e-01 -9.78372574e-01 1.37895018e-01 -3.73480976e-01 -1.10025072e+00 6.26976252e-01 2.00685278e-01 -1.34777069e+00 -7.22472429e-01 -5.37526488e-01 -2.99385309e-01 7.43817091e-01 -1.34028125e+00 -1.47572374e+00 -5.24325550e-01 5.32103658e-01 1.78426400e-01 -1.23442942e-02 8.81872714e-01 5.55392742e-01 -6.05831027e-01 1.25882900e+00 -3.51681620e-01 2.39513800e-01 9.25835669e-01 -9.86804366e-01 2.61301070e-01 5.59884191e-01 8.40481818e-02 7.06980169e-01 8.78728092e-01 -4.96502787e-01 -1.34406102e+00 -1.05988884e+00 6.28288865e-01 -3.29137772e-01 3.67713459e-02 -4.92887557e-01 -1.09226823e+00 8.28634977e-01 -2.90376604e-01 5.31049490e-01 6.59221232e-01 1.23198271e-01 -4.99513298e-01 -1.90553352e-01 -1.54163754e+00 5.20231545e-01 1.12037456e+00 -5.40454507e-01 -2.81433225e-01 2.66855091e-01 1.92727387e-01 -7.04364717e-01 -5.39398551e-01 6.59698486e-01 8.45239997e-01 -7.48369336e-01 8.49539936e-01 -4.26310420e-01 -1.40961230e-01 -2.87683755e-01 -2.30128497e-01 -1.16073775e+00 4.43057328e-01 -4.94015217e-01 -7.27366880e-02 1.22480309e+00 2.91222453e-01 -5.86947024e-01 1.41561294e+00 1.13849294e+00 1.75739303e-01 -4.90858465e-01 -1.06905365e+00 -8.28334391e-01 -2.79894099e-02 -5.00195265e-01 7.16869235e-01 8.80271375e-01 -2.00242698e-01 2.33526200e-01 -4.55878794e-01 3.05688500e-01 9.07695651e-01 -3.03548843e-01 1.04830289e+00 -1.49072850e+00 -9.20650139e-02 -9.04328302e-02 -7.09466994e-01 -1.06099343e+00 6.41848147e-01 -5.97850204e-01 2.55579263e-01 -7.60581851e-01 1.67891726e-01 -4.82326597e-01 6.12477623e-02 6.65931404e-01 8.23672935e-02 6.01879299e-01 1.34634320e-02 1.31830603e-01 -2.56689012e-01 4.82689112e-01 1.05380249e+00 3.79707515e-02 -2.54378140e-01 1.77351713e-01 -2.88827419e-01 9.35368538e-01 5.89214265e-01 -2.79791266e-01 -5.20323753e-01 -2.42543250e-01 -7.16371462e-02 1.14921920e-01 4.76504475e-01 -1.06898749e+00 3.93012047e-01 7.84302950e-02 4.81082976e-01 -4.01695848e-01 6.57808363e-01 -1.00641119e+00 5.84373251e-02 3.02415073e-01 -2.45871574e-01 -1.99607417e-01 1.82168007e-01 4.96294647e-01 -6.03283793e-02 -1.49332553e-01 9.78935540e-01 1.37815684e-01 -3.79408211e-01 5.55029809e-01 1.94726974e-01 -3.49340774e-03 8.05405974e-01 -3.53144825e-01 8.15543681e-02 -6.53586805e-01 -8.95220757e-01 3.84716922e-03 6.88951552e-01 2.93782502e-01 4.91890132e-01 -1.34793150e+00 -5.08206725e-01 6.66198432e-01 3.29382241e-01 1.42454952e-01 1.01457909e-01 7.78664231e-01 -1.74179971e-01 2.27290645e-01 -1.58640519e-01 -7.53684580e-01 -1.52489984e+00 2.80611455e-01 5.34810245e-01 -3.60722514e-03 -1.23593464e-01 6.78136110e-01 1.34110600e-01 -8.57979953e-01 5.35696507e-01 -1.41472116e-01 -2.06391856e-01 -3.07471361e-02 5.11591673e-01 3.51082124e-02 4.44328964e-01 -1.03706586e+00 -4.47441339e-01 5.32527447e-01 -3.24922614e-02 -2.83211112e-01 1.09135354e+00 -1.52650982e-01 2.02401921e-01 1.24214590e-01 1.28743684e+00 -4.49042022e-02 -1.20747650e+00 -4.44123179e-01 1.92312070e-03 -4.61431146e-01 -4.89657335e-02 -6.13099873e-01 -1.26231492e+00 7.92849839e-01 1.01244009e+00 -2.78511018e-01 1.16172993e+00 -8.47696215e-02 5.01847148e-01 4.49865162e-01 6.29170179e-01 -9.30675268e-01 -1.71210356e-02 2.00352848e-01 8.02734554e-01 -1.55352271e+00 -3.37426551e-02 -5.96714139e-01 -4.28285092e-01 7.51534343e-01 8.17540407e-01 2.70873159e-01 6.74175680e-01 2.69872814e-01 1.84230119e-01 4.77536097e-02 -1.95692435e-01 -2.01039210e-01 4.36888337e-01 8.18079531e-01 5.35734117e-01 -2.95866374e-02 -1.38911083e-01 4.96405929e-01 -3.67760122e-01 1.10480905e-01 7.21906796e-02 9.49453950e-01 6.66912692e-03 -1.47282708e+00 -7.16252804e-01 2.58290678e-01 -3.26343775e-01 2.50808746e-01 -3.55932772e-01 8.13853443e-01 8.52733776e-02 6.45588636e-01 2.49076746e-02 -4.07945484e-01 3.74143183e-01 3.46264362e-01 8.56574476e-01 -5.33104479e-01 -1.74260572e-01 2.97647044e-02 -4.58443798e-02 -3.07148933e-01 -4.91802663e-01 -7.66551256e-01 -1.07532549e+00 -2.30810076e-01 -4.39627141e-01 -1.34704098e-01 8.52317452e-01 9.59749520e-01 2.74490178e-01 2.88998112e-02 6.79849446e-01 -1.18480814e+00 -7.59322941e-01 -1.19215596e+00 -6.82624519e-01 7.33663678e-01 3.70193720e-01 -9.71992731e-01 -2.93247402e-01 2.10014001e-01]	[13.41518497467041, 0.1368931084871292]
99506bc4-93c2-4e8c-bad8-9d94b92895cd	an-inter-lingual-reference-approach-for-multi	1309.6650	null	http://arxiv.org/abs/1309.6650v1	http://arxiv.org/pdf/1309.6650v1.pdf	An Inter-lingual Reference Approach For Multi-Lingual Ontology Matching	Ontologies are considered as the backbone of the Semantic Web. With the rising success of the Semantic Web, the number of participating communities from different countries is constantly increasing. The growing number of ontologies available in different natural languages leads to an interoperability problem. In this paper, we discuss several approaches for ontology matching; examine similarities and differences, identify weaknesses, and compare the existing automated approaches with the manual approaches for integrating multilingual ontologies. In addition to that, we propose a new architecture for a multilingual ontology matching service. As a case study we used an example of two multilingual enterprise ontologies - the university ontology of Freie Universitaet Berlin and the ontology for Fayoum University in Egypt.	['Haytham Al-Feel', 'Ralph Schafermeier', 'Adrian Paschke']	2013-09-25	null	null	null	null	['ontology-matching']	['knowledge-base']	[-5.40371597e-01 2.07182735e-01 -6.77351877e-02 -1.46540642e-01 -2.97979653e-01 -6.10616803e-01 4.94483471e-01 5.06024063e-01 -4.24831390e-01 7.90327549e-01 2.74252981e-01 -3.24817419e-01 -5.35905063e-01 -9.77674544e-01 -1.07081339e-01 5.83667494e-02 1.89478114e-01 8.11475694e-01 5.21812379e-01 -9.50086355e-01 2.06933081e-01 4.88619387e-01 -1.85406148e+00 2.88162977e-01 1.24194491e+00 6.82629108e-01 2.55325556e-01 4.69507948e-02 -7.68279791e-01 6.13510549e-01 -4.55671608e-01 -5.49834192e-01 1.98936760e-01 -1.40593424e-01 -1.49042082e+00 -1.14961661e-01 2.52321899e-01 2.37903461e-01 -1.50902972e-01 1.45031583e+00 3.85459155e-01 -7.95203373e-02 2.01179847e-01 -1.57934117e+00 -7.45822132e-01 4.77999419e-01 2.50334948e-01 -9.96555164e-02 8.64927351e-01 -7.45580018e-01 9.33963954e-01 -3.61747861e-01 1.17691338e+00 1.39857578e+00 5.63339531e-01 1.30492017e-01 -4.88374054e-01 -5.63335538e-01 -2.57888407e-01 5.14182031e-01 -1.58909154e+00 -2.32710004e-01 1.84713557e-01 -5.10981977e-01 8.27232838e-01 1.18371680e-01 5.27156889e-01 2.40102649e-01 1.07950941e-01 -1.37814790e-01 9.97252345e-01 -1.01856959e+00 -8.27066079e-02 6.33880377e-01 1.41872495e-01 6.74809754e-01 7.96763182e-01 -4.39864129e-01 -9.13790613e-03 -3.82209301e-01 4.27662939e-01 -3.91364209e-02 2.44786851e-02 -4.51610118e-01 -6.67554080e-01 6.39274120e-01 -4.44178618e-02 1.10280466e+00 -5.70030212e-02 -4.37867701e-01 3.59302342e-01 5.76454103e-01 8.02860111e-02 2.76746064e-01 -4.53877777e-01 1.31861299e-01 -2.73662895e-01 4.35241967e-01 1.18503582e+00 1.11153758e+00 8.51877928e-01 -2.19897449e-01 9.71889734e-01 9.65823472e-01 7.18886495e-01 2.28177935e-01 6.72449529e-01 -1.03762603e+00 1.78806186e-01 1.26665998e+00 3.67226779e-01 -1.03024292e+00 -1.86573133e-01 7.18802363e-02 1.89255863e-01 2.04030141e-01 4.08350587e-01 1.25540137e-01 -3.77623826e-01 1.18946278e+00 4.90778714e-01 -5.23935318e-01 6.98938072e-01 4.36555475e-01 8.69125664e-01 2.00601548e-01 2.59706527e-01 2.28384033e-01 1.74009109e+00 -7.30075717e-01 -1.16487873e+00 1.55567795e-01 7.29342818e-01 -1.25856566e+00 4.69041586e-01 5.41667221e-03 -8.09279978e-01 -1.30382106e-01 -9.57781196e-01 -8.15753117e-02 -1.35181713e+00 -5.83109915e-01 5.81501424e-01 7.00754285e-01 -1.11049569e+00 4.59862560e-01 -1.83884323e-01 -1.38516736e+00 -8.01931322e-02 2.20041454e-01 -7.99485028e-01 -2.03700230e-01 -1.77112567e+00 1.42552710e+00 1.05066323e+00 -6.04408681e-01 -1.39616430e-02 -1.79090083e-01 -7.17386305e-01 5.83491884e-02 1.55575603e-01 -3.22745413e-01 8.82527888e-01 -1.02914560e+00 -9.59141731e-01 1.09392405e+00 8.17926005e-02 -1.82063669e-01 2.42315084e-01 1.28282130e-01 -1.55932522e+00 6.34683222e-02 4.89142656e-01 2.08133161e-01 -4.12064523e-01 -1.24431872e+00 -1.39915776e+00 -4.00909632e-01 5.06909549e-01 7.49918073e-03 -3.13460290e-01 7.92822659e-01 -2.11719424e-01 -2.43708178e-01 1.66717604e-01 -5.94833672e-01 4.92094606e-02 -3.03225011e-01 6.14962220e-01 -2.83239394e-01 7.74640501e-01 -8.39055717e-01 1.45866895e+00 -1.85043573e+00 -2.23118827e-01 2.80146062e-01 -1.18430063e-01 -2.05274541e-02 1.68506950e-01 9.34455574e-01 -2.21553016e-02 4.10238445e-01 -5.69482781e-02 7.00284302e-01 3.54089081e-01 6.12703323e-01 4.22239043e-02 -2.45488733e-02 -4.81679618e-01 1.99136421e-01 -1.21046615e+00 -8.94557953e-01 -6.74451143e-03 4.47391003e-01 -2.02168450e-01 -4.23887491e-01 6.76131546e-02 1.02184162e-01 -5.22995770e-01 1.04712105e+00 3.46275300e-01 -9.00569782e-02 9.16683853e-01 5.46322996e-03 -5.09665012e-01 1.49076387e-01 -1.59879017e+00 1.75590074e+00 -4.82500494e-01 4.46281403e-01 4.56741042e-02 -6.87164485e-01 1.02132380e+00 1.34370041e+00 7.79113173e-01 -6.40826046e-01 3.24709624e-01 1.10941243e+00 7.75654316e-02 -7.85347044e-01 5.39863110e-01 -1.58439040e-01 -1.66654125e-01 1.18152536e-01 2.50253320e-01 9.14363489e-02 8.49626839e-01 -3.80010046e-02 5.83256900e-01 4.89612132e-01 9.40811396e-01 -7.01847076e-01 8.76087368e-01 2.78019220e-01 5.25571704e-01 8.68013501e-02 -2.19814494e-01 -1.29597932e-01 1.40575707e-01 -7.83826292e-01 -1.05550623e+00 -7.11374164e-01 -6.13612533e-01 6.77046657e-01 2.25304335e-01 -7.35273063e-01 -7.37236977e-01 -4.23282474e-01 -7.69247934e-02 4.02160108e-01 2.36996226e-02 5.31521738e-01 -2.57870674e-01 -3.19055110e-01 5.54394543e-01 -2.07704827e-01 5.68695486e-01 -9.56826091e-01 -5.00927567e-01 5.47797859e-01 -3.82582217e-01 -1.52656174e+00 3.23694974e-01 -3.32550049e-01 -6.32082164e-01 -1.30884790e+00 -1.00598067e-01 -9.64541376e-01 3.54738325e-01 -8.45028646e-03 1.04276097e+00 3.39727700e-01 -1.98280364e-01 4.52774525e-01 -6.18652999e-01 -7.16968596e-01 -7.50837922e-01 1.66513503e-01 1.16911851e-01 -2.90672094e-01 9.63029385e-01 -5.78131855e-01 -2.36595366e-02 3.87720525e-01 -1.31643939e+00 -4.74513322e-01 1.12537947e-02 7.47850090e-02 -7.42978929e-03 3.69759023e-01 8.45844686e-01 -7.74513602e-01 5.26854515e-01 -8.16932976e-01 -7.20428705e-01 6.95956588e-01 -6.96419895e-01 -1.37203798e-01 2.00306535e-01 1.65851966e-01 -1.06812871e+00 -3.87003243e-01 -2.12777648e-02 3.69820118e-01 -3.55858982e-01 6.70658827e-01 -5.57042897e-01 -3.31908107e-01 3.60928744e-01 -3.76672506e-01 -1.38450414e-01 -6.59124374e-01 1.02386825e-01 1.08837247e+00 1.47091910e-01 -8.81671488e-01 6.20477974e-01 3.95067513e-01 -1.41409338e-01 -7.37138331e-01 -3.87258500e-01 -4.65853155e-01 -6.35080457e-01 -5.33158183e-01 9.80274498e-01 -7.98768938e-01 -4.99304712e-01 -9.11666453e-02 -1.20567143e+00 4.03907418e-01 -2.06559688e-01 5.27377486e-01 -2.98455328e-01 4.72603381e-01 -2.93729842e-01 -6.31189823e-01 -4.77172956e-02 -1.10772383e+00 4.11285847e-01 2.98124641e-01 -4.97504324e-01 -1.34697688e+00 1.76670879e-01 5.78087330e-01 4.69585449e-01 3.87670815e-01 1.06850028e+00 -9.91682887e-01 -1.15145124e-01 -4.93155956e-01 -1.56334013e-01 1.59253746e-01 4.86007690e-01 -1.57340869e-01 -4.64607775e-01 -1.15500174e-01 -4.11092281e-01 1.25653416e-01 -4.90581214e-01 -6.42784417e-01 -6.91867026e-04 -8.80668387e-02 -3.83249372e-01 -2.58041739e-01 2.09962559e+00 7.87070036e-01 7.56575048e-01 1.36711848e+00 8.15304220e-02 9.95093405e-01 7.96870708e-01 2.70487130e-01 6.55560136e-01 8.48328590e-01 8.70140418e-02 3.22376698e-01 1.73693344e-01 1.00363687e-01 -9.48958695e-02 1.31439304e+00 -6.00703657e-01 7.97023103e-02 -1.41878855e+00 6.14438415e-01 -2.02613449e+00 -9.71022904e-01 -1.12561747e-01 2.19406772e+00 6.77033901e-01 -3.53060275e-01 -8.51167813e-02 -5.77831753e-02 8.13948154e-01 -3.99121821e-01 4.91957635e-01 -3.46496403e-01 -2.57661343e-01 3.29125494e-01 3.79196048e-01 8.20330024e-01 -7.39408374e-01 1.03887880e+00 6.17806673e+00 3.49454522e-01 -7.09661782e-01 5.98333180e-01 -5.60526967e-01 5.00399351e-01 -3.05667460e-01 6.12993360e-01 -7.93187022e-01 3.69326234e-01 1.06862128e+00 -6.93342090e-01 4.53906924e-01 6.56698883e-01 -6.05942681e-02 2.03694791e-01 -4.28064376e-01 5.26238143e-01 9.72871855e-02 -1.17532647e+00 2.86895126e-01 2.81774044e-01 7.87976861e-01 2.63927821e-02 -9.00643408e-01 9.85307433e-03 6.59179986e-01 -6.01082027e-01 7.23520815e-01 5.60020387e-01 3.56485337e-01 -7.26393223e-01 1.06969774e+00 -2.25203469e-01 -1.48983502e+00 -3.38555165e-02 -3.41201305e-01 3.97971692e-03 3.61191928e-01 7.00389817e-02 -1.24680527e-01 1.35322857e+00 9.87012148e-01 1.72501862e-01 -1.58119708e-01 1.22189569e+00 -1.21260382e-01 -3.62795413e-01 -1.14902712e-01 2.73297310e-01 1.47420138e-01 -7.12342799e-01 4.27018613e-01 9.11235213e-01 7.16383934e-01 -1.34183958e-01 2.51906425e-01 7.81937838e-02 5.95109835e-02 8.31089973e-01 -7.00907826e-01 -1.28601879e-01 7.62443841e-01 9.55220520e-01 -4.64374989e-01 -5.19689381e-01 -9.97087002e-01 6.11309350e-01 -4.52680700e-02 2.57895082e-01 -5.81481636e-01 -8.03399026e-01 8.51542592e-01 2.18698755e-01 -2.87711442e-01 3.72717716e-02 4.71066952e-01 -1.19511080e+00 -1.90051526e-01 -1.31406271e+00 7.71299005e-01 -6.99444950e-01 -1.06984830e+00 7.64555097e-01 2.69786090e-01 -1.26080513e+00 -1.36261387e-02 -6.92812085e-01 1.19293049e-01 9.18061376e-01 -1.73818409e+00 -9.98428047e-01 -2.23874897e-01 3.16275686e-01 1.11504696e-01 -3.27292085e-01 1.35094047e+00 1.07368529e+00 -6.12884127e-02 -2.30966687e-01 2.93576717e-01 5.51033914e-02 8.42750609e-01 -9.89224613e-01 -1.82865784e-01 5.30606091e-01 -3.30718994e-01 7.72223055e-01 7.47640073e-01 -7.33885646e-01 -7.74192512e-01 -4.81713474e-01 1.79370451e+00 -2.10832119e-01 1.22955465e+00 2.60017306e-01 -8.44900548e-01 1.00450122e+00 7.59622574e-01 -3.72192502e-01 1.06593394e+00 -2.60141999e-01 -3.28869939e-01 -1.46268129e-01 -1.36583865e+00 7.19839513e-01 8.77572596e-01 -5.60788095e-01 -9.14232612e-01 4.90031242e-01 3.38600427e-01 -3.55505981e-02 -1.72392666e+00 2.66942978e-01 9.33897495e-01 -7.66980410e-01 8.10353220e-01 -7.36533582e-01 -1.22528672e-01 -7.73096919e-01 -6.14886165e-01 -8.02894294e-01 -8.39728266e-02 -3.95548075e-01 6.24481857e-01 1.39015067e+00 2.21112832e-01 -1.36599147e+00 1.89351231e-01 5.27190804e-01 5.39686196e-02 1.54971182e-01 -9.63499904e-01 -1.00882936e+00 9.82156470e-02 -3.61866169e-02 1.10239255e+00 1.67922819e+00 6.19366348e-01 2.24860273e-02 1.09116144e-01 3.78511131e-01 5.27666450e-01 -2.32541084e-01 4.52428490e-01 -2.11539507e+00 3.07886124e-01 -4.83550102e-01 -9.30186033e-01 1.20691635e-01 8.49717334e-02 -9.38161433e-01 -6.34738088e-01 -1.98511589e+00 -1.94979563e-01 -3.70679945e-01 -2.42937177e-01 4.71521586e-01 3.91944021e-01 -8.90178308e-02 1.86681435e-01 3.63971740e-01 -3.46866250e-01 -2.19253600e-01 8.29372227e-01 2.47017562e-01 2.90237397e-01 -8.10275912e-01 -5.56275487e-01 8.81665170e-01 8.51090848e-01 -7.62108743e-01 -1.53744549e-01 -2.92662293e-01 5.75671017e-01 -1.80634305e-01 -3.28973204e-01 -1.24558842e+00 1.70335248e-01 -2.36563936e-01 -4.27428603e-01 4.30069715e-02 -9.73431468e-02 -1.61357450e+00 8.84967864e-01 4.69525933e-01 2.89373308e-01 3.98627371e-01 1.41475409e-01 -6.34625629e-02 -7.73025334e-01 -9.99292135e-01 7.03742683e-01 -5.98786652e-01 -1.06821346e+00 -1.18631244e-01 -6.34358823e-01 -1.66657031e-01 1.14659083e+00 -4.21818197e-01 -3.92371833e-01 1.13881946e-01 -8.44963133e-01 1.71586365e-01 1.01043522e+00 6.90269887e-01 -1.05702989e-01 -1.46615148e+00 -3.94750059e-01 -3.25227022e-01 5.02008557e-01 -7.23914087e-01 -1.58389844e-02 4.60382938e-01 -1.08047092e+00 7.25082397e-01 -8.32853794e-01 2.10079327e-01 -1.23025525e+00 2.72534251e-01 5.33509254e-01 -3.11970294e-01 -3.06995511e-01 -2.65762269e-01 -3.27792943e-01 -8.98413718e-01 -6.12299554e-02 3.92396629e-01 -7.71717250e-01 3.03241223e-01 3.82716864e-01 5.29730380e-01 1.35125190e-01 -1.01972449e+00 -3.69174242e-01 6.67710066e-01 3.91875505e-01 -3.08282077e-01 1.08847845e+00 -3.01651061e-01 -9.41492915e-01 5.77204049e-01 7.72171617e-01 1.54658273e-01 1.22649632e-01 -1.97748661e-01 8.61439884e-01 -5.60652196e-01 -3.00645649e-01 -4.61410671e-01 -6.58474445e-01 1.97573230e-01 8.48673880e-01 6.90859258e-01 6.47421956e-01 -4.77072671e-02 5.02782822e-01 4.04675812e-01 9.22867775e-01 -1.47707319e+00 -7.49179840e-01 6.06523871e-01 5.94608247e-01 -7.97895074e-01 8.14264566e-02 -7.00549722e-01 -2.32362926e-01 1.56256628e+00 3.02056968e-01 3.65028828e-01 6.97633564e-01 1.55761212e-01 6.26324236e-01 -5.05611598e-01 -1.58992574e-01 -4.95719969e-01 -8.37513283e-02 6.21837318e-01 9.05965686e-01 -2.27675587e-01 -1.10430026e+00 2.09720477e-01 -1.09561324e-01 3.32094401e-01 5.40804386e-01 1.56696832e+00 -7.31731296e-01 -1.91703892e+00 -6.77594662e-01 -9.85599458e-02 -9.00520980e-01 3.01155802e-02 -1.97291270e-01 1.34774804e+00 5.49970806e-01 9.15610254e-01 2.49863826e-02 2.01086998e-01 6.81953609e-01 6.52693808e-01 3.54778737e-01 -3.93438101e-01 -6.31687939e-01 -2.05711439e-01 6.37398243e-01 -1.24572620e-01 -1.01036406e+00 -5.72855949e-01 -1.42015457e+00 -3.13376755e-01 -2.56571501e-01 8.70440543e-01 8.95147204e-01 1.05692220e+00 2.77179897e-01 3.70483786e-01 -6.54288232e-02 -5.83923832e-02 9.78488475e-02 -6.99198425e-01 -7.49066055e-01 5.64518273e-01 -5.09536743e-01 -8.05835605e-01 -1.85475349e-01 2.94918329e-01]	[9.182230949401855, 8.135478019714355]
4d0a23eb-c9f6-430a-880d-6ef76106eaad	teddi-sample-text-data-diversity-sample-for	null	null	https://aclanthology.org/2022.lrec-1.123	https://aclanthology.org/2022.lrec-1.123.pdf	TeDDi Sample: Text Data Diversity Sample for Language Comparison and Multilingual NLP	We present the TeDDi sample, a diversity sample of text data for language comparison and multilingual Natural Language Processing. The TeDDi sample currently features 89 languages based on the typological diversity sample in the World Atlas of Language Structures. It consists of more than 20k texts and is accompanied by open-source corpus processing tools. The aim of TeDDi is to facilitate text-based quantitative analysis of linguistic diversity. We describe in detail the TeDDi sample, how it was created, data availability, and its added value through for NLP and linguistic research.	['Tanja Samardzic', 'Olga Pelloni', 'Ximena Gutierrez-Vasques', 'Christian Bentz', 'Steven Moran']	null	null	null	null	lrec-2022-6	['multilingual-nlp']	['natural-language-processing']	[-5.89001298e-01 -3.77546356e-04 -6.11163676e-01 -1.63008764e-01 -9.46200728e-01 -8.11123013e-01 1.01485252e+00 6.76728487e-01 -9.84207273e-01 7.97594488e-01 1.16910803e+00 -3.95764381e-01 -1.99516192e-01 -3.89266223e-01 2.41724011e-02 3.66402492e-02 -1.28732964e-01 9.13601220e-01 -2.02168822e-01 -5.78544557e-01 4.35915053e-01 2.04071656e-01 -1.33610153e+00 3.62939686e-01 1.12478185e+00 4.33484674e-01 2.18728498e-01 3.74773830e-01 -7.44333863e-01 6.90940499e-01 -6.26942456e-01 -4.73242372e-01 -6.47483254e-03 -2.12823823e-01 -1.13597655e+00 -3.92727613e-01 7.70772457e-01 2.74136495e-02 -1.27880558e-01 8.38006616e-01 6.71457946e-01 -1.33252814e-01 7.11457253e-01 -9.20830369e-01 -7.29483902e-01 1.21703982e+00 -2.20495641e-01 8.10173213e-01 8.64540756e-01 -8.45836252e-02 1.21990764e+00 -1.03292763e+00 1.53040814e+00 1.68302989e+00 6.04572952e-01 2.71876156e-01 -1.26226330e+00 -5.95192134e-01 -1.82736591e-01 -4.06317413e-02 -1.43779790e+00 -9.26252961e-01 6.31668925e-01 -8.27014804e-01 1.38213539e+00 -9.38368365e-02 6.39551878e-01 9.85557497e-01 2.43669618e-02 6.45755172e-01 1.18488896e+00 -8.76333237e-01 -2.14656472e-01 2.21009403e-01 2.70586252e-01 2.68673927e-01 4.18070167e-01 -1.60391137e-01 -8.55077267e-01 -3.69168550e-01 2.06131876e-01 -7.43093729e-01 -1.11986790e-02 1.65399477e-01 -1.56072021e+00 7.69658744e-01 -2.48353794e-01 1.11582732e+00 5.41489944e-03 -7.22257495e-01 1.15275037e+00 7.80680835e-01 8.53279233e-01 5.08149922e-01 -4.61034596e-01 -3.88332427e-01 -1.01130092e+00 4.21710610e-01 8.74273658e-01 1.04940474e+00 2.83382386e-01 -4.06366885e-02 1.42818600e-01 1.54038072e+00 2.96306312e-01 7.93433070e-01 6.96153641e-01 -7.80380607e-01 9.16974783e-01 6.93235099e-01 -2.11593270e-01 -1.03398812e+00 -6.55693531e-01 3.77088696e-01 -3.60299468e-01 -3.66362154e-01 5.24411678e-01 1.06326334e-01 -2.38191247e-01 1.59363234e+00 2.36334845e-01 -1.27742290e+00 7.40940869e-02 2.71668285e-01 1.26091909e+00 5.23367465e-01 1.53804272e-01 -3.51840824e-01 1.39043331e+00 -4.03149575e-01 -7.72759616e-01 -5.00520505e-02 1.10605299e+00 -1.14294577e+00 1.48667884e+00 4.09635156e-01 -1.35618496e+00 -1.98099047e-01 -7.43429959e-01 -6.87189519e-01 -7.85267770e-01 -6.18199222e-02 3.86384726e-01 6.39050841e-01 -1.16174829e+00 -2.11044922e-01 -6.05542719e-01 -8.80048096e-01 2.08136648e-01 -2.98577338e-01 -6.49366319e-01 2.86474023e-02 -1.26119077e+00 1.26481700e+00 6.88576162e-01 -5.70074856e-01 -3.93628553e-02 -6.08210862e-01 -1.15267575e+00 -6.19075119e-01 1.82829008e-01 3.60857770e-02 1.07964659e+00 -6.92052007e-01 -1.16357124e+00 1.84260976e+00 -3.68302912e-02 -1.08399510e-01 2.38329530e-01 6.49464130e-02 -9.62823391e-01 1.00939505e-01 5.56025326e-01 5.21458745e-01 -6.51616454e-02 -7.10659504e-01 -7.65703022e-01 -3.87499839e-01 -4.31590766e-01 9.74514708e-02 -5.00414550e-01 9.64418888e-01 -1.72741011e-01 -1.08824360e+00 -2.76823789e-01 -6.16512775e-01 1.67495951e-01 -2.37147748e-01 -1.02020532e-01 -4.91857827e-01 1.84873357e-01 -1.19172549e+00 1.76212299e+00 -2.00182629e+00 -1.65542454e-01 6.46428168e-02 5.17817795e-01 1.75592601e-02 -1.14684619e-01 1.10849321e+00 2.87637919e-01 5.37981033e-01 -1.27766013e-01 -2.80641496e-01 3.34891051e-01 2.23740563e-01 -1.67326942e-01 6.06482565e-01 -9.14442837e-02 7.48854756e-01 -1.11269867e+00 -9.08372700e-01 2.19239220e-01 -1.41361337e-02 -5.40159941e-01 -4.26050365e-01 -6.98215365e-02 2.79271722e-01 -1.36092469e-01 7.48041451e-01 4.45155323e-01 6.22006059e-01 3.76828551e-01 1.54572070e-01 -1.04826772e+00 1.09907341e+00 -6.90994680e-01 1.77331161e+00 -5.40220797e-01 1.18270898e+00 2.31397510e-01 -4.74067509e-01 8.33768427e-01 1.03212610e-01 7.75195062e-02 -9.24484849e-01 1.31895021e-01 7.39370286e-01 2.78212786e-01 -2.94045568e-01 1.09885550e+00 5.54660410e-02 -8.15246046e-01 5.99485636e-01 2.21563593e-01 -3.82498354e-01 1.10266471e+00 2.24577501e-01 6.64912939e-01 -3.06803733e-01 1.05728626e+00 -1.24103379e+00 7.95310974e-01 5.26751041e-01 6.15503490e-01 7.01528639e-02 -2.74179101e-01 -6.63457066e-02 4.66328919e-01 -3.64231676e-01 -1.52047050e+00 -1.08631003e+00 -8.30496728e-01 1.10996783e+00 -5.84134638e-01 -7.23553061e-01 -3.32095861e-01 -2.31193919e-02 1.00898422e-01 7.78479517e-01 -5.34612119e-01 4.48682994e-01 -7.29164839e-01 -3.97670835e-01 1.06337094e+00 5.34890816e-02 2.11431324e-01 -1.27088666e+00 -2.28456616e-01 2.19762605e-02 -3.79741818e-01 -9.12697315e-01 -5.98980665e-01 -2.24681184e-01 -2.86750346e-01 -9.99945223e-01 -5.13513863e-01 -1.22805703e+00 1.37368098e-01 -1.74873590e-01 1.57760918e+00 -1.20634846e-01 -2.72713423e-01 2.24057019e-01 -4.61751699e-01 -4.03947681e-01 -1.13976002e+00 4.68074590e-01 3.57989341e-01 -1.02181280e+00 7.68843532e-01 -1.35078266e-01 2.86974400e-01 -1.80717066e-01 -8.74911964e-01 -3.19808483e-01 -1.26368836e-01 7.37297475e-01 4.43238676e-01 -2.53595978e-01 6.61284447e-01 -8.70259225e-01 1.01377559e+00 -6.22738600e-01 -5.48431218e-01 2.55663306e-01 -5.00774682e-01 -1.43091813e-01 6.59565747e-01 -6.76758438e-02 -1.01966417e+00 -7.11915433e-01 -4.21020955e-01 4.81135488e-01 -6.29549623e-02 9.49951828e-01 -1.05281614e-01 2.80626595e-01 6.69287205e-01 -1.92734376e-01 -1.01961508e-01 -8.25435162e-01 4.32233483e-01 1.20004678e+00 7.22977340e-01 -7.99442947e-01 3.39946926e-01 1.09439299e-01 -6.38099551e-01 -1.37686098e+00 -2.84124166e-01 -4.92875844e-01 -1.02890158e+00 5.27127134e-03 5.62156796e-01 -9.35367763e-01 -3.45404774e-01 5.69044292e-01 -8.09936404e-01 -4.51920003e-01 -3.17840427e-01 4.13625866e-01 -3.15016478e-01 3.17648113e-01 -6.86096191e-01 -5.84106803e-01 -4.99186277e-01 -6.72381938e-01 8.60760629e-01 -4.87230867e-01 -7.94194043e-01 -1.69446099e+00 6.88055098e-01 -1.06756233e-01 1.65960208e-01 3.21879923e-01 1.28552437e+00 -8.19127977e-01 7.38431811e-01 6.06516488e-02 1.97143644e-01 -2.45612245e-02 1.38343245e-01 4.69364166e-01 -3.56449962e-01 -3.38241071e-01 -3.00924361e-01 -6.88099802e-01 5.21516204e-01 1.78762764e-01 2.75042027e-01 -4.94177490e-01 -1.02604600e-02 9.38299075e-02 1.33378792e+00 -2.99633872e-02 2.88079351e-01 8.49909544e-01 4.60775048e-01 1.13845658e+00 4.20929879e-01 5.84492505e-01 9.88967299e-01 4.94781017e-01 -6.41730130e-01 1.53170899e-01 -2.96752274e-01 -3.26856166e-01 4.48982447e-01 1.96808720e+00 5.57948053e-01 -1.53461114e-01 -1.86396241e+00 1.10800052e+00 -1.30056262e+00 -8.85329902e-01 -1.90028891e-01 2.09890485e+00 1.20246565e+00 4.31326143e-02 6.99540675e-01 1.34405047e-01 5.79994798e-01 3.22289020e-01 -1.00266263e-01 -1.00530291e+00 -7.55131006e-01 2.89652199e-02 2.74040997e-01 8.13700974e-01 -5.77036083e-01 1.23157775e+00 8.14045811e+00 1.00753438e+00 -7.62345433e-01 7.85484836e-02 1.94874778e-01 -2.20091328e-01 -7.85309136e-01 -2.19830632e-01 -9.24411058e-01 4.05739367e-01 1.10714376e+00 -9.65579629e-01 3.30559522e-01 2.95513242e-01 3.65979224e-01 -3.05869788e-01 -8.25587749e-01 6.67600453e-01 2.95974493e-01 -1.18554068e+00 2.00719342e-01 8.42180029e-02 5.20075560e-01 5.98461986e-01 -1.33819550e-01 2.61309773e-01 5.24621844e-01 -7.95377254e-01 1.26146996e+00 1.36737451e-01 1.48470879e+00 -6.78612709e-01 4.24345970e-01 3.29521239e-01 -1.13304234e+00 2.28497803e-01 -3.34695786e-01 -2.24198371e-01 2.64857441e-01 6.36978447e-01 -3.61211449e-01 2.76357114e-01 7.09934175e-01 8.30321312e-01 -6.56296790e-01 4.89237368e-01 4.17267233e-02 7.92942822e-01 -3.33795607e-01 -1.55747578e-01 1.65765077e-01 -1.66294172e-01 8.88331234e-01 1.70820534e+00 -9.19393897e-02 -3.33458692e-01 4.02534634e-01 5.42346835e-01 -1.26069142e-02 7.61792302e-01 -7.62921631e-01 -6.44207299e-01 1.10159302e+00 9.41025972e-01 -7.24253178e-01 -3.65535289e-01 -5.15745759e-01 2.66465217e-01 8.75646412e-01 -8.93275514e-02 8.27318206e-02 -6.21782839e-01 4.54931200e-01 7.32317343e-02 -1.54612139e-01 -6.94683492e-01 -4.07555312e-01 -1.08260906e+00 -1.09915964e-01 -1.10835183e+00 6.84294164e-01 -2.53359407e-01 -1.77585781e+00 7.56638110e-01 4.12071288e-01 -8.43468010e-01 -6.60784841e-01 -8.25105071e-01 1.99242439e-02 9.56959605e-01 -8.22796047e-01 -1.00501788e+00 2.98639745e-01 4.33240175e-01 5.24308324e-01 -5.96825540e-01 8.14434528e-01 4.55621809e-01 -4.66386318e-01 8.15361559e-01 4.66496289e-01 1.38248354e-01 8.98558378e-01 -1.14867222e+00 8.28407645e-01 4.60981458e-01 -1.38775155e-01 6.70691431e-01 5.79536438e-01 -9.66171205e-01 -8.77436161e-01 -6.69845402e-01 1.90152276e+00 -5.62084615e-01 1.49897349e+00 -6.22775435e-01 -5.77649534e-01 6.45290852e-01 5.50289392e-01 -6.80608451e-01 9.46989655e-01 3.11286181e-01 -2.80650765e-01 3.10923070e-01 -1.33057642e+00 8.52274358e-01 1.33335352e+00 -9.22225475e-01 -1.19743288e+00 2.50026643e-01 5.00330806e-01 -2.70861536e-01 -1.45581293e+00 -1.05455399e-01 6.66754544e-01 -5.41203558e-01 3.77912492e-01 -2.62273699e-01 4.78048176e-01 1.12796739e-01 -1.61512524e-01 -1.38839960e+00 -4.50807631e-01 -7.23200679e-01 5.70406377e-01 1.71883476e+00 5.77974081e-01 -7.15354323e-01 -7.59819746e-02 3.20897311e-01 -3.93438488e-01 -1.99337408e-01 -1.17280853e+00 -8.79362881e-01 1.01211214e+00 -5.34736395e-01 6.41824126e-01 1.35448897e+00 7.75944114e-01 3.06346983e-01 2.38741547e-01 -7.96346724e-01 2.81842351e-01 -2.89142787e-01 6.57940209e-01 -1.23614371e+00 2.93334275e-01 -1.00428903e+00 -3.55070531e-01 -4.09631908e-01 3.99442464e-01 -1.33960426e+00 -2.50977039e-01 -1.48814893e+00 1.33658469e-01 -3.48144382e-01 4.70363349e-01 4.67829943e-01 1.80288970e-01 1.40252188e-01 1.02851845e-01 5.69173276e-01 -3.42754304e-01 3.89534235e-01 7.83598483e-01 3.80612873e-02 -5.25760531e-01 -8.78805637e-01 -6.63593411e-01 6.48094893e-01 7.64168680e-01 -4.13377464e-01 -7.50989839e-02 -6.41943455e-01 5.59557378e-01 -4.97966945e-01 -3.92559618e-01 -6.03039503e-01 -1.26304016e-01 -3.82271260e-01 -1.69760287e-01 -7.50232577e-01 -3.97602320e-01 -2.08694831e-01 -2.54328717e-02 3.96872401e-01 -4.44276601e-01 6.95473850e-01 5.40390909e-01 -4.03187782e-01 -4.26437110e-01 -1.33718327e-01 5.10819197e-01 -1.93374857e-01 -6.23665571e-01 -1.31623168e-02 -9.95555699e-01 9.89217460e-01 4.56726134e-01 -2.73721665e-01 -6.95163250e-01 2.04134490e-02 -2.66919807e-02 4.53271538e-01 9.45271850e-01 5.18526077e-01 -1.16050348e-01 -1.56963003e+00 -1.23484337e+00 1.82914305e-02 6.52713895e-01 -4.15168405e-01 -2.89956391e-01 6.34877026e-01 -7.42376149e-01 7.59794235e-01 -4.47072148e-01 1.11096308e-01 -7.91353762e-01 5.42497039e-01 -1.51346296e-01 -3.40018451e-01 -6.58419192e-01 3.47529799e-01 -2.13064149e-01 -8.09604228e-01 -3.98555547e-02 -2.42472291e-01 -5.61832845e-01 3.02406102e-01 5.88734925e-01 8.03436160e-01 -6.46104962e-02 -1.41951048e+00 -5.58847666e-01 1.46892011e-01 -1.18559137e-01 -7.60059595e-01 1.07620573e+00 -7.17177153e-01 -6.60996974e-01 1.45977032e+00 1.24527395e+00 8.29310060e-01 2.31497195e-02 -4.00865853e-01 7.18131483e-01 -3.16136181e-01 -9.78536811e-03 -8.73892307e-01 -2.98931569e-01 4.16206628e-01 -4.89584394e-02 2.75818080e-01 7.69227386e-01 -1.41359698e-02 9.26459610e-01 1.78631306e-01 2.32649133e-01 -1.69833243e+00 -6.95373952e-01 1.14333594e+00 1.19860709e+00 -8.31326306e-01 4.82924469e-02 -2.31671661e-01 -4.68023449e-01 8.99505734e-01 2.15074465e-01 6.98218569e-02 7.42025256e-01 5.20973086e-01 3.60548764e-01 -3.93747926e-01 -5.15562177e-01 -7.48521984e-02 5.47582090e-01 7.88876951e-01 1.03100717e+00 1.20687269e-01 -1.36166823e+00 6.57780468e-01 -1.16924334e+00 -4.35878724e-01 2.07573697e-01 6.84867501e-01 -3.97893697e-01 -1.29840171e+00 -3.84323418e-01 5.08067667e-01 -3.95026445e-01 -5.78478813e-01 -8.16431642e-01 1.16672671e+00 6.21827506e-02 9.63340223e-01 4.07824129e-01 -1.19645886e-01 1.02719665e-01 -7.30299503e-02 4.90151614e-01 -5.43885410e-01 -7.47678518e-01 -1.16111115e-01 9.36426461e-01 -1.64229915e-01 -6.04751468e-01 -1.19572306e+00 -9.92387831e-01 -8.45889747e-01 6.44745082e-02 1.36051208e-01 4.29456562e-01 8.75421584e-01 1.11306489e-01 -1.95064574e-01 3.69153827e-01 -7.27444291e-01 7.23555237e-02 -1.27786922e+00 -8.31376493e-01 4.09489088e-02 -5.81552759e-02 -5.73229074e-01 -4.24796015e-01 -2.46562824e-01]	[10.384483337402344, 10.09496784210205]
ad76465f-b4cf-4dc7-9794-b6f20fbf62c5	3d-reconstruction-of-spherical-images-based	2306.12770	null	https://arxiv.org/abs/2306.12770v2	https://arxiv.org/pdf/2306.12770v2.pdf	3D Reconstruction of Spherical Images based on Incremental Structure from Motion	3D reconstruction plays an increasingly important role in modern photogrammetric systems. Conventional satellite or aerial-based remote sensing (RS) platforms can provide the necessary data sources for the 3D reconstruction of large-scale landforms and cities. Even with low-altitude UAVs (Unmanned Aerial Vehicles), 3D reconstruction in complicated situations, such as urban canyons and indoor scenes, is challenging due to the frequent tracking failures between camera frames and high data collection costs. Recently, spherical images have been extensively exploited due to the capability of recording surrounding environments from one camera exposure. Classical 3D reconstruction pipelines, however, cannot be used for spherical images. Besides, there exist few software packages for 3D reconstruction of spherical images. Based on the imaging geometry of spherical cameras, this study investigates the algorithms for the relative orientation using spherical correspondences, absolute orientation using 3D correspondences between scene and spherical points, and the cost functions for BA (bundle adjustment) optimization. In addition, an incremental SfM (Structure from Motion) workflow has been proposed for spherical images using the above-mentioned algorithms. The proposed solution is finally verified by using three spherical datasets captured by both consumer-grade and professional spherical cameras. The results demonstrate that the proposed SfM workflow can achieve the successful 3D reconstruction of complex scenes and provide useful clues for the implementation in open-source software packages. The source code of the designed SfM workflow would be made publicly available.	['Wu Chen', 'Duojie Weng', 'Yaxin Li', 'Kan You', 'San Jiang']	2023-06-22	null	null	null	null	['3d-reconstruction']	['computer-vision']	[ 1.64654821e-01 -2.46941790e-01 5.83927095e-01 -3.29457313e-01 -3.95730436e-01 -7.09451675e-01 6.28849924e-01 -1.45522699e-01 -4.29076821e-01 4.42245543e-01 -3.22161674e-01 -3.64539295e-01 -2.39750490e-01 -9.06785429e-01 -5.44899881e-01 -6.62520826e-01 1.17853530e-01 6.77788973e-01 4.39980388e-01 -3.84656310e-01 1.40104041e-01 1.29608500e+00 -1.74665058e+00 -4.27160501e-01 7.83678353e-01 6.48160219e-01 8.08135152e-01 6.77352726e-01 -2.72277482e-02 -2.45115414e-01 1.02795720e-01 -1.89977229e-01 5.61704457e-01 1.79404784e-02 -2.74818242e-01 4.83220458e-01 5.24015844e-01 -5.99180162e-01 -2.06184257e-02 8.39748323e-01 3.78643692e-01 3.77825387e-02 4.09064889e-01 -7.78065622e-01 1.15873873e-01 -1.71544015e-01 -3.73996735e-01 -2.08876252e-01 6.15150094e-01 1.13518260e-01 5.77218175e-01 -9.84284282e-01 6.28742695e-01 8.64296317e-01 7.45982766e-01 -2.16727555e-01 -1.00803924e+00 -1.05112739e-01 -3.00825208e-01 1.79158017e-01 -1.69260228e+00 -6.02007985e-01 5.38221538e-01 -5.56971073e-01 8.92200530e-01 4.72795248e-01 1.07915318e+00 4.49142575e-01 6.97678849e-02 5.14304526e-02 1.03488243e+00 -4.52614814e-01 1.44168377e-01 1.30700171e-01 -2.22276211e-01 4.41907912e-01 5.70278466e-01 -4.23990302e-02 1.63565762e-02 3.57924066e-02 1.04334462e+00 2.74203926e-01 -4.86745030e-01 -4.14416194e-01 -1.22596562e+00 4.67803538e-01 4.21817482e-01 3.28795254e-01 -6.49521172e-01 -8.27441439e-02 -2.81283438e-01 4.30041030e-02 4.12068576e-01 1.12381607e-01 -3.12970400e-01 -7.14622363e-02 -1.00983381e+00 -4.83402535e-02 5.14466763e-01 1.15448356e+00 9.41106915e-01 1.33173257e-01 6.59985602e-01 3.64347368e-01 7.30464160e-01 1.17698622e+00 5.09127267e-02 -6.99038088e-01 3.25358957e-01 8.13258052e-01 3.38647097e-01 -1.30082011e+00 -5.08612335e-01 -2.24448785e-01 -7.23570228e-01 1.44533411e-01 1.33527786e-01 2.69886643e-01 -4.76151973e-01 6.84380770e-01 6.98163271e-01 1.84089124e-01 1.78327501e-01 8.77897799e-01 8.55737567e-01 5.85429788e-01 -6.47356749e-01 -3.13781112e-01 1.05304372e+00 -2.78042585e-01 -3.38759780e-01 -2.78163135e-01 3.22392493e-01 -1.09304976e+00 8.60816419e-01 2.09472284e-01 -8.38299811e-01 -3.01126659e-01 -8.00745845e-01 1.36432037e-01 -1.07231870e-01 5.40144563e-01 3.24950635e-01 7.40536213e-01 -1.21283555e+00 3.70462298e-01 -1.00075150e+00 -9.83209789e-01 9.86149609e-02 1.16606422e-01 -5.05917490e-01 -1.38588980e-01 -5.94815314e-01 1.02310908e+00 -2.74891630e-02 7.04039693e-01 -7.12799370e-01 -3.39863300e-01 -6.91810369e-01 -1.42653108e-01 7.19947442e-02 -4.89134997e-01 7.98825622e-01 -6.31586134e-01 -1.43855298e+00 1.12620759e+00 -1.01175122e-01 -8.26014131e-02 6.08639657e-01 -2.15951622e-01 -2.17470407e-01 3.02155495e-01 1.56212419e-01 4.41730954e-02 6.83295667e-01 -1.20924783e+00 -3.98925632e-01 -6.02250278e-01 -3.78764756e-02 5.49411535e-01 -5.99524342e-02 -3.81451547e-02 -2.45254681e-01 -3.62546346e-03 8.42151821e-01 -1.02795744e+00 -3.50951254e-01 1.57859460e-01 -1.04705974e-01 4.49434578e-01 8.19196641e-01 -6.72770381e-01 6.99086845e-01 -2.12720203e+00 -4.07910161e-03 2.84246832e-01 -3.20693195e-01 2.42118105e-01 2.56287515e-01 4.89931643e-01 1.60551757e-01 -1.57755911e-01 -3.13213140e-01 -2.63219923e-01 -4.05896813e-01 3.01953882e-01 1.43375680e-01 9.28217232e-01 -4.47809815e-01 2.94944495e-01 -6.43442571e-01 -4.40770179e-01 8.40628445e-01 5.64738572e-01 -1.66465595e-01 6.00779019e-02 1.79023474e-01 5.79604924e-01 -4.39210564e-01 6.73234701e-01 1.09416938e+00 1.44943520e-01 7.23335445e-02 -2.30179980e-01 -8.28450739e-01 -1.49940118e-01 -1.60374701e+00 1.45782006e+00 -5.59253633e-01 4.50911224e-01 5.13361871e-01 -6.43053889e-01 1.18665135e+00 4.72352326e-01 4.11677688e-01 -1.28573790e-01 -1.43486343e-03 4.53008264e-01 -4.81153876e-01 -6.49620473e-01 6.66975856e-01 -1.02960758e-01 3.88223886e-01 -8.86011589e-03 -4.40718234e-01 -1.00950980e+00 -1.67320192e-01 5.45619288e-04 5.08880496e-01 4.09414589e-01 7.09925294e-01 -2.05688611e-01 8.52338731e-01 3.82487506e-01 2.51014650e-01 1.86473668e-01 1.67047575e-01 8.36317480e-01 -2.68984109e-01 -6.15585685e-01 -1.26992500e+00 -8.67155910e-01 -4.35278863e-01 6.37599975e-02 2.51285017e-01 -1.50688887e-01 -4.01034147e-01 9.98363644e-02 -1.04389541e-01 4.00384575e-01 2.56896056e-02 5.34767568e-01 -2.62504935e-01 -6.15316570e-01 1.18556991e-01 -1.15871981e-01 6.17232740e-01 -5.86545527e-01 -9.24831212e-01 1.49625301e-01 -8.58236551e-02 -1.18666458e+00 6.02916218e-02 -3.99317771e-01 -1.28523588e+00 -1.23451722e+00 -4.39861447e-01 -3.87210548e-01 7.95539021e-01 1.21056783e+00 8.46377254e-01 2.38735035e-01 -7.68947154e-02 7.90047348e-01 -5.66761315e-01 -1.23909727e-01 -2.69399256e-01 -1.47387475e-01 1.70083836e-01 1.11021861e-01 6.64488822e-02 -8.77788186e-01 -5.43438554e-01 7.23466337e-01 -7.33328223e-01 1.27464265e-01 5.33018291e-01 8.73750821e-02 7.45954752e-01 6.45747483e-02 -7.79254213e-02 -3.67023557e-01 -1.81671530e-01 -3.26179326e-01 -1.18791294e+00 4.91897836e-02 -1.90635458e-01 -5.23280442e-01 5.10221064e-01 2.90375441e-01 -1.04845047e+00 5.68029642e-01 -2.16854572e-01 -2.20687807e-01 -6.46490455e-01 5.87981641e-01 -3.15195888e-01 -2.96256036e-01 6.04677141e-01 5.50971329e-01 1.98602512e-01 -5.01741827e-01 1.80800363e-01 9.19351161e-01 2.87457615e-01 -1.45912990e-01 1.11730886e+00 9.64260995e-01 2.18018159e-01 -1.73428178e+00 -3.19534034e-01 -8.13143969e-01 -1.11614513e+00 -5.94023705e-01 8.97956550e-01 -1.03234947e+00 -4.28658903e-01 5.01626611e-01 -1.19310856e+00 1.35023177e-01 -2.37397552e-02 7.37982213e-01 -4.49983358e-01 7.53937602e-01 1.10037401e-01 -1.00538421e+00 -2.78787911e-01 -1.32937968e+00 1.17330313e+00 2.60671496e-01 2.12961361e-01 -8.85211289e-01 -9.04913805e-03 6.48951411e-01 3.34179282e-01 3.50026965e-01 1.57958716e-01 1.10420108e-01 -1.11311495e+00 -3.43077928e-01 1.19227014e-01 1.73828050e-01 1.48754284e-01 4.40930992e-01 -7.52471864e-01 -2.20212340e-01 1.99684933e-01 2.84718126e-01 1.12971120e-01 5.68653166e-01 3.08232516e-01 -5.26028052e-02 -2.10358188e-01 9.37136292e-01 1.80012321e+00 4.34061624e-02 9.52576637e-01 7.83772588e-01 7.16716111e-01 5.78302383e-01 8.17266464e-01 6.75763011e-01 5.29262364e-01 8.19163561e-01 9.59175825e-01 6.28243610e-02 2.64233410e-01 8.58936012e-02 3.75746787e-01 6.94418073e-01 -8.13824356e-01 2.80898064e-01 -9.69903171e-01 4.02109891e-01 -1.51071894e+00 -1.09589458e+00 -1.20452929e+00 2.64236522e+00 1.42946348e-01 -3.79532605e-01 -3.99635166e-01 1.52781844e-01 4.51272100e-01 8.49231184e-02 -1.41751364e-01 1.72971059e-02 -3.40897709e-01 -7.92212263e-02 8.02480400e-01 8.03913176e-01 -1.00324607e+00 9.06404912e-01 5.22199106e+00 2.54195184e-01 -1.12484121e+00 3.30529967e-03 -3.23154598e-01 2.28349194e-01 -4.30011809e-01 3.49153996e-01 -9.95539010e-01 1.46706477e-01 6.38331175e-01 4.95930947e-02 4.03308183e-01 1.01708245e+00 9.80532706e-01 -5.03027499e-01 -4.67284888e-01 1.14486718e+00 2.18587797e-02 -1.16979742e+00 -1.63324550e-01 2.76591808e-01 7.24084198e-01 3.31536204e-01 -4.68232572e-01 -5.52808225e-01 -5.17781191e-02 -5.89152813e-01 8.10384691e-01 7.19907463e-01 6.56670511e-01 -5.01602829e-01 8.28892231e-01 5.95488548e-01 -1.42069006e+00 2.10401565e-01 -6.73162222e-01 -2.60219574e-01 5.44645011e-01 8.52390528e-01 -1.08031166e+00 1.03946149e+00 8.92911911e-01 9.04663205e-01 -6.39824748e-01 1.21033347e+00 -3.42083722e-01 1.94280028e-01 -7.23363817e-01 7.32581243e-02 2.20969185e-01 -1.06639302e+00 7.85738468e-01 6.67147815e-01 1.07502127e+00 2.91673481e-01 -7.64760077e-02 4.12736714e-01 6.68148279e-01 2.28600651e-01 -1.06779861e+00 4.66022134e-01 5.15938520e-01 1.52414477e+00 -7.84409106e-01 -2.47025955e-03 -4.68253821e-01 8.69944930e-01 -4.31592524e-01 4.60495204e-02 -6.00757837e-01 1.23327650e-01 4.39971983e-01 5.69255114e-01 1.34717494e-01 -8.58108222e-01 -1.53997257e-01 -1.22795486e+00 2.95324717e-02 -4.93638068e-01 -1.26667261e-01 -1.33569884e+00 -5.43769360e-01 4.31000710e-01 1.25268415e-01 -1.69279790e+00 1.02648765e-01 -4.93490338e-01 -4.24944222e-01 7.67479658e-01 -1.34342659e+00 -1.38434029e+00 -8.29555035e-01 6.73969448e-01 5.11710584e-01 -7.56542161e-02 8.21355581e-01 1.16605915e-01 -2.74232954e-01 -4.61631358e-01 6.27947390e-01 -5.12798548e-01 3.63760918e-01 -9.66905057e-01 5.71085326e-02 1.19894230e+00 3.71678621e-02 3.56578410e-01 6.76434875e-01 -6.85729742e-01 -1.78936434e+00 -9.07974005e-01 9.30580437e-01 -4.11525518e-01 3.73685718e-01 -8.94648135e-02 -5.33137381e-01 8.72966826e-01 -1.29611030e-01 -1.05408944e-01 4.42547619e-01 -4.20392036e-01 4.11430508e-01 -3.65696102e-01 -1.23755050e+00 3.45521003e-01 9.10355449e-01 -1.15597397e-01 -4.91073400e-01 4.98907208e-01 2.14238942e-01 -4.50957090e-01 -9.63224828e-01 4.45452519e-02 6.02420032e-01 -1.38588178e+00 1.11239600e+00 2.59472996e-01 6.49323016e-02 -7.89211571e-01 -5.02203763e-01 -1.23414314e+00 -7.80232474e-02 -3.04951310e-01 6.31388307e-01 1.00042319e+00 5.12024313e-02 -7.61009216e-01 7.21513212e-01 4.02667791e-01 -4.50063318e-01 2.02853940e-02 -1.06650257e+00 -6.09395206e-01 -6.26960754e-01 -4.58936185e-01 5.56725085e-01 6.92781150e-01 -5.56085050e-01 7.97857344e-02 -2.32999831e-01 9.65765119e-01 7.88813949e-01 2.43382439e-01 1.26521385e+00 -1.76363444e+00 1.36907756e-01 -8.00571889e-02 -7.74886668e-01 -9.53206122e-01 -2.77726352e-01 -6.87624812e-01 -1.55207738e-01 -1.80459201e+00 -1.31264806e-01 -6.42694950e-01 9.50042188e-01 -5.41050173e-03 3.87616038e-01 9.81379375e-02 5.02982065e-02 6.57938004e-01 -4.26042080e-02 6.37902677e-01 1.11047232e+00 3.01046431e-01 -1.77649036e-01 2.84245938e-01 -5.67125566e-02 9.25162137e-01 5.20404339e-01 -1.69486105e-01 -3.10307682e-01 -6.71743631e-01 5.94198227e-01 1.98932774e-02 4.77758437e-01 -1.02847683e+00 3.31785321e-01 -2.69285560e-01 6.51856810e-02 -1.19754827e+00 5.03077447e-01 -1.66133058e+00 9.74001110e-01 4.08868879e-01 7.85443962e-01 5.90531975e-02 -5.60506396e-02 3.64280850e-01 -7.96697661e-02 -5.58735967e-01 8.13786626e-01 -4.06183064e-01 -7.58553803e-01 2.17238933e-01 -4.35097635e-01 -7.66157269e-01 1.25075150e+00 -7.75437295e-01 4.45755869e-02 -4.26546901e-01 -7.16073334e-01 -1.23348329e-02 1.16165090e+00 -1.86101213e-01 8.97947967e-01 -1.16897035e+00 -7.64787138e-01 4.19601589e-01 -1.72412372e-03 6.87332571e-01 4.67376709e-01 1.03538728e+00 -1.45168173e+00 4.54058617e-01 -1.89813346e-01 -1.02536726e+00 -1.53664756e+00 8.58344324e-03 4.89910185e-01 3.29107463e-01 -6.55783713e-01 2.58912265e-01 -2.30793938e-01 -7.74494410e-01 -4.13528681e-01 -3.84839147e-01 -3.39428216e-01 -9.00438987e-04 3.07890385e-01 6.78935349e-01 3.68868530e-01 -1.20792806e+00 -5.45754015e-01 1.20662367e+00 6.58884048e-01 -1.79535329e-01 1.84433901e+00 -5.56242466e-01 -3.31543058e-01 1.80635214e-01 6.95270360e-01 1.53486252e-01 -1.04837251e+00 1.21455692e-01 -3.02326679e-01 -8.92462969e-01 2.76300877e-01 -6.86319694e-02 -8.19593728e-01 7.32764781e-01 5.34397364e-01 7.93894231e-02 1.05650902e+00 -1.08340636e-01 1.30259663e-01 4.73777443e-01 8.37770760e-01 -6.68834448e-01 -7.04718411e-01 4.09959227e-01 1.04929149e+00 -1.09368289e+00 4.26412344e-01 -5.50079942e-01 -4.19691473e-01 1.41968238e+00 1.07193738e-01 1.02414459e-01 6.68163240e-01 4.98163477e-02 9.69279930e-03 -2.43116349e-01 9.30191725e-02 -2.24679396e-01 -1.40529633e-01 8.40067625e-01 3.76148611e-01 1.58658236e-01 -4.20708060e-01 -1.96426660e-02 -2.80287117e-01 -6.74106553e-02 1.05392599e+00 8.35191309e-01 -6.46781087e-01 -8.23788583e-01 -1.24651468e+00 1.38591588e-01 2.48745233e-01 -2.73001250e-02 -1.09899655e-01 8.79701674e-01 -3.36147137e-02 8.62077713e-01 8.29064101e-02 -5.20818681e-02 6.59772038e-01 -3.54139894e-01 3.71252596e-01 -5.04249990e-01 -2.43977040e-01 2.20114902e-01 1.01208240e-01 -4.89799291e-01 -9.17937994e-01 -1.20176649e+00 -8.48908305e-01 -3.92473966e-01 -3.22389334e-01 -2.89878100e-02 1.14517736e+00 7.68501937e-01 2.02649757e-01 -3.57982844e-01 8.78968239e-01 -1.36702740e+00 -2.62826979e-01 -9.52678442e-01 -8.86535883e-01 -4.52951193e-02 3.01362071e-02 -6.22950733e-01 -5.58039069e-01 2.49259561e-01]	[8.380221366882324, -2.556986093521118]
7a9ceef4-e56c-43cc-ab05-91a04531bdf7	text2seg-remote-sensing-image-semantic	2304.10597	null	https://arxiv.org/abs/2304.10597v1	https://arxiv.org/pdf/2304.10597v1.pdf	Text2Seg: Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models	Recent advancements in foundation models (FMs), such as GPT-4 and LLaMA, have attracted significant attention due to their exceptional performance in zero-shot learning scenarios. Similarly, in the field of visual learning, models like Grounding DINO and the Segment Anything Model (SAM) have exhibited remarkable progress in open-set detection and instance segmentation tasks. It is undeniable that these FMs will profoundly impact a wide range of real-world visual learning tasks, ushering in a new paradigm shift for developing such models. In this study, we concentrate on the remote sensing domain, where the images are notably dissimilar from those in conventional scenarios. We developed a pipeline that leverages multiple FMs to facilitate remote sensing image semantic segmentation tasks guided by text prompt, which we denote as Text2Seg. The pipeline is benchmarked on several widely-used remote sensing datasets, and we present preliminary results to demonstrate its effectiveness. Through this work, we aim to provide insights into maximizing the applicability of visual FMs in specific contexts with minimal model tuning. The code is available at https://github.com/Douglas2Code/Text2Seg.	['Sheng Li', 'Mengxuan Hu', 'Lan Mu', 'Gengchen Mai', 'Zhongliang Zhou', 'Jielu Zhang']	2023-04-20	null	null	null	null	['segmentation-of-remote-sensing-imagery']	['miscellaneous']	[ 5.74524701e-01 -5.98662943e-02 -2.02618569e-01 -2.79132158e-01 -9.33271527e-01 -7.22707033e-01 5.75938225e-01 1.74532071e-01 -2.10211843e-01 4.04815555e-01 -6.73588142e-02 -7.69858360e-01 -1.06558956e-01 -8.05731535e-01 -5.37290990e-01 -4.88148421e-01 -1.51274770e-01 3.96551132e-01 3.22923928e-01 -4.16202992e-02 2.12633327e-01 4.12211984e-01 -1.70563936e+00 2.20801577e-01 9.16341424e-01 6.08608365e-01 4.73311722e-01 7.32507706e-01 -2.29807034e-01 7.15893567e-01 -2.92156160e-01 -7.56160617e-02 4.24886405e-01 -2.38630638e-01 -9.84681666e-01 7.55163357e-02 5.26979864e-01 -2.03106552e-01 9.97935236e-02 1.01533902e+00 6.11281514e-01 4.78699297e-01 7.07501590e-01 -1.09713542e+00 -5.08871675e-01 4.90165412e-01 -7.31601775e-01 3.37656766e-01 -2.58983463e-01 4.57753897e-01 1.45558918e+00 -8.15197408e-01 6.96032405e-01 1.15794885e+00 8.87134135e-01 2.60058463e-01 -1.23062015e+00 -4.28013265e-01 3.13223392e-01 1.41981691e-01 -1.41583538e+00 -4.96378750e-01 3.78299981e-01 -7.42879570e-01 1.10639548e+00 3.27824235e-01 6.52642548e-01 7.34951615e-01 -2.93725967e-01 1.04842758e+00 1.19111824e+00 -4.29619879e-01 3.56917173e-01 -9.06839222e-02 2.27281988e-01 6.07387900e-01 -6.37350753e-02 7.52162747e-03 -1.43201753e-01 2.27270033e-02 5.67031741e-01 6.41810149e-02 -2.79322028e-01 -1.81571066e-01 -9.69803512e-01 1.06579340e+00 8.67892027e-01 5.51874302e-02 -1.66172639e-01 1.23770900e-01 1.74572915e-01 -1.86200067e-01 9.75653231e-01 3.47495168e-01 -3.19374830e-01 1.56728730e-01 -1.27456582e+00 2.34011635e-01 7.11779356e-01 6.72669947e-01 9.97339368e-01 3.16806659e-02 -1.58983380e-01 1.08934462e+00 4.25160944e-01 4.71185923e-01 -8.01903307e-02 -8.41658056e-01 3.21973354e-01 5.00983775e-01 -1.72834303e-02 -7.71066725e-01 -4.24013466e-01 -2.68285304e-01 -4.83957291e-01 4.64252174e-01 2.31935188e-01 -2.69770563e-01 -1.63893259e+00 1.30936098e+00 3.84647131e-01 3.19976538e-01 -1.03505820e-01 7.88436651e-01 1.15594089e+00 1.01278555e+00 4.84231681e-01 4.59126979e-01 1.15610635e+00 -1.07733107e+00 -1.68063626e-01 -7.71058083e-01 5.01282036e-01 -5.50705731e-01 1.37015498e+00 -3.52974720e-02 -5.09236693e-01 -4.48635072e-01 -8.92483890e-01 -3.68548781e-02 -7.30437458e-01 -3.43925171e-02 7.94289827e-01 4.78725493e-01 -8.90148342e-01 5.36328971e-01 -1.04331899e+00 -9.24407542e-01 9.40669239e-01 -2.89549798e-01 3.52400951e-02 -7.33345523e-02 -8.60225558e-01 6.83694363e-01 5.97190201e-01 3.12637269e-01 -1.07894635e+00 -9.49024856e-01 -8.03621829e-01 9.02589932e-02 4.66076970e-01 -4.89711553e-01 1.31643414e+00 -8.30447674e-01 -8.42176914e-01 1.18418646e+00 5.86196557e-02 -2.55717754e-01 5.02883434e-01 -1.47945464e-01 -1.32104829e-01 7.33819231e-02 3.28019530e-01 1.24661314e+00 6.07841909e-01 -1.43614650e+00 -8.10856640e-01 -2.93247998e-01 1.13207243e-01 3.58871847e-01 1.15134031e-01 1.26800016e-01 -4.02002245e-01 -5.06973684e-01 4.23635207e-02 -8.09523463e-01 -5.85846066e-01 2.59500414e-01 -5.09472787e-01 2.43771095e-02 8.90226543e-01 -6.36515081e-01 1.06130993e+00 -2.08699703e+00 -1.55703858e-01 9.45693478e-02 4.01575416e-02 5.49512148e-01 -7.78105482e-02 5.33014059e-01 1.96167797e-01 5.11715531e-01 -9.21162903e-01 -1.96920991e-01 -1.17799804e-01 4.14197534e-01 -4.03872341e-01 4.21144396e-01 3.32869977e-01 1.12807274e+00 -8.89915824e-01 -4.39937681e-01 3.98852021e-01 3.34450185e-01 -2.88807452e-01 1.94359183e-01 -8.08486521e-01 5.18842280e-01 -3.79259259e-01 1.03815091e+00 5.95229030e-01 -5.33120453e-01 2.70778444e-02 1.97137639e-01 -4.34437722e-01 -2.14515045e-01 -9.68874395e-01 1.47773957e+00 -1.16133764e-01 7.50495315e-01 1.17793843e-01 -8.07057440e-01 8.27446401e-01 -9.30551514e-02 2.13532254e-01 -5.51579833e-01 -1.89490646e-01 7.12549686e-02 -2.96399772e-01 -6.58527017e-01 5.42294800e-01 -2.33348802e-01 1.19702421e-01 2.70039737e-01 -1.19050257e-01 -3.24478418e-01 1.41756892e-01 1.89521402e-01 5.62409401e-01 4.78449047e-01 5.38103044e-01 -2.11750269e-01 -1.10467635e-01 6.30320966e-01 3.86103064e-01 1.05295467e+00 -4.06753540e-01 8.80831420e-01 2.22822294e-01 -4.49197769e-01 -8.45715404e-01 -1.02099240e+00 -2.59833425e-01 1.36913574e+00 1.92904994e-01 -1.05763696e-01 -5.31626642e-01 -6.70884848e-01 1.52835220e-01 7.31936276e-01 -6.32189631e-01 3.51623654e-01 -5.76335154e-02 -1.09139669e+00 7.23508954e-01 5.07794201e-01 5.67993164e-01 -1.28458798e+00 -8.87973011e-01 1.62644342e-01 -1.22369170e-01 -9.13683772e-01 1.64639816e-01 2.51002163e-01 -7.48415828e-01 -1.16183770e+00 -7.38033295e-01 -6.07556522e-01 2.55390733e-01 7.99513757e-01 1.18543398e+00 -4.74524349e-02 -6.38212085e-01 3.08169067e-01 -5.21270812e-01 -6.54472291e-01 -2.74626791e-01 4.20866489e-01 -7.79898942e-01 -2.29959950e-01 4.50365275e-01 -3.48278403e-01 -6.86343670e-01 1.77959681e-01 -1.17398632e+00 2.69640565e-01 3.50692689e-01 4.66457486e-01 6.69027686e-01 -2.99889565e-01 4.40495133e-01 -1.22956419e+00 2.07891658e-01 -8.78707349e-01 -6.19896352e-01 4.27492023e-01 -5.83066225e-01 -4.24540490e-01 1.05693437e-01 1.77380934e-01 -1.28775275e+00 7.73609281e-02 -2.56304115e-01 -2.23337948e-01 -5.69474220e-01 9.77458894e-01 1.44429952e-01 2.23980229e-02 8.93180192e-01 -9.60599855e-02 -2.16433227e-01 -7.16408551e-01 6.93999946e-01 9.96179581e-01 4.01562840e-01 -2.49128461e-01 6.36251807e-01 7.27242112e-01 -3.49309146e-01 -1.22521055e+00 -1.29909575e+00 -8.65521312e-01 -4.50600475e-01 -2.36922666e-01 1.05502474e+00 -1.22755277e+00 1.45854503e-01 5.16006052e-01 -6.48681641e-01 -7.78442502e-01 -1.58977717e-01 6.36865571e-02 -3.64008874e-01 2.76173353e-01 -2.63255298e-01 -9.19623196e-01 -5.28752565e-01 -1.00398231e+00 1.20197070e+00 5.46625257e-01 -2.31391061e-02 -1.19726145e+00 1.90198928e-01 4.91750270e-01 5.20050824e-01 3.92228693e-01 8.17544103e-01 -5.35403252e-01 -5.67659020e-01 2.66584903e-01 -5.83161652e-01 4.28635418e-01 -1.17345631e-01 3.31125140e-01 -1.34347498e+00 -1.73528597e-01 -6.96829379e-01 -5.14204800e-01 1.41641581e+00 5.86499214e-01 1.02160060e+00 2.47221008e-01 -4.28049594e-01 1.02918077e+00 1.66843474e+00 -1.77107509e-02 5.64060748e-01 5.05705237e-01 1.00258934e+00 6.57071829e-01 6.61543489e-01 3.86260599e-01 4.76933807e-01 3.66445810e-01 7.25942492e-01 -7.05805957e-01 -2.32033506e-01 -3.82697135e-01 -1.40121073e-01 1.62165627e-01 -1.22565821e-01 -3.45948160e-01 -1.57795274e+00 7.78792381e-01 -1.99702513e+00 -1.05053329e+00 -2.67964423e-01 1.84162652e+00 5.26708424e-01 -2.08951443e-01 -6.51134625e-02 -3.87592912e-01 6.90282702e-01 7.44187891e-01 -7.23309517e-01 1.16056642e-02 -2.58489400e-01 2.14595646e-01 6.41401887e-01 5.78543603e-01 -1.58648312e+00 1.53149152e+00 6.26333380e+00 9.26369429e-01 -1.06589818e+00 1.16421215e-01 9.51749146e-01 1.46885857e-01 -2.43634239e-01 3.15299541e-01 -9.17985976e-01 1.54067695e-01 6.31927371e-01 -1.27067463e-02 2.44535699e-01 8.20733488e-01 5.42562544e-01 -4.02724624e-01 -5.71938515e-01 6.45325720e-01 -1.04097053e-01 -1.49272454e+00 5.46816327e-02 -7.54545704e-02 9.77654874e-01 8.22291315e-01 1.40190925e-02 3.62247109e-01 5.82613647e-01 -1.14799058e+00 5.76713443e-01 2.80172437e-01 8.63628328e-01 -4.33778733e-01 3.56974125e-01 2.40060210e-01 -1.25804949e+00 -7.54223093e-02 -4.85016197e-01 -3.49244326e-02 3.19612443e-01 3.61235917e-01 -1.00606883e+00 6.22018576e-01 8.52094889e-01 1.03120577e+00 -6.96872771e-01 1.40297031e+00 -3.01173687e-01 9.95231330e-01 -2.70639598e-01 4.50439274e-01 7.13681936e-01 -3.12438130e-01 5.11550605e-01 1.44088912e+00 1.77739799e-01 5.89461252e-02 4.87325758e-01 9.57166970e-01 5.42391799e-02 9.86492038e-02 -7.16747463e-01 -2.21942708e-01 3.68919283e-01 1.53412747e+00 -1.01825833e+00 -3.41305405e-01 -3.93362582e-01 5.96460760e-01 2.04648167e-01 6.06211543e-01 -8.97975385e-01 -2.07387596e-01 7.14042246e-01 -1.82251595e-02 3.00676435e-01 -1.10915229e-01 -3.12914938e-01 -1.09671283e+00 -3.96693677e-01 -7.33359337e-01 6.63989425e-01 -9.03919876e-01 -1.29860437e+00 3.65605533e-01 1.51500687e-01 -1.06508613e+00 2.31514007e-01 -4.27373976e-01 -8.26439142e-01 8.56415629e-01 -2.02759099e+00 -1.57025254e+00 -6.85259521e-01 2.31142506e-01 7.73880005e-01 2.04589099e-01 6.86491847e-01 1.32396037e-03 -6.36700511e-01 -5.17776143e-03 3.26862693e-01 -2.71759145e-02 4.43633974e-01 -1.17177773e+00 8.70644033e-01 1.11471009e+00 4.05140191e-01 1.87934712e-01 4.94077265e-01 -6.82293236e-01 -8.02025676e-01 -1.58467257e+00 4.59036291e-01 -3.19272608e-01 7.03905284e-01 -3.06989461e-01 -1.10515487e+00 9.43080246e-01 -4.57681417e-02 9.32708457e-02 7.73455977e-01 -4.21129726e-02 -3.38881552e-01 2.30866522e-01 -9.57512021e-01 4.43697870e-01 1.05694818e+00 -4.83049542e-01 -4.12531197e-01 5.92762113e-01 5.30399740e-01 -2.70569950e-01 -5.86639166e-01 4.56122935e-01 4.17863339e-01 -1.02587020e+00 9.42254722e-01 -6.33866072e-01 4.94788080e-01 -4.56889153e-01 -3.04515004e-01 -1.35972714e+00 -4.50586289e-01 -1.94627702e-01 2.02487782e-01 1.07110167e+00 5.75246811e-01 -4.64418054e-01 7.22002506e-01 2.49789104e-01 -3.30522090e-01 -4.49819744e-01 -7.05683351e-01 -7.40708828e-01 1.57292977e-01 -2.98575133e-01 3.25237662e-01 1.09117818e+00 -4.68973011e-01 2.56059140e-01 -2.72233725e-01 4.25398588e-01 5.67417920e-01 3.61222386e-01 7.95837820e-01 -1.29888320e+00 -4.18658048e-01 -4.57032531e-01 -1.11247614e-01 -9.58099365e-01 -1.99389048e-02 -1.15238965e+00 2.94447154e-01 -2.06212807e+00 3.85158509e-01 -6.09314978e-01 -1.25576019e-01 9.51621473e-01 -6.18872523e-01 5.03878891e-01 2.86722869e-01 3.18318784e-01 -5.83000898e-01 4.82446700e-01 8.74658346e-01 -3.23477298e-01 -2.69933879e-01 3.85280736e-02 -6.74048424e-01 6.71766698e-01 1.16447544e+00 -3.45520854e-01 -3.79504919e-01 -6.85888588e-01 5.16429171e-02 -4.20117229e-01 4.67987686e-01 -9.55909491e-01 5.94199263e-03 -4.03618842e-01 1.58790365e-01 -6.33453369e-01 -2.38606166e-02 -4.20627236e-01 2.69895464e-01 1.47350684e-01 -1.58946142e-01 -3.58108193e-01 3.61848712e-01 4.88890558e-01 -9.54562202e-02 -3.52104366e-01 9.55056906e-01 -5.11284888e-01 -1.49821341e+00 5.02229631e-01 -2.98394233e-01 2.47705847e-01 1.13993263e+00 -3.43045652e-01 -6.44486964e-01 -1.77377835e-01 -7.65613019e-01 4.36086744e-01 5.69795489e-01 3.79493982e-01 3.19779456e-01 -5.58196902e-01 -9.35755134e-01 1.58721387e-01 6.21990621e-01 2.18609571e-01 5.18564582e-01 6.20755672e-01 -7.67230749e-01 1.48978345e-02 -1.38486505e-01 -8.05195749e-01 -1.24932468e+00 1.27353773e-01 5.07021129e-01 -1.48401976e-01 -9.16117013e-01 9.31267977e-01 2.58781403e-01 -6.91006184e-01 -1.82763543e-02 -8.37642252e-02 -1.72358975e-01 2.95532405e-01 4.52432334e-01 4.51245725e-01 -4.84472550e-02 -5.89430451e-01 -2.68279850e-01 3.15157324e-01 7.46583790e-02 -4.13143933e-02 1.64327407e+00 -1.31962463e-01 3.76470909e-02 5.02124906e-01 8.11135173e-01 -3.84395003e-01 -1.71931922e+00 -2.14434311e-01 9.16126296e-02 -4.50408995e-01 3.15411031e-01 -1.00528169e+00 -9.39076841e-01 1.07565618e+00 6.74745619e-01 3.09945464e-01 8.64314616e-01 2.31125489e-01 3.74413580e-01 2.02095792e-01 2.35249564e-01 -9.46869016e-01 -4.16086674e-01 7.07977533e-01 5.03026783e-01 -1.69659102e+00 1.52250482e-02 -2.58400083e-01 -7.31256962e-01 8.74917388e-01 4.18852597e-01 2.58302480e-01 4.93780434e-01 -5.60209295e-03 4.36706185e-01 -4.92184222e-01 -4.47598517e-01 -8.84427428e-01 2.31508166e-01 7.65975893e-01 3.71462494e-01 3.39331537e-01 1.71789676e-01 4.66679642e-03 1.92165911e-01 -5.64107634e-02 4.47510600e-01 1.10235822e+00 -1.05987358e+00 -7.36908674e-01 -2.60106742e-01 5.47339141e-01 -2.96240330e-01 -4.65570062e-01 -3.79402429e-01 7.38433599e-01 3.93288583e-02 9.25002098e-01 8.52157325e-02 4.34339803e-04 2.01027453e-01 6.55164793e-02 7.13249221e-02 -9.94991660e-01 -5.33121109e-01 3.82921062e-02 2.09775761e-01 -4.66495425e-01 -5.73730290e-01 -5.93682766e-01 -1.11027920e+00 -1.56957597e-01 -6.59573972e-02 -1.29663646e-01 5.51160932e-01 7.50072122e-01 3.54619384e-01 2.81487972e-01 1.93045348e-01 -1.12412250e+00 -3.79330158e-01 -1.02138197e+00 -6.45959377e-01 1.79787487e-01 7.37888217e-02 -4.33570832e-01 -3.23771656e-01 1.27518520e-01]	[9.474609375, -1.2804348468780518]
4cafa948-5d59-40ed-bbcc-f3b364679953	graph-convolutional-auto-encoder-with-bi	2003.04508	null	https://arxiv.org/abs/2003.04508v3	https://arxiv.org/pdf/2003.04508v3.pdf	Unsupervised Graph Embedding via Adaptive Graph Learning	Graph autoencoders (GAEs) are powerful tools in representation learning for graph embedding. However, the performance of GAEs is very dependent on the quality of the graph structure, i.e., of the adjacency matrix. In other words, GAEs would perform poorly when the adjacency matrix is incomplete or be disturbed. In this paper, two novel unsupervised graph embedding methods, unsupervised graph embedding via adaptive graph learning (BAGE) and unsupervised graph embedding via variational adaptive graph learning (VBAGE) are proposed. The proposed methods expand the application range of GAEs on graph embedding, i.e, on the general datasets without graph structure. Meanwhile, the adaptive learning mechanism can initialize the adjacency matrix without be affected by the parameter. Besides that, the latent representations are embedded in the laplacian graph structure to preserve the topology structure of the graph in the vector space. Moreover, the adjacency matrix can be self-learned for better embedding performance when the original graph structure is incomplete. With adaptive learning, the proposed method is much more robust to the graph structure. Experimental studies on several datasets validate our design and demonstrate that our methods outperform baselines by a wide margin in node clustering, node classification, and graph visualization tasks.	['Xuelong. Li', 'Yunxing Zhang', 'Rui Zhang']	2020-03-10	null	null	null	null	['graph-reconstruction']	['graphs']	[-2.91865081e-01 2.87368298e-01 -2.29440734e-01 2.66829114e-02 1.66792914e-01 -4.32250053e-01 1.98612884e-01 1.33295015e-01 -5.18439859e-02 2.30069786e-01 1.73959494e-01 -2.84569442e-01 -3.07677805e-01 -1.10839510e+00 -5.69179416e-01 -1.03322780e+00 -9.92183480e-03 2.65090108e-01 -9.63540524e-02 -3.78093988e-01 -1.83772817e-01 2.68372774e-01 -8.58026922e-01 -3.80761087e-01 8.11407030e-01 4.05532449e-01 4.50875238e-03 2.91173577e-01 -2.27847293e-01 6.41094089e-01 -3.02347064e-01 -1.82384998e-01 6.51530027e-02 -3.77637833e-01 -3.03995192e-01 3.48252326e-01 -3.02615762e-02 -1.14290364e-01 -9.83410001e-01 1.35854065e+00 2.66726732e-01 1.93423718e-01 7.05455005e-01 -1.72107756e+00 -1.10747790e+00 8.29831243e-01 -4.70827878e-01 -6.90926164e-02 6.62196800e-02 2.87139658e-02 1.37154138e+00 -6.63855493e-01 5.25352895e-01 1.30765581e+00 6.87624037e-01 3.55826557e-01 -1.40084481e+00 -7.63002932e-01 3.95132959e-01 2.44473442e-01 -1.42812324e+00 -4.46339250e-02 1.54225135e+00 -6.47261500e-01 6.08273506e-01 3.77256684e-02 7.37404823e-01 9.22937989e-01 1.74890801e-01 4.70206946e-01 7.20647454e-01 -2.74406761e-01 2.25858226e-01 4.73550707e-02 3.24417919e-01 1.13374782e+00 4.25490350e-01 1.80739239e-01 2.40573697e-02 -1.24747716e-01 8.05352807e-01 3.44068110e-01 -3.16702992e-01 -8.38208139e-01 -1.08597231e+00 1.23500574e+00 9.52284276e-01 3.88212740e-01 -2.99178928e-01 2.46448457e-01 4.95786965e-01 4.86084402e-01 3.58144343e-01 2.79301971e-01 -3.11219925e-03 4.61060703e-01 -3.42464387e-01 -3.30490500e-01 7.30590940e-01 9.44387138e-01 9.95361149e-01 4.79080349e-01 -7.57892057e-02 5.52488267e-01 5.42377353e-01 4.52912211e-01 5.46291411e-01 -4.88443792e-01 3.67596209e-01 1.00700128e+00 -3.26603919e-01 -1.92024219e+00 -3.62929791e-01 -3.81600767e-01 -1.43027663e+00 -1.71942145e-01 6.49452433e-02 -5.62437773e-02 -7.68400609e-01 1.80210280e+00 2.33712494e-01 3.92371118e-01 4.81112823e-02 6.75393641e-01 1.07195306e+00 7.71104813e-01 -2.21088603e-01 -5.79271168e-02 9.60362315e-01 -8.79026175e-01 -1.10383153e+00 -2.11691692e-01 6.52718842e-01 -8.05009082e-02 1.11671197e+00 -1.44434631e-01 -4.35316682e-01 -5.15157521e-01 -1.19954944e+00 2.00544864e-01 -3.62791777e-01 -6.50019348e-02 8.23668897e-01 5.25442541e-01 -1.01509440e+00 4.21407759e-01 -9.62288380e-01 -3.50538582e-01 1.91867813e-01 3.57893288e-01 -5.42534769e-01 -7.48099163e-02 -1.27010477e+00 1.87064707e-01 7.14524984e-01 1.55647174e-01 -4.05031919e-01 -1.99090049e-01 -1.21111655e+00 4.88217711e-01 3.38237226e-01 -4.93652523e-01 3.19381952e-01 -9.95414019e-01 -1.28895283e+00 3.64288211e-01 1.76940680e-01 -3.60927880e-01 1.42029777e-01 4.00991768e-01 -3.93634230e-01 3.48340362e-01 -1.28100410e-01 2.09418848e-01 1.00993228e+00 -1.11592698e+00 2.83142388e-01 -3.10739517e-01 7.88222924e-02 2.69516185e-02 -8.27136576e-01 -6.85037196e-01 -4.11705494e-01 -7.43513823e-01 3.89050096e-01 -1.11371922e+00 -2.22161710e-01 -2.30759121e-02 -3.55014294e-01 -2.69960791e-01 1.01558816e+00 -7.36573160e-01 1.48842907e+00 -2.53815436e+00 4.80450302e-01 5.43069184e-01 7.72971094e-01 8.89587924e-02 -4.27862525e-01 8.04645300e-01 -4.03376669e-01 4.11205441e-01 -1.91949889e-01 2.03503340e-01 1.28990710e-01 4.28656995e-01 -1.19275965e-01 5.17608881e-01 -3.80820297e-02 1.24908876e+00 -1.07155538e+00 -5.21865487e-01 3.43136609e-01 5.59128165e-01 -7.42247581e-01 2.60987580e-01 1.18544400e-01 3.06282997e-01 -6.05279207e-01 2.38318488e-01 5.28075278e-01 -6.56131268e-01 4.63515639e-01 -5.13758242e-01 4.55021292e-01 -2.32340187e-01 -1.33507931e+00 1.50765002e+00 -3.06911737e-01 5.26374578e-01 2.74299048e-02 -1.47161531e+00 1.11008060e+00 1.71360686e-01 6.82699561e-01 -3.75026733e-01 7.53699169e-02 -2.64766306e-01 3.66681099e-01 -2.78565258e-01 -1.69305112e-02 1.09930843e-01 1.04402184e-01 4.54370141e-01 1.04759902e-01 2.80886769e-01 1.39077649e-01 6.48351312e-01 9.80579197e-01 -4.15798813e-01 3.85004103e-01 -2.63950676e-01 4.81760800e-01 -5.35528660e-01 6.65001094e-01 3.67793769e-01 -1.85125828e-01 1.35387585e-01 8.14880490e-01 -3.52609009e-01 -9.81926680e-01 -1.00108790e+00 1.47299632e-01 6.67972803e-01 2.49522522e-01 -7.99394667e-01 -6.65300429e-01 -7.51157880e-01 4.15496295e-03 3.66459370e-01 -7.70085454e-01 -7.73777246e-01 -3.83108169e-01 -6.74141884e-01 2.13929132e-01 5.47652125e-01 4.50204700e-01 -1.02950621e+00 2.74880409e-01 2.01590806e-01 1.94734167e-02 -9.21455324e-01 -7.96006858e-01 -2.19809741e-01 -9.25905168e-01 -1.26660311e+00 -2.68825293e-01 -1.05368233e+00 1.04066944e+00 4.10385549e-01 8.10440421e-01 7.26554930e-01 6.86024725e-02 6.39481783e-01 -5.98917663e-01 1.09790266e-01 -3.97386879e-01 4.53800075e-02 3.18523012e-02 2.79304355e-01 1.81428745e-01 -9.33222294e-01 -4.39587265e-01 1.79478422e-01 -1.01916075e+00 5.77351935e-02 5.08796334e-01 1.40180266e+00 5.85748911e-01 4.82328087e-01 5.50622106e-01 -1.02889693e+00 8.20461035e-01 -5.72155416e-01 -5.27093649e-01 2.58433789e-01 -9.78275955e-01 3.99771780e-01 8.61076534e-01 -5.82870305e-01 -4.19034809e-01 -1.57186806e-01 4.89988849e-02 -7.77356982e-01 4.54994112e-01 9.13024127e-01 -4.21451420e-01 -5.45008667e-02 3.06998670e-01 3.48228574e-01 2.97464162e-01 -2.63195366e-01 5.30405104e-01 2.08163589e-01 5.65304309e-02 -2.01071858e-01 1.12063086e+00 2.49519736e-01 1.02986127e-01 -8.75446200e-01 -2.72661418e-01 -2.83370346e-01 -6.76129699e-01 7.15461746e-02 7.19861865e-01 -7.13344872e-01 -5.19565284e-01 2.25197986e-01 -7.25019574e-01 -1.70052797e-01 -1.20298140e-01 4.81602937e-01 -1.35330036e-01 9.22422051e-01 -8.27805221e-01 -4.73293751e-01 -4.72689241e-01 -1.10071158e+00 7.62656212e-01 1.56032881e-02 2.95859694e-01 -1.52359414e+00 7.89976493e-02 -1.65525839e-01 7.36073628e-02 4.66590285e-01 1.19867098e+00 -5.66201746e-01 -4.70757067e-01 -3.47083569e-01 -2.42287487e-01 3.55059206e-01 4.13709611e-01 1.26004279e-01 -4.04033124e-01 -8.52728367e-01 -2.46321857e-01 5.63351065e-03 8.06264997e-01 2.56326586e-01 1.16802907e+00 -6.85244679e-01 -4.14929062e-01 8.73054385e-01 1.40519571e+00 2.63001714e-02 4.03324604e-01 1.33726686e-01 1.28080237e+00 4.19135332e-01 1.04159601e-01 1.97241738e-01 2.88584232e-01 4.27620471e-01 4.98831540e-01 -1.92312822e-01 2.84469761e-02 -6.79270089e-01 4.17752177e-01 1.60432422e+00 1.23042531e-01 -2.78843045e-01 -8.91002417e-01 2.15388864e-01 -1.93718719e+00 -8.27380002e-01 -1.12559572e-01 1.85906112e+00 2.75480539e-01 -5.23475334e-02 -2.65236050e-02 2.72956371e-01 9.29347694e-01 5.51310360e-01 -6.34685397e-01 -1.26836717e-01 -3.65954302e-02 -6.05549887e-02 2.51935035e-01 5.70155561e-01 -8.96710455e-01 9.90279138e-01 5.16647720e+00 5.45238614e-01 -9.59278345e-01 3.84122506e-02 2.10213974e-01 5.72420716e-01 -6.21459663e-01 1.50752828e-01 -1.18571661e-01 6.68935180e-01 5.71406424e-01 -3.49727958e-01 7.92405009e-01 9.01153326e-01 -1.83235809e-01 7.38827944e-01 -9.53843355e-01 1.21384573e+00 4.05898020e-02 -1.07127643e+00 1.57434404e-01 2.66957313e-01 5.51862717e-01 -2.44960457e-01 3.47108245e-02 5.88621438e-01 3.77214700e-01 -9.73732948e-01 4.25199699e-03 4.13039953e-01 6.85016632e-01 -8.11333597e-01 8.48313570e-01 2.84792244e-01 -1.47426224e+00 -8.47184751e-03 -6.62678838e-01 9.38584730e-02 -1.28188491e-01 5.06142080e-01 -5.44916153e-01 6.36114120e-01 4.81316060e-01 1.17990077e+00 -8.81619215e-01 5.71036100e-01 -6.12870693e-01 7.99074233e-01 -9.72313583e-02 -3.79425511e-02 3.32852900e-01 -8.59483600e-01 7.45001316e-01 7.73872614e-01 6.01887666e-02 3.51428939e-03 5.13485670e-01 9.66746986e-01 -1.18125752e-01 3.52042437e-01 -9.05388892e-01 -6.27982378e-01 5.25724828e-01 1.32774806e+00 -7.25291789e-01 -1.14118256e-01 -3.84269774e-01 9.96997952e-01 6.07231796e-01 7.71915972e-01 -6.33185804e-01 -5.49279153e-01 3.10092479e-01 -1.31079897e-01 2.83800393e-01 -4.43972319e-01 4.19187337e-01 -1.44188082e+00 6.51021972e-02 -8.06568921e-01 5.30773699e-01 -5.90510130e-01 -1.44710326e+00 7.01887131e-01 -1.49308056e-01 -1.13925433e+00 -1.91198111e-01 -6.37870193e-01 -8.25134099e-01 4.19877172e-01 -1.12183487e+00 -1.22827744e+00 -4.72763866e-01 8.33334029e-01 -6.03738502e-02 -3.48050863e-01 8.06165576e-01 2.43493587e-01 -7.87613750e-01 8.16877306e-01 4.42957640e-01 6.97048604e-01 3.01104486e-01 -1.36053276e+00 1.84175730e-01 7.53717899e-01 5.35395265e-01 7.62353182e-01 3.46386462e-01 -6.66474640e-01 -1.76208127e+00 -1.14677322e+00 2.09446907e-01 5.14975488e-02 9.94772375e-01 -8.30290020e-01 -1.16217411e+00 1.00140274e+00 7.04292953e-02 2.77416766e-01 6.63657308e-01 3.68572682e-01 -5.22652745e-01 -2.11325347e-01 -8.36084843e-01 6.40534222e-01 8.82270038e-01 -8.24049115e-01 -3.46965313e-01 5.04949927e-01 1.04228616e+00 -1.24611355e-01 -1.13024414e+00 2.25610197e-01 4.41422492e-01 -6.03456318e-01 9.71518278e-01 -7.61032760e-01 5.16246371e-02 -3.11948180e-01 -8.30900222e-02 -1.59033573e+00 -7.63305187e-01 -4.56030518e-01 -3.66713256e-01 1.28739691e+00 7.75981918e-02 -9.52092052e-01 6.33145273e-01 1.87872484e-01 1.92967877e-01 -5.86749077e-01 -5.83150089e-01 -7.77856588e-01 4.22725268e-02 3.39583009e-02 7.82757580e-01 1.40499115e+00 -1.91965431e-01 6.85841501e-01 -3.82324159e-01 3.55970472e-01 5.98029613e-01 2.45659500e-01 8.12802255e-01 -1.30536973e+00 -2.93788880e-01 -4.90606964e-01 -8.16114545e-01 -7.96023011e-01 5.58852077e-01 -1.43405664e+00 -3.98281395e-01 -1.62724483e+00 8.76698792e-02 -2.44516805e-01 -5.22170842e-01 4.52738225e-01 -3.92848134e-01 -3.48559707e-01 1.95967570e-01 2.62591541e-01 -4.79735732e-01 1.07260501e+00 1.25675631e+00 -5.25981545e-01 -3.69487911e-01 -3.31725270e-01 -5.43898940e-01 5.56715012e-01 8.90644431e-01 -4.24559861e-01 -7.20397949e-01 -2.08388671e-01 2.65626878e-01 -1.05226012e-02 3.14295113e-01 -6.46972895e-01 2.28764310e-01 6.22086972e-02 4.71864194e-02 -2.62783140e-01 -5.74368350e-02 -1.00979805e+00 1.89868912e-01 5.39931297e-01 -1.17094964e-01 2.31407136e-01 -8.57391283e-02 1.11814702e+00 -2.60497123e-01 -3.29678357e-02 5.37414789e-01 1.16811745e-01 -5.87313056e-01 8.14919114e-01 -2.22354457e-02 6.18976653e-02 6.98430538e-01 -2.50412881e-01 -4.44376357e-02 -5.85542262e-01 -8.20910513e-01 4.26390052e-01 4.96747524e-01 4.73492086e-01 8.13726187e-01 -1.81391525e+00 -6.34093821e-01 4.25557226e-01 2.62487113e-01 -4.72243316e-02 2.59918630e-01 7.61464775e-01 -4.16351557e-01 1.13841996e-01 -1.24247648e-01 -6.06546223e-01 -1.03834474e+00 1.14985132e+00 2.30830505e-01 -3.41379195e-01 -1.02899289e+00 4.36856508e-01 5.38952887e-01 -7.07419932e-01 1.60870761e-01 -1.55661896e-01 -3.59395087e-01 -5.51353507e-02 1.46159679e-01 1.53245300e-01 -3.86888057e-01 -7.26801634e-01 -1.86012343e-01 6.44223809e-01 4.84433509e-02 4.25153166e-01 1.31802714e+00 -3.48356143e-02 -3.88285100e-01 5.37773848e-01 1.42824876e+00 6.89066350e-02 -1.03237128e+00 -3.55603218e-01 -1.85466319e-01 -2.71982521e-01 3.79713714e-01 -5.52854650e-02 -1.61224055e+00 9.61688459e-01 5.16040325e-01 4.09645855e-01 9.98685539e-01 -1.01181112e-01 5.62161088e-01 6.35773718e-01 7.90423676e-02 -7.70515144e-01 3.92538339e-01 1.59731552e-01 9.53220546e-01 -1.27847803e+00 1.34442881e-01 -4.86700416e-01 -5.03852725e-01 1.02634692e+00 5.74714482e-01 -5.00434577e-01 1.03879535e+00 -2.98019916e-01 -2.92393804e-01 -5.76177537e-01 -3.50433201e-01 -3.45201194e-02 5.70962071e-01 6.37814283e-01 1.41372755e-01 2.18148082e-01 -9.78454575e-02 6.64859891e-01 -2.02728987e-01 -7.34366655e-01 3.85281175e-01 4.25201803e-01 -3.65787745e-02 -8.95108581e-01 5.04410528e-02 4.23434138e-01 8.89436379e-02 -1.69240922e-01 -6.26357853e-01 1.02631879e+00 -3.12557608e-01 8.33882153e-01 -7.74641857e-02 -6.36014163e-01 1.09602965e-01 -2.10299373e-01 1.38303161e-01 -6.24246657e-01 -6.98296055e-02 6.22495078e-02 -3.65818888e-01 -4.78599817e-01 -3.02871943e-01 -2.46545911e-01 -1.22506773e+00 -2.38459647e-01 -6.69908106e-01 4.86304671e-01 2.00410560e-01 5.50529599e-01 4.84118402e-01 6.27696753e-01 8.73683751e-01 -3.65224421e-01 -3.70295554e-01 -8.74623716e-01 -1.05587685e+00 6.42651498e-01 2.37985998e-01 -7.71211922e-01 -6.50642514e-01 -2.49979883e-01]	[7.22027063369751, 6.255685806274414]
10deef70-61a0-4864-bcb9-6b501b429fc5	audio-visual-scene-analysis-with-self	1804.03641	null	http://arxiv.org/abs/1804.03641v2	http://arxiv.org/pdf/1804.03641v2.pdf	Audio-Visual Scene Analysis with Self-Supervised Multisensory Features	The thud of a bouncing ball, the onset of speech as lips open -- when visual and audio events occur together, it suggests that there might be a common, underlying event that produced both signals. In this paper, we argue that the visual and audio components of a video signal should be modeled jointly using a fused multisensory representation. We propose to learn such a representation in a self-supervised way, by training a neural network to predict whether video frames and audio are temporally aligned. We use this learned representation for three applications: (a) sound source localization, i.e. visualizing the source of sound in a video; (b) audio-visual action recognition; and (c) on/off-screen audio source separation, e.g. removing the off-screen translator's voice from a foreign official's speech. Code, models, and video results are available on our webpage: http://andrewowens.com/multisensory	['Alexei A. Efros', 'Andrew Owens']	2018-04-10	audio-visual-scene-analysis-with-self-1	http://openaccess.thecvf.com/content_ECCV_2018/html/Andrew_Owens_Audio-Visual_Scene_Analysis_ECCV_2018_paper.html	http://openaccess.thecvf.com/content_ECCV_2018/papers/Andrew_Owens_Audio-Visual_Scene_Analysis_ECCV_2018_paper.pdf	eccv-2018-9	['audio-source-separation']	['audio']	[ 3.93197328e-01 -3.99510264e-01 -1.00933000e-01 -5.87593997e-03 -1.20704544e+00 -7.98436761e-01 4.54587162e-01 6.88393191e-02 8.75679627e-02 4.00116652e-01 4.91683066e-01 -1.67818084e-01 9.56452861e-02 2.93088481e-02 -9.49650347e-01 -7.15943873e-01 8.58677477e-02 -4.09050375e-01 1.62281454e-01 2.39032865e-01 2.48846874e-01 3.63439679e-01 -2.13765669e+00 5.67953408e-01 1.20823264e-01 1.13653898e+00 3.42024595e-01 1.20427191e+00 1.15635134e-01 1.12000358e+00 -7.13043690e-01 1.78487182e-01 -4.91976738e-03 -5.96686959e-01 -5.25004804e-01 9.52917188e-02 5.02929449e-01 -3.03594112e-01 -1.02407649e-01 1.22935593e+00 4.71883088e-01 8.94051641e-02 3.89829636e-01 -1.71621585e+00 -3.18141043e-01 3.97667378e-01 -5.94381869e-01 3.83914471e-01 9.26998496e-01 1.30917594e-01 8.56762826e-01 -8.70394826e-01 5.63485861e-01 1.05594051e+00 4.40517247e-01 4.43581164e-01 -1.18856990e+00 -5.86685598e-01 4.89378534e-02 3.09565872e-01 -1.32221889e+00 -1.15335417e+00 1.04676211e+00 -6.61095321e-01 8.29630673e-01 5.39857209e-01 5.90958118e-01 1.47200906e+00 -4.56772372e-02 9.82603788e-01 8.07867706e-01 -7.09868789e-01 -3.26904468e-02 2.17199251e-01 -2.32196540e-01 1.69143036e-01 -4.20473069e-01 2.40278170e-01 -1.03313053e+00 -3.21846753e-01 6.62626982e-01 -1.44965932e-01 -5.61058760e-01 -8.02330375e-02 -1.19517946e+00 3.74478072e-01 -2.83802360e-01 4.60837483e-01 -2.96178639e-01 3.50338519e-01 1.88155621e-01 3.55970860e-01 3.95664841e-01 -4.39333767e-02 -2.74417758e-01 -5.41433156e-01 -8.15180480e-01 -7.37641081e-02 6.22809172e-01 6.71418667e-01 2.82958806e-01 2.29922056e-01 3.95929903e-01 8.96705449e-01 6.85057759e-01 3.74321133e-01 5.86759746e-01 -1.12491918e+00 1.15546957e-01 -1.27214789e-01 2.86751509e-01 -7.41026342e-01 -2.36987352e-01 3.21793139e-01 -1.23042561e-01 4.61666882e-01 4.49015975e-01 -4.75617141e-01 -7.06763864e-01 1.81792283e+00 3.82863075e-01 7.96342432e-01 1.81068759e-02 1.08382344e+00 8.64239991e-01 9.05636072e-01 -8.10656622e-02 -5.54090858e-01 1.45169890e+00 -6.46549404e-01 -1.09097004e+00 -2.11059853e-01 -6.27028123e-02 -1.15467560e+00 7.99069405e-01 5.62007427e-01 -1.26613128e+00 -7.21975207e-01 -8.49044323e-01 8.78555253e-02 -1.10826895e-01 1.70829430e-01 1.72222629e-01 3.32586884e-01 -9.99834836e-01 2.24907711e-01 -8.28006148e-01 -4.48222876e-01 -1.42627865e-01 6.26603365e-02 -3.72100443e-01 4.34861720e-01 -8.59171033e-01 4.76810157e-01 -9.85925347e-02 -9.64510888e-02 -1.12312162e+00 -3.39449167e-01 -9.16502118e-01 -1.38782650e-01 3.85163695e-01 -3.34211171e-01 1.68361473e+00 -1.65735698e+00 -1.61993921e+00 8.17972541e-01 -4.93037641e-01 -8.88460949e-02 -1.32662160e-02 -4.39614385e-01 -9.85670567e-01 4.80659246e-01 1.72273517e-01 4.39986318e-01 1.52143824e+00 -1.50457525e+00 -9.23820972e-01 -3.43752950e-01 -2.34521821e-01 3.30695659e-01 8.02697912e-02 7.83604562e-01 -2.87062645e-01 -7.90133595e-01 -8.67403485e-03 -6.78957999e-01 5.65914810e-01 -9.51075852e-02 -3.88572812e-01 -1.60415500e-01 9.81991649e-01 -7.39602923e-01 9.17229593e-01 -2.48994064e+00 9.69651416e-02 -1.32655129e-01 -1.34117350e-01 -7.77763724e-02 -1.83260009e-01 3.56261045e-01 -4.62026119e-01 -8.76971036e-02 3.66382450e-01 -4.20492887e-01 -3.83986145e-01 -3.13918322e-01 -5.96430361e-01 6.49010062e-01 -1.47838458e-01 3.50253016e-01 -9.54993248e-01 -3.01894456e-01 1.11817025e-01 7.72452950e-01 -4.34645489e-02 4.07942533e-01 -6.95245154e-03 6.26403034e-01 4.71900031e-02 8.95274818e-01 2.73546100e-01 4.68442217e-02 -6.98845983e-02 -2.61146009e-01 -2.77361840e-01 3.67380708e-01 -1.48264658e+00 1.85986722e+00 -2.66629577e-01 1.22767222e+00 5.96154809e-01 -4.50496674e-01 7.23886728e-01 9.25467849e-01 6.42403483e-01 -4.30767149e-01 1.97249129e-01 2.01993436e-01 -1.24524094e-01 -9.11009252e-01 4.24352318e-01 -2.64869444e-02 2.36920774e-01 6.43437862e-01 2.09930763e-01 -5.86137660e-02 -1.34407535e-01 3.79187018e-02 8.39228213e-01 2.23879799e-01 2.13166848e-01 2.83653736e-01 2.61230111e-01 -4.23531950e-01 3.13740164e-01 3.37479353e-01 -4.44633096e-01 8.20198894e-01 3.05885643e-01 1.04468025e-01 -6.21080577e-01 -1.02680433e+00 1.25499025e-01 1.30754375e+00 2.25973934e-01 -5.63861310e-01 -6.14614189e-01 -1.04006864e-01 -1.21260650e-01 6.32650733e-01 -2.30954587e-01 -5.22314273e-02 -4.32482034e-01 9.97456070e-03 5.03550828e-01 5.07378399e-01 -3.59871835e-01 -1.12446356e+00 -8.01960528e-01 2.34888233e-02 -6.97799206e-01 -1.13796258e+00 -6.25737309e-01 3.91085863e-01 -3.57412666e-01 -9.59617019e-01 -6.73254728e-01 -5.58314800e-01 7.51468539e-02 4.82087970e-01 6.18046641e-01 -3.90666664e-01 -2.09360123e-01 1.04857087e+00 -2.38009244e-01 -6.61824942e-01 -5.26669204e-01 -8.46947491e-01 4.27866161e-01 5.21692157e-01 3.01756740e-01 -6.06728733e-01 -4.21780914e-01 2.93654799e-01 -7.07732856e-01 1.68499537e-02 -8.91212001e-02 2.39947394e-01 5.56405365e-01 -7.15998327e-03 3.66602808e-01 3.21172833e-01 6.83723748e-01 -6.35677516e-01 -4.56908435e-01 9.58022103e-02 1.82469055e-01 -6.68196082e-01 2.37123609e-01 -8.59015644e-01 -9.50728118e-01 2.51857013e-01 -1.97057985e-02 -1.04423249e+00 -7.25549877e-01 6.80981055e-02 -1.52782544e-01 1.76204756e-01 6.26961708e-01 1.40928477e-01 -3.86874937e-02 -7.02231765e-01 2.38122255e-01 1.10403860e+00 7.78428495e-01 -2.29014903e-01 1.93412632e-01 6.15090847e-01 -4.76473570e-01 -1.07907772e+00 -3.89791757e-01 -6.73519611e-01 -3.28356475e-01 -7.36474276e-01 9.65460479e-01 -1.18399262e+00 -8.78947556e-01 6.55663133e-01 -1.44494331e+00 -4.36840355e-01 -1.95249408e-01 8.97483230e-01 -8.16533566e-01 6.88558444e-02 -3.54375720e-01 -1.16342545e+00 3.03034544e-01 -1.17676508e+00 1.28818882e+00 4.57748264e-01 -4.29661334e-01 -6.24686241e-01 3.16657037e-01 4.29927558e-01 -1.25467986e-01 5.76563738e-02 2.44371429e-01 -6.14262283e-01 -2.39809304e-01 -7.81599283e-02 1.09547205e-01 4.01480049e-01 5.33873379e-01 4.33469146e-01 -1.61271393e+00 -1.19123042e-01 2.31242821e-01 -2.97490239e-01 3.90915364e-01 8.42975438e-01 9.06526744e-01 -1.97632834e-01 -2.63384372e-01 5.35821080e-01 1.03706110e+00 7.07171142e-01 2.53313303e-01 -9.36136916e-02 5.94747901e-01 7.46394157e-01 4.64253813e-01 5.20328343e-01 1.25004411e-01 1.03607786e+00 6.15032554e-01 2.05194741e-01 -4.12088662e-01 -3.70851934e-01 8.19995522e-01 6.06347144e-01 -2.77971104e-02 -3.35218459e-01 -7.77413547e-01 6.03567958e-01 -1.65446651e+00 -1.03662443e+00 -3.39590944e-02 2.08500433e+00 5.98589599e-01 -1.92293391e-01 3.94073576e-01 2.42120951e-01 9.98701811e-01 2.11217955e-01 -5.21528721e-01 -3.43942404e-01 -1.05412565e-01 -1.36731267e-01 3.36314775e-02 5.55274725e-01 -1.16440833e+00 5.22376359e-01 6.34279442e+00 6.43413723e-01 -1.52156246e+00 3.20794880e-01 1.88194618e-01 -5.59214532e-01 -2.17892691e-01 -8.52608979e-02 -6.54965281e-01 5.70436418e-01 1.25299633e+00 -1.57319326e-02 4.76200700e-01 4.98821855e-01 4.76752013e-01 -4.38292921e-01 -1.30194342e+00 1.45187628e+00 4.51417506e-01 -1.02718186e+00 -4.78224725e-01 -1.09246030e-01 1.55472040e-01 2.98064947e-02 -8.21808353e-02 -2.59240508e-01 2.96982694e-02 -9.14951980e-01 1.31416094e+00 5.02859414e-01 7.32526302e-01 -3.28949213e-01 -2.11069971e-01 3.16292673e-01 -1.27917421e+00 -8.49591494e-02 3.59186053e-01 8.77686217e-02 3.93711388e-01 1.19042717e-01 -5.46856880e-01 2.08611757e-01 1.06227648e+00 6.09143555e-01 -1.77340791e-01 1.11174607e+00 -3.76758039e-01 6.63450956e-01 -3.16861480e-01 3.83624166e-01 -2.82345742e-01 2.97458380e-01 1.18107998e+00 1.08768702e+00 4.68065947e-01 -3.81395593e-02 -1.02452070e-01 6.58490181e-01 1.60934508e-01 -5.72478250e-02 -9.22215462e-01 -1.26078799e-01 5.39865315e-01 1.10609269e+00 -7.23086476e-01 -3.71133499e-02 -5.78230739e-01 9.34800923e-01 -3.08390051e-01 5.68881333e-01 -9.09769893e-01 -4.38703805e-01 8.07220519e-01 -1.76893622e-01 2.91661203e-01 6.73714429e-02 1.07422680e-01 -9.98595119e-01 1.16404779e-01 -9.28118110e-01 1.64660066e-01 -1.65381730e+00 -6.58426344e-01 5.57029426e-01 -7.13135228e-02 -1.64395130e+00 -7.61687458e-01 -2.65509337e-01 -6.60793543e-01 7.27453291e-01 -1.16399384e+00 -9.52151120e-01 -1.29179865e-01 1.01249146e+00 6.10958457e-01 -1.35180846e-01 7.01279283e-01 3.37531000e-01 -4.18923736e-01 1.53968588e-01 -8.09639394e-02 4.37395051e-02 1.04173207e+00 -1.02524853e+00 -1.15657210e-01 8.97604644e-01 6.94356263e-01 2.19087675e-01 9.42176521e-01 -5.52113235e-01 -1.36135650e+00 -4.92918491e-01 7.43851244e-01 -3.60674977e-01 8.43492270e-01 -2.66248822e-01 -8.41867626e-01 8.28976810e-01 4.90718931e-01 1.43277943e-01 9.77246761e-01 -1.83929175e-01 -3.99324536e-01 -1.72846362e-01 -7.57604420e-01 4.04832304e-01 4.97009665e-01 -1.10252130e+00 -7.79866219e-01 3.34983826e-01 5.60122311e-01 -4.13610309e-01 -4.92101640e-01 -5.79257682e-02 8.53760839e-01 -1.07532775e+00 1.01241601e+00 -3.19637299e-01 2.27403805e-01 -3.67474049e-01 -3.99754107e-01 -1.32552123e+00 1.42533287e-01 -1.00165570e+00 -4.61042434e-01 1.29745328e+00 6.63133487e-02 -3.50873083e-01 -3.43536921e-02 2.35675201e-01 4.61136028e-02 -1.83373138e-01 -1.13885188e+00 -6.53826833e-01 -5.97864807e-01 -9.14665818e-01 3.28752339e-01 8.90260756e-01 2.98553556e-01 2.95285463e-01 -6.78131998e-01 4.77237284e-01 3.78931910e-01 2.89633800e-03 5.60007453e-01 -1.15193009e+00 -3.99679005e-01 -3.16255480e-01 -2.74211287e-01 -9.85428035e-01 1.63505793e-01 -4.27970797e-01 2.04835579e-01 -1.10673237e+00 -2.23762780e-01 1.91643581e-01 -4.44077075e-01 4.89353657e-01 2.54095823e-01 1.33269757e-01 3.88920873e-01 3.88131529e-01 -3.21159363e-01 1.01836726e-01 8.38175356e-01 1.48920680e-03 -3.79312664e-01 2.04465002e-01 -6.37760401e-01 1.03715348e+00 6.48416400e-01 -4.22611475e-01 -3.97977561e-01 -4.89056945e-01 1.35632098e-01 9.46260929e-01 7.28927791e-01 -8.13349307e-01 5.19753039e-01 -1.34846374e-01 2.01962233e-01 -3.78318101e-01 9.68266368e-01 -8.85560513e-01 2.42173210e-01 -3.01522743e-02 -3.30988407e-01 -5.12895957e-02 5.35344720e-01 6.50809646e-01 -5.78655005e-01 -2.59690970e-01 6.91378415e-01 5.84091805e-02 -6.05326533e-01 -1.72625631e-01 -8.07685852e-01 -3.25279087e-01 1.09059227e+00 -3.36033911e-01 -3.03827375e-01 -8.12200129e-01 -1.06026554e+00 -3.31989437e-01 7.29655847e-02 7.87765026e-01 8.32749903e-01 -1.37050283e+00 -3.78243327e-01 4.35572565e-01 -1.28043532e-01 -4.94783282e-01 4.30137873e-01 9.58920419e-01 1.41314149e-01 1.61337614e-01 -1.64254352e-01 -8.70225966e-01 -1.88688552e+00 3.23112607e-01 4.61629570e-01 6.68464303e-01 -3.91219109e-01 1.04676652e+00 6.54314160e-02 3.35819483e-01 6.26919746e-01 -3.13572198e-01 -3.04361075e-01 4.93284494e-01 8.38936329e-01 5.02522051e-01 -1.52837291e-01 -1.00558925e+00 -5.18685460e-01 5.48573911e-01 3.27445388e-01 -5.71943343e-01 1.14153826e+00 -5.79587460e-01 8.20562318e-02 1.29845607e+00 1.20933104e+00 4.76900876e-01 -1.28897989e+00 -1.39763758e-01 -3.43829364e-01 -5.48057020e-01 1.31970212e-01 -7.54583299e-01 -8.44372928e-01 1.02952886e+00 8.16440225e-01 6.81825817e-01 1.37690675e+00 3.41188163e-01 3.26693058e-01 -9.21071917e-02 9.85973328e-03 -9.46863592e-01 2.61795253e-01 1.12137139e-01 1.08149886e+00 -1.20225477e+00 -3.48199219e-01 -8.23598355e-02 -7.31943011e-01 1.31085157e+00 3.90651524e-01 3.17110062e-01 7.46029139e-01 6.24534369e-01 4.18475658e-01 -1.73112769e-02 -1.00040567e+00 -3.33813101e-01 3.71397197e-01 6.85921073e-01 4.31996971e-01 -2.20166929e-02 6.21576965e-01 5.10833859e-01 7.69397570e-03 1.00991681e-01 5.99093020e-01 9.00082886e-01 -3.66520196e-01 -6.27220809e-01 -9.41160977e-01 -1.88514292e-02 -6.77383125e-01 6.65777177e-02 -4.64732140e-01 3.24052572e-01 1.38270393e-01 1.42744613e+00 2.49329060e-01 -3.77952814e-01 2.42114380e-01 4.11290944e-01 5.30008614e-01 -4.35495853e-01 -3.32633823e-01 9.44053948e-01 -3.97471115e-02 -7.44275093e-01 -8.35199118e-01 -9.31428492e-01 -9.66302931e-01 2.99715221e-01 -1.42176941e-01 -1.18957736e-01 8.55461419e-01 6.83387995e-01 3.09601814e-01 4.99529511e-01 5.46072125e-01 -1.19350719e+00 -1.08940184e-01 -9.57373321e-01 -8.24339747e-01 2.91989535e-01 1.01340258e+00 -5.83824158e-01 -7.51744270e-01 4.57821757e-01]	[14.602190971374512, 5.0448455810546875]
fc232446-33a1-4787-838f-c6856656c3a9	multiple-imputation-with-neural-network	2211.13297	null	https://arxiv.org/abs/2211.13297v2	https://arxiv.org/pdf/2211.13297v2.pdf	Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data	Missing data are ubiquitous in real world applications and, if not adequately handled, may lead to the loss of information and biased findings in downstream analysis. Particularly, high-dimensional incomplete data with a moderate sample size, such as analysis of multi-omics data, present daunting challenges. Imputation is arguably the most popular method for handling missing data, though existing imputation methods have a number of limitations. Single imputation methods such as matrix completion methods do not adequately account for imputation uncertainty and hence would yield improper statistical inference. In contrast, multiple imputation (MI) methods allow for proper inference but existing methods do not perform well in high-dimensional settings. Our work aims to address these significant methodological gaps, leveraging recent advances in neural network Gaussian process (NNGP) from a Bayesian viewpoint. We propose two NNGP-based MI methods, namely MI-NNGP, that can apply multiple imputations for missing values from a joint (posterior predictive) distribution. The MI-NNGP methods are shown to significantly outperform existing state-of-the-art methods on synthetic and real datasets, in terms of imputation error, statistical inference, robustness to missing rates, and computation costs, under three missing data mechanisms, MCAR, MAR, and MNAR.	['Qi Long', 'Zhiqi Bu', 'Zongyu Dai']	2022-11-23	null	null	null	null	['matrix-completion']	['methodology']	[ 4.29373264e-01 -2.40611345e-01 -4.19875860e-01 -4.13806856e-01 -9.95182216e-01 -2.08558768e-01 4.11060423e-01 1.91872176e-02 -2.19746381e-01 1.38217247e+00 3.88469189e-01 -3.68821114e-01 -5.45709014e-01 -8.41705263e-01 -9.74566519e-01 -8.18090916e-01 2.18433127e-01 5.91979504e-01 -6.40773475e-01 3.41755480e-01 1.89674228e-01 7.59944841e-02 -1.28659415e+00 1.58199489e-01 1.25687957e+00 4.88075227e-01 -1.08041838e-01 1.82055011e-01 -8.86742026e-02 3.79280061e-01 -2.26537675e-01 -6.14127517e-01 -5.81101254e-02 -1.72488421e-01 -1.10089265e-01 -5.08862793e-01 -1.21346653e-01 -3.04476053e-01 -1.07971318e-01 6.91139042e-01 6.39254510e-01 -3.81340384e-02 1.05862701e+00 -1.40220737e+00 -7.31083155e-01 6.56776071e-01 -9.84967172e-01 -4.29281533e-01 1.46844536e-01 3.69681418e-02 4.16536182e-01 -1.15994620e+00 3.76594663e-01 1.40794718e+00 1.11100757e+00 2.75392711e-01 -1.71015906e+00 -8.63587499e-01 -1.02642782e-01 -2.28261963e-01 -1.36465001e+00 -6.11142218e-01 3.99444610e-01 -6.21207058e-01 5.44353604e-01 1.08392246e-01 -3.07632498e-02 1.69129837e+00 4.84055221e-01 4.56215650e-01 1.14998221e+00 5.27233854e-02 5.94861507e-01 -3.92585605e-01 8.36234689e-02 -3.63274753e-01 8.48300040e-01 3.33001941e-01 -6.48316860e-01 -7.15904295e-01 6.50964737e-01 5.47891676e-01 1.10768683e-01 -1.74805135e-01 -1.61091626e+00 8.24363112e-01 -2.81781882e-01 -4.43520904e-01 -8.78533363e-01 7.93726370e-02 2.78474003e-01 -1.04339812e-02 6.22989058e-01 1.46258287e-02 -6.86582029e-01 -2.75173724e-01 -1.01081967e+00 4.66480881e-01 7.17601657e-01 8.98468614e-01 3.96176755e-01 3.37041020e-02 -5.21430552e-01 8.73837888e-01 3.72884661e-01 8.50704312e-01 -3.26480120e-02 -1.06910586e+00 8.46792936e-01 3.20853502e-01 6.53088212e-01 -9.03275073e-01 -5.67194045e-01 -2.04564795e-01 -1.84626627e+00 -1.70521230e-01 6.86034203e-01 -5.28612375e-01 -7.90613890e-01 1.96761370e+00 3.56712550e-01 4.56871867e-01 3.18761736e-01 6.47225499e-01 7.58997977e-01 4.26798165e-01 5.79607189e-01 -4.14845139e-01 1.20066679e+00 -9.94100273e-02 -8.95456612e-01 -2.19459891e-01 1.87841862e-01 -5.38521409e-01 6.79076791e-01 5.17581344e-01 -1.10613692e+00 -2.90620178e-01 -4.49591041e-01 1.40321463e-01 -1.62758350e-01 1.37637258e-01 7.36973107e-01 4.79668170e-01 -2.92770803e-01 5.00951111e-01 -9.86471236e-01 -3.87348533e-02 6.04811668e-01 3.56766790e-01 -5.14453888e-01 -2.71175742e-01 -1.00088978e+00 6.13319933e-01 7.78683946e-02 6.73043549e-01 -7.16826200e-01 -1.25380003e+00 -8.16534400e-01 2.09491193e-01 1.13430880e-01 -1.06652176e+00 7.81823575e-01 -2.45065406e-01 -1.16951072e+00 2.41997853e-01 -7.32897639e-01 -1.80869326e-01 6.38936341e-01 -1.18265487e-01 -2.87376076e-01 -5.23499966e-01 1.26086324e-01 3.79479140e-01 6.43754900e-01 -1.20041978e+00 -1.53558433e-01 -7.68270910e-01 -7.70205617e-01 -1.51462778e-01 1.35350868e-01 -1.51147857e-01 1.74509361e-01 -7.55448103e-01 5.02245545e-01 -6.47531450e-01 -4.19313401e-01 -3.02421480e-01 -6.28175735e-01 2.08793759e-01 2.66488612e-01 -8.75339687e-01 1.08792722e+00 -1.96035790e+00 3.07489306e-01 -5.44812493e-02 1.43606048e-02 -8.40829983e-02 -5.21355271e-02 6.28113806e-01 6.06702156e-02 1.88115790e-01 -7.62465477e-01 -5.15270293e-01 1.50606617e-01 2.89474070e-01 -3.25356513e-01 4.99822050e-01 1.91477671e-01 8.56422663e-01 -6.33558512e-01 -1.32800162e-01 1.72487363e-01 7.10118890e-01 -4.15350378e-01 1.30546376e-01 -3.78705524e-02 1.03008246e+00 -1.76774368e-01 9.23017740e-01 1.29512763e+00 -1.30784422e-01 2.86112666e-01 1.55065864e-01 -1.29848644e-01 -1.84523478e-01 -1.37770379e+00 1.45198226e+00 -2.35742241e-01 2.06574295e-02 2.29113623e-01 -1.01800299e+00 9.56743956e-01 3.15779477e-01 3.81406486e-01 -4.58589822e-01 -2.96485960e-01 1.81890428e-01 -1.08632013e-01 -5.82853794e-01 2.84105986e-01 -2.58623898e-01 -2.66342252e-01 1.85025439e-01 -3.18500608e-01 4.98889357e-01 -7.43915588e-02 -2.27807581e-01 1.04837227e+00 4.03925538e-01 2.03716844e-01 -2.13230196e-02 9.83296856e-02 -2.51958430e-01 1.36936724e+00 1.20064831e+00 8.48352164e-02 9.35711980e-01 7.83721566e-01 -2.95254290e-01 -1.06070328e+00 -1.47983813e+00 -6.02720976e-01 7.74744868e-01 -2.42074460e-01 2.19186708e-01 -2.70256937e-01 -2.44421363e-02 6.07321441e-01 6.99161768e-01 -3.86551142e-01 4.27612886e-02 -1.82733133e-01 -1.85040677e+00 6.95003271e-01 5.27097404e-01 2.87157059e-01 -9.38494444e-01 -8.34756158e-03 5.36896706e-01 -4.91495013e-01 -1.00789750e+00 2.50280499e-01 1.10729106e-01 -1.06984460e+00 -9.38172638e-01 -6.90040350e-01 3.75667252e-02 6.21021867e-01 8.40042084e-02 1.10539627e+00 -4.60397989e-01 1.44196004e-01 -1.88540876e-01 -6.27426282e-02 -6.39358997e-01 -3.32223594e-01 3.23801003e-02 3.50901902e-01 2.37909034e-02 8.03936422e-01 -8.08510363e-01 -5.76933980e-01 2.38928750e-01 -9.31572556e-01 1.34163722e-01 7.02049315e-01 1.20435452e+00 6.93046629e-01 -2.43002757e-01 1.37332547e+00 -1.00680304e+00 4.40278947e-01 -1.17627656e+00 -6.08924091e-01 2.21588507e-01 -4.26667631e-01 -4.51677479e-02 4.71317559e-01 -3.39694232e-01 -1.35414767e+00 -3.62515002e-02 -2.38995120e-01 -1.71442702e-01 -4.90216315e-01 1.04063964e+00 -4.10466790e-01 5.14206886e-01 3.54512662e-01 1.74498722e-01 2.31540278e-01 -7.31482387e-01 -5.69183081e-02 8.40787828e-01 4.62696999e-01 -6.46335900e-01 4.58540529e-01 5.54965675e-01 6.01972520e-01 -6.12113774e-01 -7.15072930e-01 -3.42428654e-01 -7.21185327e-01 3.61227453e-01 5.92199028e-01 -1.31129646e+00 -1.06617451e+00 6.76190734e-01 -1.12024856e+00 -6.60120100e-02 1.42177328e-01 8.74096513e-01 -5.61637342e-01 3.93956602e-01 -5.92302084e-01 -1.16403103e+00 -3.47698063e-01 -1.08204532e+00 1.01464832e+00 -3.17541026e-02 -2.48038933e-01 -7.51897573e-01 8.43174234e-02 4.51750666e-01 4.91245121e-01 7.11982369e-01 1.09839463e+00 -4.06470984e-01 -2.12716237e-01 -8.28251466e-02 -3.97659183e-01 -1.02642544e-01 1.77532911e-01 -1.39261661e-02 -9.12281513e-01 -3.48659195e-02 -3.31905067e-01 2.70104725e-02 8.32916558e-01 1.11757755e+00 1.33358359e+00 -2.78103322e-01 -3.19944173e-01 6.17904961e-01 1.26317990e+00 -2.00936615e-01 9.66054320e-01 -7.44834691e-02 4.97270703e-01 6.73311174e-01 2.94376701e-01 9.19423759e-01 5.57846367e-01 5.08188188e-01 5.89916408e-01 -7.38535598e-02 5.13674974e-01 -4.24155176e-01 3.95134985e-02 4.63573128e-01 5.71037158e-02 -1.66073054e-01 -7.96248734e-01 4.23437387e-01 -2.35623074e+00 -1.24101448e+00 -8.35405290e-01 2.85148787e+00 8.83548856e-01 -3.08158875e-01 6.71276078e-02 -1.23683199e-01 7.02056348e-01 -3.84366095e-01 -8.53280008e-01 -1.39828011e-01 -5.55338681e-01 -1.70682967e-01 5.85767508e-01 1.20933473e-01 -1.01703262e+00 2.21789911e-01 6.83702421e+00 3.99983436e-01 -1.72054633e-01 1.76968858e-01 8.17804039e-01 -5.14939986e-02 -3.90443832e-01 1.07263446e-01 -9.32333529e-01 9.83081937e-01 1.18524206e+00 2.44207755e-01 2.73198366e-01 3.52209747e-01 9.09668982e-01 -3.55180770e-01 -1.03474116e+00 9.25460041e-01 -3.19758981e-01 -1.36896360e+00 -9.47103426e-02 3.96090269e-01 9.20298278e-01 4.28817198e-02 3.61488275e-02 4.19631422e-01 4.05653447e-01 -1.32433152e+00 7.95557946e-02 1.15702569e+00 5.11300087e-01 -9.17980313e-01 1.15818930e+00 5.34971178e-01 -4.57815379e-01 -1.15392767e-01 -8.21480036e-01 -3.57728928e-01 4.07664210e-01 1.41290581e+00 -1.64342687e-01 7.18601167e-01 6.30758047e-01 6.13250375e-01 -9.03252512e-02 1.20062959e+00 1.26090437e-01 9.08987164e-01 -3.72016281e-01 5.45496225e-01 -2.91431367e-01 -6.90623522e-01 3.85739625e-01 9.19583201e-01 8.65263462e-01 -1.19136930e-01 -1.92081466e-01 1.25634706e+00 -1.15887269e-01 -3.04639846e-01 -7.24441111e-01 2.17225835e-01 7.52498090e-01 9.56546009e-01 -1.14317313e-01 -3.78887006e-03 -5.47054589e-01 4.57287222e-01 6.41372278e-02 7.23245561e-01 -6.76395059e-01 3.56247984e-02 9.42920685e-01 -8.57161134e-02 6.93481555e-03 -2.43484437e-01 -7.88012028e-01 -1.34841156e+00 8.96467716e-02 -9.34721172e-01 4.96410459e-01 -7.15925395e-01 -1.98296714e+00 -3.54452670e-01 1.22348880e-02 -1.06003404e+00 -2.83239603e-01 -3.68593812e-01 -4.64630008e-01 1.21720076e+00 -1.52694249e+00 -1.28478134e+00 -2.14961141e-01 1.40068054e-01 1.50722638e-01 -1.14790939e-01 8.73515129e-01 3.81501853e-01 -8.75646114e-01 2.93295354e-01 1.00150299e+00 -2.03237891e-01 8.28183353e-01 -9.64840233e-01 2.81548560e-01 6.43234789e-01 -4.54284459e-01 7.98433363e-01 6.90281332e-01 -9.98463631e-01 -1.83876324e+00 -1.18363941e+00 9.68789160e-01 -6.23366952e-01 3.04723918e-01 -4.38770324e-01 -1.07671428e+00 7.24195123e-01 -3.39723021e-01 -1.44482315e-01 1.13229120e+00 6.72664225e-01 -3.29889596e-01 -8.17169100e-02 -1.37436080e+00 6.04500473e-01 7.49010205e-01 6.22522868e-02 -2.75150210e-01 2.16108754e-01 4.07992840e-01 -2.05323383e-01 -1.21505332e+00 6.80145919e-01 8.39585185e-01 -7.61235416e-01 1.32411790e+00 -8.79944324e-01 7.22114205e-01 -3.40566218e-01 -3.75048876e-01 -1.15622652e+00 -3.28668892e-01 -4.49659616e-01 -3.61643702e-01 1.48338556e+00 4.58959877e-01 -6.78367198e-01 6.57587171e-01 9.60990191e-01 1.18739769e-01 -2.77171701e-01 -1.41327667e+00 -7.69396067e-01 5.26504576e-01 -6.03150010e-01 1.10914052e+00 8.14368963e-01 -2.27340698e-01 -1.12606503e-01 -9.85087097e-01 2.76872128e-01 1.26660502e+00 -2.48138253e-02 9.87419724e-01 -1.75070620e+00 -1.70199886e-01 6.65251762e-02 -1.74463205e-02 -4.40219522e-01 2.86197007e-01 -5.55276394e-01 -1.68561786e-01 -1.53310335e+00 6.08123541e-01 -5.68276763e-01 -2.40692869e-01 4.39101309e-01 -3.52711767e-01 2.21565202e-01 -2.16107368e-01 2.62614816e-01 -1.50829315e-01 6.85373187e-01 8.14482331e-01 -1.45308420e-01 -3.37527394e-01 3.71226490e-01 -8.64530146e-01 5.49654901e-01 8.03354681e-01 -7.11400568e-01 -7.71287233e-02 -4.35564876e-01 5.75444818e-01 5.42944252e-01 7.30574548e-01 -5.78785539e-01 4.71000634e-02 -6.33771360e-01 8.98340285e-01 -8.96521211e-01 3.44447702e-01 -7.44653821e-01 9.21866834e-01 1.22346468e-01 -2.08184779e-01 5.45408502e-02 1.09363176e-01 8.90110373e-01 4.92485380e-03 -3.33707593e-02 3.41766357e-01 4.78056967e-02 6.42945319e-02 2.14404896e-01 -4.74828571e-01 -2.01299459e-01 6.01707399e-01 -1.34881258e-01 -5.53751349e-01 -3.10392171e-01 -8.18850219e-01 4.55489397e-01 1.29615083e-01 1.28538385e-01 6.35196745e-01 -1.30337310e+00 -1.24906754e+00 2.47497305e-01 1.04742892e-01 5.42307533e-02 6.96427286e-01 1.36314654e+00 1.63100213e-01 3.16366196e-01 -9.66244959e-04 -6.42522216e-01 -6.26471341e-01 5.00014067e-01 -8.75681266e-02 -1.89426377e-01 -4.88608450e-01 -9.09408629e-02 8.33193734e-02 -1.14374828e+00 -1.77287254e-02 -8.65986645e-02 1.35224089e-01 1.03578448e-01 4.86980200e-01 8.07330370e-01 3.51991598e-03 -4.29482400e-01 -1.60735577e-01 3.17297369e-01 3.15552682e-01 1.04381181e-01 1.51875532e+00 -3.98610413e-01 -3.00326526e-01 5.58899164e-01 5.75506806e-01 -3.44548941e-01 -1.35834932e+00 -1.00629814e-01 2.32254830e-03 -4.31747377e-01 -2.66008258e-01 -9.16810036e-01 -5.73240221e-01 8.88474524e-01 1.94218963e-01 -2.34446123e-01 8.26809824e-01 -4.99267161e-01 3.66120368e-01 2.21988991e-01 3.60737324e-01 -8.15503359e-01 -7.38322258e-01 3.37921113e-01 7.60890305e-01 -1.59054494e+00 1.70970842e-01 -2.36337826e-01 -5.31522810e-01 8.46227586e-01 4.09187704e-01 3.57904792e-01 6.86323285e-01 2.94922799e-01 -3.24750870e-01 1.78123310e-01 -8.30346465e-01 2.54744172e-01 -1.09075367e-01 9.64174807e-01 4.82712448e-01 1.84955925e-01 -3.78801644e-01 1.09065688e+00 2.43907616e-01 4.50606585e-01 7.20820069e-01 6.08342886e-01 1.47573799e-01 -1.00059509e+00 -7.22947836e-01 9.52319503e-01 -6.84585333e-01 -1.63103074e-01 1.64785251e-01 4.82915461e-01 -1.65674463e-01 1.18740416e+00 4.41077836e-02 2.94262946e-01 1.54377818e-01 2.45222509e-01 -3.31895910e-02 -1.94980085e-01 -2.85894692e-01 8.53199288e-02 -4.38163504e-02 -2.21518710e-01 -4.03322786e-01 -1.03896451e+00 -7.48753667e-01 -6.96955144e-01 -7.02176318e-02 -7.06333071e-02 6.07820034e-01 1.01795161e+00 8.53969038e-01 2.31274158e-01 3.29270035e-01 -7.61617720e-01 -8.46359313e-01 -1.20425999e+00 -6.22557759e-01 3.38897943e-01 1.86559334e-01 -7.00524867e-01 -3.79324436e-01 -7.23428428e-02]	[7.607182502746582, 4.724435806274414]
83783181-95c0-4b25-a1f6-12e4fafc07fd	deep-learning-based-defect-classification-and-1	2211.02185	null	https://arxiv.org/abs/2211.02185v1	https://arxiv.org/pdf/2211.02185v1.pdf	Deep Learning based Defect classification and detection in SEM images: A Mask R-CNN approach	In this research work, we have demonstrated the application of Mask-RCNN (Regional Convolutional Neural Network), a deep-learning algorithm for computer vision and specifically object detection, to semiconductor defect inspection domain. Stochastic defect detection and classification during semiconductor manufacturing has grown to be a challenging task as we continuously shrink circuit pattern dimensions (e.g., for pitches less than 32 nm). Defect inspection and analysis by state-of-the-art optical and e-beam inspection tools is generally driven by some rule-based techniques, which in turn often causes to misclassification and thereby necessitating human expert intervention. In this work, we have revisited and extended our previous deep learning-based defect classification and detection method towards improved defect instance segmentation in SEM images with precise extent of defect as well as generating a mask for each defect category/instance. This also enables to extract and calibrate each segmented mask and quantify the pixels that make up each mask, which in turn enables us to count each categorical defect instances as well as to calculate the surface area in terms of pixels. We are aiming at detecting and segmenting different types of inter-class stochastic defect patterns such as bridge, break, and line collapse as well as to differentiate accurately between intra-class multi-categorical defect bridge scenarios (as thin/single/multi-line/horizontal/non-horizontal) for aggressive pitches as well as thin resists (High NA applications). Our proposed approach demonstrates its effectiveness both quantitatively and qualitatively.	['Magdy A. Bayoumi', 'Philippe Leray', 'Sandip Halder', 'Kasem Khalil', 'Enrique Dehaerne', 'Bappaditya Dey']	2022-11-03	null	null	null	null	['defect-detection']	['computer-vision']	[ 4.59908307e-01 1.78784236e-01 4.52054292e-01 -4.86408770e-02 -4.82389331e-01 -4.23499823e-01 1.46767631e-01 7.23680496e-01 -1.90796509e-01 4.82788891e-01 -6.84933424e-01 -4.95091856e-01 -2.81729519e-01 -9.49879408e-01 -3.68947774e-01 -9.06742752e-01 2.78021127e-01 9.50069308e-01 3.07434499e-01 -2.31519446e-01 7.71193087e-01 9.95903373e-01 -1.44247139e+00 6.02233350e-01 8.82788181e-01 1.21513307e+00 3.03458035e-01 6.62907481e-01 -1.96853548e-01 2.23853096e-01 -8.28123212e-01 -1.12703219e-01 -3.14128287e-02 -3.44291300e-01 -6.63258970e-01 4.94729787e-01 1.54252917e-01 -1.35232329e-01 2.18779206e-01 1.08248854e+00 1.64961040e-01 -4.46491569e-01 1.15575600e+00 -7.37837374e-01 -3.39561641e-01 3.42197865e-01 -7.64988899e-01 1.23013578e-01 1.22769795e-01 4.83148962e-01 6.34745955e-01 -7.13198423e-01 4.90558118e-01 1.04254794e+00 6.65368497e-01 4.10024256e-01 -1.11171663e+00 -4.53928888e-01 -3.94486248e-01 9.84446779e-02 -1.05339074e+00 -7.52052367e-02 1.00592482e+00 -7.68965662e-01 1.05901825e+00 1.14265241e-01 5.30130088e-01 7.32767522e-01 7.39730060e-01 3.93081516e-01 9.84724283e-01 -6.89911425e-01 3.16945612e-01 7.00789969e-03 3.59839976e-01 7.52677560e-01 6.09264314e-01 -7.53763365e-03 5.96487224e-02 3.46094131e-01 9.60156739e-01 1.59751967e-01 2.02719383e-02 -4.70175408e-02 -8.09529543e-01 7.19549716e-01 2.77704120e-01 8.51681709e-01 -3.93741518e-01 6.29763529e-02 5.19028962e-01 4.05197561e-01 3.54862541e-01 7.19119310e-01 -3.90164047e-01 -1.31497039e-02 -1.11357832e+00 1.07527316e-01 5.51362395e-01 5.33744812e-01 8.21668267e-01 2.38836721e-01 -1.76359951e-01 9.12323415e-01 2.85972774e-01 1.43496767e-01 2.31871545e-01 -6.45548999e-01 2.70182192e-01 1.08277321e+00 1.15063369e-01 -8.59208941e-01 -6.76124930e-01 -3.92600328e-01 -1.06441569e+00 7.58592606e-01 4.40330416e-01 3.57844532e-02 -1.31106663e+00 7.89448380e-01 1.96183790e-02 -7.92149544e-01 -2.86393940e-01 5.46139359e-01 5.46222091e-01 3.67793798e-01 -2.76427358e-01 -2.38558948e-01 1.33056712e+00 -4.80395943e-01 -5.77142477e-01 8.11873525e-02 6.31954789e-01 -5.68325877e-01 1.10315955e+00 8.84638071e-01 -1.05628216e+00 -6.73008680e-01 -1.44249558e+00 1.45122945e-01 -4.73766178e-01 6.03158176e-01 3.38636696e-01 8.15215528e-01 -7.85211205e-01 9.62057829e-01 -1.07879603e+00 -3.01368266e-01 9.21187103e-01 5.95973611e-01 -2.37933159e-01 -2.20931143e-01 -3.94756198e-01 4.61698055e-01 -7.60239884e-02 3.46898228e-01 -9.49347615e-01 -6.45526946e-01 -6.47964299e-01 -2.18621939e-02 1.47238538e-01 -2.14368492e-01 8.34473789e-01 -6.09319508e-01 -1.33463109e+00 1.09304619e+00 8.10085312e-02 -4.41052705e-01 4.72153991e-01 8.18678439e-02 -4.52008307e-01 4.10470320e-03 1.68612078e-02 2.88123101e-01 8.39718342e-01 -1.60710990e+00 -6.39621854e-01 -6.63093150e-01 6.42847344e-02 -4.68287766e-01 -2.87988156e-01 -4.31705788e-02 1.23818271e-01 -2.76978552e-01 6.86060309e-01 -2.72408634e-01 -1.67515948e-01 -6.46897033e-02 -8.61784875e-01 -3.33850861e-01 1.13613343e+00 -6.28466725e-01 1.03111482e+00 -1.90678608e+00 -1.62918732e-01 3.05112213e-01 3.96127433e-01 1.18088804e-01 3.10864955e-01 6.53866768e-01 -2.73692049e-02 9.65609625e-02 -8.01009893e-01 -3.96920949e-01 -1.54149503e-01 -9.51388944e-03 2.85060078e-01 7.68268347e-01 4.34821665e-01 4.70765084e-01 -4.18573648e-01 -1.79098845e-01 5.15440643e-01 -2.67723557e-02 -3.86039227e-01 -3.48897791e-03 -2.44601816e-01 4.60698634e-01 -1.36042103e-01 1.29021120e+00 9.89054859e-01 3.56692709e-02 -1.49601951e-01 -5.69332242e-01 -4.62863922e-01 -2.70388871e-01 -1.00727999e+00 1.24521589e+00 -6.61848962e-01 5.54581046e-01 2.77603745e-01 -1.35302567e+00 1.41583967e+00 -3.79593968e-02 5.01759112e-01 -7.32501745e-01 2.53872901e-01 6.06542945e-01 2.48390421e-01 -6.17249131e-01 4.29145902e-01 -3.41579854e-01 -1.43938661e-01 2.06357330e-01 -6.92335814e-02 -6.08218253e-01 3.21407348e-01 -2.74857402e-01 1.34209979e+00 -4.65148836e-01 -7.90831447e-02 -5.52689135e-01 7.39350975e-01 2.19847113e-02 2.90572852e-01 6.92849636e-01 -6.67119352e-03 7.88218141e-01 8.54930162e-01 -5.37059009e-01 -1.24434960e+00 -1.00430715e+00 -3.53597432e-01 -3.35499048e-02 2.34173849e-01 4.17189628e-01 -7.78462529e-01 -7.07324684e-01 9.00300071e-02 5.37459254e-01 -3.91676635e-01 -1.88566238e-01 -5.62592328e-01 -8.65839660e-01 2.67593026e-01 5.02559841e-01 5.04267812e-01 -1.40898621e+00 -6.83506429e-01 4.29356277e-01 7.56148756e-01 -9.06042635e-01 2.61364758e-01 6.21014595e-01 -8.49665523e-01 -1.34309518e+00 -3.69809598e-01 -8.23681593e-01 1.05816889e+00 -3.78154516e-01 1.13724077e+00 3.08807820e-01 -1.15169716e+00 1.73493415e-01 -4.36217457e-01 -4.03537840e-01 -8.41265917e-01 -2.04131782e-01 -1.90257296e-01 -7.74323801e-03 3.46952341e-02 -3.52319270e-01 -8.64960253e-01 2.63401479e-01 -9.76024568e-01 -3.09101820e-01 6.68679833e-01 9.81486082e-01 4.50329036e-01 5.17594874e-01 5.97828090e-01 -1.14140689e+00 5.77355146e-01 -2.34795004e-01 -6.47543609e-01 -5.40559590e-02 -6.90912902e-01 -4.89535093e-01 4.99421388e-01 1.54931694e-01 -9.34308350e-01 -2.19160974e-01 -5.95734775e-01 -1.66234091e-01 -7.12377548e-01 5.37951827e-01 -2.58227438e-01 -1.08857065e-01 7.02828348e-01 -1.91860516e-02 3.69385481e-02 -2.95632660e-01 -1.84594542e-01 9.11773503e-01 1.83060229e-01 -2.91059971e-01 7.19729066e-01 7.31564581e-01 1.06446527e-01 -1.13013458e+00 -1.77924469e-01 -4.42339331e-01 -8.85205448e-01 -2.72153556e-01 1.02332985e+00 -3.70157838e-01 -8.60173941e-01 1.09098816e+00 -1.22504199e+00 -4.35176313e-01 -5.00606120e-01 -1.04936577e-01 -3.31788331e-01 3.72570604e-01 -1.10851216e+00 -1.08673835e+00 -4.44428712e-01 -1.33859527e+00 1.16400456e+00 2.54961997e-01 -1.33435324e-01 -1.07271183e+00 -4.83848602e-01 4.16987717e-01 3.68240923e-01 4.43482161e-01 1.57936978e+00 -3.43704730e-01 -5.33794403e-01 -3.75259846e-01 -3.28252077e-01 6.95743084e-01 4.57140148e-01 2.54386455e-01 -6.60867989e-01 -3.62692356e-01 3.50224853e-01 -3.27587903e-01 9.84481633e-01 5.92498660e-01 1.33513105e+00 4.46017951e-01 -4.70089942e-01 1.79845572e-01 1.75730658e+00 5.47036052e-01 8.35958242e-01 6.06162250e-02 7.96562731e-01 5.31561315e-01 6.81542456e-01 4.28257644e-01 -3.15239012e-01 5.88286817e-01 7.49741971e-01 -3.97900671e-01 -1.16695203e-01 4.65969861e-01 -9.73806810e-03 6.95578873e-01 8.05432275e-02 -3.69481653e-01 -9.95726109e-01 8.37720633e-01 -1.05940318e+00 -4.56324577e-01 -5.44004798e-01 1.90500009e+00 5.02621591e-01 4.60350811e-01 -1.86712697e-01 8.13519537e-01 8.10896337e-01 -2.19901383e-01 -5.48356295e-01 -7.67711699e-01 -6.92355335e-02 7.37272859e-01 4.05084580e-01 1.20794706e-01 -8.31529140e-01 7.39370823e-01 4.62243032e+00 1.02106464e+00 -1.15110743e+00 -1.03866523e-02 8.64453971e-01 4.03914243e-01 -2.35782310e-01 -2.66452432e-01 -8.00690114e-01 3.44312221e-01 3.33060294e-01 7.91927576e-01 -8.10628012e-02 3.70492131e-01 -5.36557585e-02 -4.83075678e-01 -1.15222204e+00 1.04458046e+00 -1.52371526e-01 -1.37909770e+00 -9.56564322e-02 2.23607257e-01 9.41999137e-01 -3.71037185e-01 -4.41615209e-02 7.54600333e-04 5.05010672e-02 -1.04745579e+00 6.51895881e-01 2.75414020e-01 9.57018077e-01 -6.82845056e-01 1.09133983e+00 -5.66040762e-02 -9.15989578e-01 -5.21246135e-01 -4.50474799e-01 1.37952551e-01 8.75749737e-02 1.21602190e+00 -6.75206721e-01 6.38462484e-01 7.72232533e-01 5.85773349e-01 -2.75380850e-01 9.31829810e-01 1.43251106e-01 6.17583930e-01 -1.31892651e-01 1.30829573e-01 2.00697988e-01 -3.05678248e-01 3.55069399e-01 1.01902127e+00 6.20991945e-01 -3.74503911e-01 -7.59527609e-02 1.56935811e+00 1.03916265e-01 -3.40314329e-01 -4.18257952e-01 -1.17100105e-01 3.38558525e-01 1.28366721e+00 -1.57938099e+00 1.04401700e-01 -9.11776870e-02 8.20519447e-01 -4.16871011e-02 1.07260808e-01 -3.95282924e-01 -4.65956360e-01 6.54302776e-01 5.16051054e-01 4.62358862e-01 -3.40837568e-01 -8.83837938e-01 -2.00864524e-01 3.45598981e-02 -4.72452879e-01 7.61813894e-02 -1.78660303e-01 -1.40871859e+00 3.65093261e-01 -3.79775405e-01 -8.78316462e-01 3.86069834e-01 -1.11794186e+00 -9.91346598e-01 6.76350653e-01 -1.23435080e+00 -1.19377840e+00 -3.89844120e-01 1.28112242e-01 9.00142729e-01 -2.02651769e-01 4.75116611e-01 3.59283060e-01 -7.31986046e-01 5.57455599e-01 2.16874585e-01 -3.57509740e-02 8.67161155e-02 -1.29703343e+00 3.86417121e-01 4.66527402e-01 -1.89181477e-01 9.35676545e-02 7.36456811e-01 -8.19802344e-01 -1.24399137e+00 -9.68667388e-01 1.82683975e-01 -6.37811869e-02 5.09871244e-01 -4.92401928e-01 -9.70288277e-01 -1.04850214e-02 -5.87397590e-02 -1.60082504e-02 -3.31746116e-02 -1.85078889e-01 4.59942937e-01 -3.29927921e-01 -1.70830309e+00 2.84195900e-01 9.19375181e-01 -3.50474924e-01 6.18708022e-02 3.94291103e-01 3.10071617e-01 -4.31080371e-01 -8.02716315e-01 8.88977766e-01 8.84836167e-02 -1.52044964e+00 5.61393678e-01 5.05296625e-02 7.54851937e-01 -2.68906653e-01 1.03659429e-01 -1.06717980e+00 -8.50104243e-02 8.61161649e-02 3.28273267e-01 1.41416180e+00 4.93620723e-01 -6.34188116e-01 1.11454880e+00 -1.38592914e-01 -9.00485516e-01 -1.17072821e+00 -1.18138433e+00 -6.84662521e-01 1.88445017e-01 -4.17804986e-01 3.58643115e-01 6.47780478e-01 -5.30345500e-01 -4.35116678e-01 3.78042340e-01 2.66262382e-01 3.55262369e-01 1.28997415e-01 1.97593629e-01 -1.57820773e+00 -2.10441947e-02 -6.46638870e-01 -7.04138458e-01 -5.00571847e-01 -1.34068951e-01 -4.90193427e-01 2.45025918e-01 -1.75664413e+00 -3.30059230e-01 -9.06102777e-01 -1.35795861e-01 9.70954150e-02 3.76839072e-01 4.09661710e-01 -4.43704486e-01 1.65384114e-01 -1.02338523e-01 2.60712892e-01 1.16459453e+00 -5.54631054e-01 -1.02210172e-01 2.21192196e-01 -2.48763099e-01 5.06456494e-01 6.50992870e-01 -2.81659007e-01 2.19022296e-02 -9.33013707e-02 2.01592326e-01 8.47912114e-03 4.46083188e-01 -1.63380837e+00 1.90683957e-02 3.27042848e-01 5.10623336e-01 -7.25548565e-01 8.93277898e-02 -8.64709973e-01 -1.67708233e-01 7.26274133e-01 8.62950236e-02 -3.11884135e-01 3.03869009e-01 4.50176567e-01 -3.83304983e-01 -7.28206456e-01 1.06845522e+00 -3.34223300e-01 -3.68408978e-01 4.72470261e-02 -5.31976402e-01 -5.51206768e-01 1.17984724e+00 -7.73297608e-01 -3.01952839e-01 2.65950620e-01 -8.05725217e-01 -1.16806321e-01 5.95663011e-01 -2.82786414e-02 9.34764147e-01 -9.01635766e-01 -4.32958812e-01 5.73501348e-01 1.08717985e-01 2.57704079e-01 8.75489175e-01 8.02229166e-01 -1.02680016e+00 1.26016527e-01 -3.59068900e-01 -9.39801395e-01 -1.07886255e+00 2.59935051e-01 5.39194643e-01 -5.00187039e-01 -4.83339995e-01 1.07407844e+00 -7.16641545e-02 -1.78334653e-01 -1.89979717e-01 -8.22474062e-01 -4.10588861e-01 5.37070855e-02 -1.62669674e-01 5.24745584e-01 6.54130280e-01 -2.02506870e-01 -5.08462079e-02 8.75027895e-01 -2.64083475e-01 5.38589954e-01 1.26031005e+00 8.13331753e-02 -3.13965261e-01 5.04206061e-01 1.00636697e+00 -1.09493546e-01 -1.14906168e+00 3.99268508e-01 9.31886658e-02 2.27720980e-02 1.26207564e-02 -8.12649667e-01 -1.36164975e+00 1.03810036e+00 1.08427072e+00 6.58479095e-01 9.86000240e-01 1.98256373e-01 9.41496491e-01 -1.21537514e-03 4.71357882e-01 -1.25711131e+00 4.15109754e-01 2.68747360e-01 9.08771694e-01 -1.36346662e+00 1.25454599e-02 -6.75780177e-01 -1.72944635e-01 1.51014376e+00 7.94469237e-01 -2.00059995e-01 6.62189722e-01 4.72657263e-01 -3.01132798e-02 -1.03134382e+00 -1.62304550e-01 -6.48212656e-02 -2.46197004e-02 6.25580251e-01 3.00535172e-01 7.83865526e-02 -1.82213426e-01 5.35798848e-01 2.04014569e-03 -3.62306833e-01 6.55759156e-01 1.12455821e+00 -5.77377975e-01 -1.02146983e+00 -3.92414868e-01 1.01193249e+00 -2.87753195e-01 1.59663916e-01 -1.60270140e-01 8.08739066e-01 6.34576023e-01 9.73942339e-01 4.20019358e-01 -4.08518553e-01 3.93821478e-01 -2.64260024e-01 5.74789166e-01 -9.12787437e-01 -8.21673155e-01 -2.95778573e-01 -1.22654580e-01 -2.11334631e-01 2.77617760e-02 -5.89240313e-01 -1.47202051e+00 2.47970909e-01 -4.45394516e-01 -2.55913913e-01 9.27625299e-01 1.03265667e+00 -1.05166540e-01 9.70781207e-01 6.86041415e-01 -9.85379159e-01 -3.10486108e-01 -1.19826412e+00 -1.06812215e+00 4.63055223e-01 2.54379898e-01 -9.12811995e-01 -5.19391656e-01 -2.43652776e-01]	[7.314776420593262, 1.9213964939117432]
aae26acd-2882-49e8-a457-c9285da7988f	building-state-of-the-art-distant-speech	1803.10109	null	http://arxiv.org/abs/1803.10109v1	http://arxiv.org/pdf/1803.10109v1.pdf	Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline	This paper describes a new baseline system for automatic speech recognition (ASR) in the CHiME-4 challenge to promote the development of noisy ASR in speech processing communities by providing 1) state-of-the-art system with a simplified single system comparable to the complicated top systems in the challenge, 2) publicly available and reproducible recipe through the main repository in the Kaldi speech recognition toolkit. The proposed system adopts generalized eigenvalue beamforming with bidirectional long short-term memory (LSTM) mask estimation. We also propose to use a time delay neural network (TDNN) based on the lattice-free version of the maximum mutual information (LF-MMI) trained with augmented all six microphones plus the enhanced data after beamforming. Finally, we use a LSTM language model for lattice and n-best re-scoring. The final system achieved 2.74\% WER for the real test set in the 6-channel track, which corresponds to the 2nd place in the challenge. In addition, the proposed baseline recipe includes four different speech enhancement measures, short-time objective intelligibility measure (STOI), extended STOI (eSTOI), perceptual evaluation of speech quality (PESQ) and speech distortion ratio (SDR) for the simulation test set. Thus, the recipe also provides an experimental platform for speech enhancement studies with these performance measures.	['Szu-Jui Chen', 'Aswin Shanmugam Subramanian', 'Hainan Xu', 'Shinji Watanabe']	2018-03-27	null	null	null	null	['noisy-speech-recognition', 'distant-speech-recognition']	['speech', 'speech']	[ 2.37485953e-02 -1.65229991e-01 6.89534366e-01 -2.63175189e-01 -1.40962338e+00 -8.63576531e-02 1.97851017e-01 -2.97213584e-01 -8.54436755e-01 3.71584833e-01 6.29428267e-01 -6.18731201e-01 -1.34064317e-01 -5.19961156e-02 -4.51505333e-01 -7.42099106e-01 -1.53729677e-01 -1.06727391e-01 -4.00374085e-02 -4.84294593e-01 -1.52615368e-01 4.96667892e-01 -1.32862270e+00 4.55923498e-01 6.75240576e-01 1.01759362e+00 7.60166824e-01 1.09367609e+00 2.92182356e-01 4.98413414e-01 -8.77899349e-01 -2.76654094e-01 1.05919123e-01 -1.77723646e-01 -5.21280587e-01 -9.77957845e-02 1.30277812e-01 -3.50063562e-01 -7.29902148e-01 1.05831444e+00 1.44687319e+00 6.06937528e-01 3.14277619e-01 -4.82509494e-01 -5.11043310e-01 8.84845793e-01 -7.03135356e-02 4.20161068e-01 1.63691014e-01 2.65607238e-03 7.30386496e-01 -1.44156420e+00 1.11469239e-01 1.21550655e+00 5.85385859e-01 5.29419303e-01 -7.55327344e-01 -6.68109417e-01 -2.18468308e-01 6.73833549e-01 -1.47933400e+00 -1.18702424e+00 4.17868435e-01 -8.10768083e-02 1.66740298e+00 5.21342158e-01 2.44173825e-01 1.05208397e+00 -2.26574257e-01 6.29863739e-01 1.05926907e+00 -6.98899925e-01 7.94267058e-02 2.20421970e-01 2.89357066e-01 2.87347704e-01 -5.60240686e-01 4.89309549e-01 -6.88364685e-01 1.36403322e-01 3.39894623e-01 -8.27282310e-01 -4.26149696e-01 7.90602684e-01 -1.05000269e+00 1.51033610e-01 2.24482473e-02 6.75924242e-01 -4.48966473e-01 -2.12394848e-01 4.75154638e-01 7.61672676e-01 6.52431130e-01 5.58272824e-02 -5.98376334e-01 -3.25261325e-01 -1.11705232e+00 -9.26937684e-02 5.34590662e-01 7.06445158e-01 1.15186848e-01 7.62929380e-01 -5.48966646e-01 1.59579766e+00 6.63022697e-01 7.54141152e-01 6.84230566e-01 -6.94592655e-01 7.10269094e-01 -4.21571523e-01 2.96092350e-02 -3.93625051e-01 -2.70699441e-01 -1.06223881e+00 -9.67977464e-01 1.26102924e-01 -8.29611346e-02 -3.69103372e-01 -9.00825441e-01 1.68116117e+00 -1.33335561e-01 2.88233727e-01 4.87057060e-01 7.46788681e-01 9.12370265e-01 1.22345221e+00 -3.72233778e-01 -5.63412011e-01 1.10239184e+00 -1.23860204e+00 -1.23698068e+00 -7.50416890e-02 5.49143374e-01 -1.29847395e+00 9.06070530e-01 7.91404366e-01 -1.50087130e+00 -9.04136539e-01 -1.22009480e+00 1.58149526e-01 -2.56120086e-01 6.61364734e-01 -3.43209118e-01 1.13406706e+00 -1.77486813e+00 4.91968125e-01 -5.14444053e-01 -7.49570429e-02 -4.99225020e-01 2.82107472e-01 -3.39974463e-01 1.44422546e-01 -1.52480268e+00 9.71862137e-01 2.70263493e-01 5.29693961e-01 -9.34092104e-01 -4.73624229e-01 -7.52452552e-01 1.86516628e-01 -3.16644944e-02 -1.71437725e-01 1.41556513e+00 -5.08690298e-01 -2.24331117e+00 5.83599687e-01 -4.85643834e-01 -5.52182078e-01 1.27816200e-01 -3.89089793e-01 -1.15083432e+00 -3.33050638e-01 -6.12243772e-01 1.92833215e-01 7.72054434e-01 -8.33259523e-01 -3.70175928e-01 -2.53554255e-01 -6.63001299e-01 4.86290276e-01 -4.85970765e-01 6.46110296e-01 -3.85194510e-01 -9.54423487e-01 1.82500869e-01 -5.37921667e-01 -1.61769122e-01 -8.89529526e-01 -5.32650352e-01 -1.02479182e-01 5.68256021e-01 -1.60367668e+00 1.72760212e+00 -2.58960748e+00 3.00194602e-02 1.97346598e-01 -3.97352785e-01 9.85782444e-01 -4.57175732e-01 3.91629666e-01 -3.65856916e-01 3.26088741e-02 3.33699994e-02 -9.37671483e-01 2.29695916e-01 -2.58786500e-01 -2.35944301e-01 2.47570872e-01 -1.59837246e-01 2.64027685e-01 -4.15326178e-01 -3.68628576e-02 6.39450371e-01 8.23793709e-01 -2.23514408e-01 4.51548636e-01 4.66088831e-01 2.98615485e-01 3.66121948e-01 9.72674321e-03 8.61715019e-01 6.69591069e-01 -3.04438055e-01 -1.97463855e-01 -4.83964115e-01 7.29839265e-01 -1.63912094e+00 1.69356227e+00 -8.07764947e-01 7.21865952e-01 5.91542304e-01 -6.39650166e-01 1.08150423e+00 1.10212588e+00 -3.03990152e-02 -5.64080775e-01 -1.01084448e-01 5.29359102e-01 2.39552125e-01 -3.90092045e-01 4.21891093e-01 1.70893818e-01 5.79559207e-01 6.70794696e-02 2.99314231e-01 -3.56091820e-02 -1.15890533e-01 -6.83675036e-02 1.00926876e+00 -4.95291382e-01 8.22938513e-03 -2.05333889e-01 9.66029465e-01 -9.67228711e-01 2.60434836e-01 7.43866146e-01 -3.01258028e-01 6.67641759e-01 -3.72753382e-01 2.52638847e-01 -1.18650091e+00 -1.31225848e+00 -2.19802469e-01 1.05328476e+00 -6.37792766e-01 -3.37407649e-01 -1.03270853e+00 2.53152996e-01 -7.67033160e-01 9.84322488e-01 1.58113316e-01 2.64085948e-01 -5.98693490e-01 -6.62552953e-01 1.00513029e+00 2.21013054e-01 5.27700722e-01 -1.09139478e+00 4.98986900e-01 3.28720868e-01 -3.57288688e-01 -1.27233469e+00 -7.03059912e-01 2.41689980e-01 -3.29393715e-01 -6.79882839e-02 -1.02177727e+00 -9.50433671e-01 -7.65043870e-03 1.27474472e-01 6.36157691e-01 -2.88266480e-01 1.90139875e-01 8.90479311e-02 -4.64569598e-01 -2.44508702e-02 -9.05373394e-01 -1.85454905e-01 4.43568617e-01 9.05254856e-02 8.36691447e-03 -4.96103585e-01 -3.24874133e-01 5.04877150e-01 -4.75129217e-01 -1.45087674e-01 5.45522213e-01 8.32980216e-01 4.25575495e-01 2.08181649e-01 8.90066743e-01 1.44610181e-01 1.00921881e+00 2.98750997e-02 -4.89354938e-01 3.02489579e-01 -4.13063377e-01 -1.46488369e-01 5.70229530e-01 -2.73739040e-01 -1.52798295e+00 -3.64343941e-01 -1.34667850e+00 -1.38172030e-01 -2.41943613e-01 4.58515018e-01 -5.95177412e-01 2.14770794e-01 5.08736312e-01 4.88987803e-01 -3.94913077e-01 -9.37962353e-01 2.39523068e-01 1.64311612e+00 6.07962370e-01 -1.52923882e-01 5.00049889e-01 -2.80035168e-01 -6.13366365e-01 -1.50005960e+00 -2.71997750e-01 -7.46876895e-01 -2.88424522e-01 -6.99815527e-02 6.00725651e-01 -1.11651611e+00 -4.40226406e-01 1.03191066e+00 -1.53570783e+00 -3.29714328e-01 3.53042968e-02 1.08462203e+00 -3.03148448e-01 5.06007493e-01 -1.05950642e+00 -1.28472424e+00 -8.63893270e-01 -1.50762856e+00 7.45986640e-01 -3.03596795e-01 1.39867544e-01 -6.53042674e-01 2.98213549e-02 4.93798256e-01 9.50079560e-01 -7.08607435e-01 4.91522998e-01 -6.52467012e-01 1.04181003e-02 3.94748859e-02 -1.00728162e-02 1.37634385e+00 -1.39100149e-01 -1.60227537e-01 -1.53958881e+00 -4.63489175e-01 3.93082827e-01 1.17151976e-01 7.36710310e-01 8.03631902e-01 8.16312850e-01 -2.29973763e-01 2.08149463e-01 5.36735296e-01 8.88562441e-01 6.58032119e-01 9.86239851e-01 -1.43758327e-01 2.78837293e-01 4.15549248e-01 2.16396093e-01 3.54233950e-01 -7.84704387e-02 1.01267481e+00 -2.64198035e-01 -2.13350803e-01 -6.12536013e-01 1.00157380e-01 1.12517130e+00 2.15651941e+00 1.69682994e-01 -5.29583454e-01 -7.12786436e-01 3.76188546e-01 -1.27076626e+00 -9.09136415e-01 -2.41828784e-01 2.49584818e+00 7.23504603e-01 6.09029904e-02 -9.78439599e-02 6.91386878e-01 1.03900898e+00 1.35315195e-01 -8.30181409e-03 -8.28670502e-01 -4.22559500e-01 4.76545751e-01 4.25586015e-01 1.19613111e+00 -8.18271637e-01 8.67543519e-01 5.85757732e+00 1.63724220e+00 -1.00155699e+00 7.26066232e-01 5.12101233e-01 -8.24630484e-02 9.70393345e-02 -5.93498111e-01 -8.64231646e-01 2.54278660e-01 1.77497983e+00 -8.16385224e-02 8.23975801e-01 4.37101513e-01 8.64874899e-01 2.73013055e-01 -7.14518547e-01 1.10658121e+00 5.72043955e-02 -7.43109524e-01 -3.31372768e-01 -1.39338136e-01 3.75929654e-01 5.92607617e-01 4.28673416e-01 3.87572587e-01 -1.28586635e-01 -1.05443084e+00 6.90102637e-01 2.56135345e-01 1.13735533e+00 -6.48317814e-01 7.32154965e-01 2.96612233e-01 -1.27891386e+00 -5.21121360e-02 -3.57025445e-01 1.57082513e-01 3.29300493e-01 7.35047162e-01 -1.00468433e+00 5.48377991e-01 4.79846805e-01 5.88471889e-02 -9.31590647e-02 1.29096329e+00 -1.72774523e-01 1.02236557e+00 -3.89966667e-01 3.28918099e-02 1.50099173e-01 8.82924199e-02 1.17507684e+00 1.70918477e+00 7.65642166e-01 -1.01331502e-01 -4.41380113e-01 3.30899537e-01 4.49501164e-02 3.74898791e-01 -1.57576337e-01 1.92242414e-01 6.39984548e-01 9.99371409e-01 5.21430708e-02 -9.29024816e-02 -1.56104296e-01 9.31490362e-01 -1.30813360e-01 7.08601117e-01 -5.14919460e-01 -6.10604942e-01 5.60813248e-01 -2.24476874e-01 1.21559519e-02 -3.50719690e-01 -3.93963493e-02 -8.26781452e-01 3.64301875e-02 -1.00323808e+00 -2.47461930e-01 -9.34993386e-01 -9.05241013e-01 1.30764031e+00 -3.11251074e-01 -9.12991405e-01 -3.40888590e-01 -8.12590539e-01 -4.56823409e-01 1.53096640e+00 -1.34197176e+00 -7.24868119e-01 3.33569229e-01 5.37740290e-01 9.36649144e-01 -5.76969147e-01 9.87996757e-01 1.13771057e+00 -7.12456167e-01 1.08626783e+00 5.76016903e-01 -6.27301261e-02 7.50547647e-01 -1.08484840e+00 8.55180979e-01 1.13516378e+00 1.61285460e-01 5.06366670e-01 7.63923764e-01 -3.08868200e-01 -1.04626453e+00 -9.75342214e-01 1.09603655e+00 3.24429795e-02 5.47897518e-01 -4.58641261e-01 -7.94962883e-01 3.24556947e-01 3.90017062e-01 -3.76694262e-01 4.77130353e-01 9.83729884e-02 -2.56854412e-03 -3.37749779e-01 -8.71016085e-01 4.19867545e-01 7.67551541e-01 -7.77554154e-01 -3.20191294e-01 3.15964788e-01 1.20223904e+00 -4.60397422e-01 -7.30828702e-01 4.00749445e-01 2.55492210e-01 -9.31680679e-01 8.68027031e-01 -1.36990445e-02 -3.02130520e-01 -3.32691193e-01 -7.30408669e-01 -1.70547104e+00 -2.37697318e-01 -1.07206857e+00 2.70904094e-01 1.47251761e+00 8.93739164e-01 -4.51277196e-01 2.14144111e-01 4.36564907e-02 -9.29969609e-01 -4.58434969e-01 -1.35663354e+00 -9.93154645e-01 -9.17255357e-02 -1.06593084e+00 3.88297766e-01 2.64918625e-01 -1.34893060e-01 2.46094048e-01 -7.31144845e-01 5.64841092e-01 3.93052161e-01 -1.20080411e+00 2.29736194e-01 -4.96731341e-01 -6.91703379e-01 -3.93302679e-01 -1.71149522e-01 -1.18104208e+00 4.82064374e-02 -7.08692789e-01 2.58188933e-01 -1.44369781e+00 -3.09296489e-01 -1.31153956e-01 -7.30296016e-01 -1.17928544e-02 6.60171872e-03 -2.61328846e-01 1.84410557e-01 -4.32811290e-01 -2.32166529e-01 6.27741635e-01 7.96641707e-01 -1.32314488e-01 -3.91997755e-01 3.19715679e-01 -8.64184722e-02 5.26949644e-01 7.34200001e-01 -1.93189099e-01 -2.67586112e-01 -6.00361347e-01 -2.27293029e-01 4.61009800e-01 -1.13134831e-02 -1.27812934e+00 4.12622690e-01 5.59670150e-01 -1.91283315e-01 -7.96312988e-01 8.97027433e-01 -5.04450440e-01 2.11616814e-01 2.61198968e-01 -4.40880626e-01 3.04373801e-02 3.90064687e-01 3.10476609e-02 -4.42175239e-01 -4.15070295e-01 9.27066803e-01 3.42986494e-01 -4.22845036e-01 -9.15223137e-02 -6.24408364e-01 -3.08648050e-01 2.41209030e-01 6.61247224e-02 -1.63319379e-01 -5.44554114e-01 -1.01065779e+00 -2.41450563e-01 -4.49185103e-01 2.03810528e-01 8.30237210e-01 -1.15997636e+00 -1.39049971e+00 3.16922903e-01 -3.01049888e-01 -7.11142600e-01 7.16276526e-01 6.41318798e-01 -9.71037000e-02 5.77195942e-01 2.70055115e-01 -2.03475028e-01 -1.47144938e+00 1.14553019e-01 7.10631132e-01 -3.31227958e-01 -2.14382380e-01 1.31577897e+00 -9.66606587e-02 -4.97133255e-01 8.21937919e-01 -1.25521570e-01 -1.90907434e-01 -3.77223581e-01 8.31664383e-01 7.78844237e-01 7.88752079e-01 -8.82984579e-01 -2.28204191e-01 7.79042020e-02 4.66299281e-02 -9.57945585e-01 1.08680785e+00 -4.43721652e-01 -1.11781195e-01 4.58733708e-01 1.40017903e+00 2.81551898e-01 -4.41424459e-01 -3.18988651e-01 -1.92781776e-01 -1.00724846e-01 6.81232870e-01 -1.24689806e+00 -6.88928068e-01 1.25790608e+00 1.22516644e+00 6.66810051e-02 1.30009758e+00 -5.98233044e-01 1.06438565e+00 5.45268416e-01 -4.10915427e-02 -1.34943044e+00 -2.08292544e-01 9.37145710e-01 1.22411382e+00 -7.97194481e-01 -7.52521992e-01 -9.09472778e-02 -4.22091335e-01 9.42387819e-01 1.95915610e-01 4.15851980e-01 9.00571227e-01 7.20470667e-01 3.41118366e-01 5.19050062e-01 -7.17650473e-01 -2.17086822e-01 4.17924374e-01 5.44158518e-01 7.21503556e-01 2.00807050e-01 -2.66876698e-01 7.44680643e-01 -4.80435818e-01 -3.64661068e-01 2.57760495e-01 5.67243546e-02 -7.21470773e-01 -1.08898437e+00 -6.87547386e-01 9.03538093e-02 -8.11963260e-01 -7.22888768e-01 1.09834880e-01 -4.74486575e-02 -8.36403519e-02 1.68957448e+00 -3.15247595e-01 -8.22837055e-01 5.22902429e-01 1.60056323e-01 1.21764891e-01 -4.39276427e-01 -8.11693549e-01 5.94091594e-01 3.89933705e-01 -2.00519919e-01 8.87216553e-02 -3.75280827e-01 -8.37505162e-01 -9.70646515e-02 -6.23053372e-01 2.75380731e-01 1.27770603e+00 9.23900783e-01 2.38860488e-01 8.27638447e-01 7.62494683e-01 -7.65268624e-01 -7.24281490e-01 -1.59251118e+00 -7.54637957e-01 -5.56676909e-02 5.23294508e-01 -1.21675104e-01 -5.61845362e-01 -1.29082367e-01]	[14.823627471923828, 6.042372226715088]
10c76181-12d1-49b2-a634-8aa4d1daa5a4	boundary-detection-with-bert-for-span-level	null	null	https://aclanthology.org/2021.findings-acl.60	https://aclanthology.org/2021.findings-acl.60.pdf	Boundary Detection with BERT for Span-level Emotion Cause Analysis	null	['Daling Wang', 'Yifei Zhang', 'Shi Feng', 'Wei Gao', 'Xiangju Li']	null	null	null	null	findings-acl-2021-8	['boundary-detection']	['computer-vision']	[-8.63703638e-02 1.71006292e-01 -6.22772932e-01 -4.08054382e-01 -8.41685571e-03 -9.08429027e-01 6.55310392e-01 -6.53472245e-01 -2.85945535e-01 1.06888819e+00 -4.63127941e-02 -1.01159286e+00 -3.91567826e-01 -9.63214397e-01 -4.95059669e-01 -6.31337762e-01 -9.79754329e-01 7.25764990e-01 3.30370307e-01 -6.93831444e-01 7.03166842e-01 7.88774848e-01 -1.68942046e+00 7.18545914e-01 7.04417467e-01 8.52217197e-01 2.49141872e-01 1.14950800e+00 -1.95044339e-01 1.55633950e+00 -7.48382092e-01 -5.46825826e-01 3.13719302e-01 -1.23176083e-01 -7.22945035e-01 -1.01074085e-01 9.28529128e-02 -8.59008506e-02 -2.09758401e-01 9.22211111e-01 5.37373662e-01 4.49454933e-02 1.08379531e+00 -1.42548037e+00 -5.91619551e-01 6.10313773e-01 -4.01565880e-02 1.21627934e-01 1.03678203e+00 -5.39447069e-01 1.19919395e+00 -1.13026452e+00 7.20913768e-01 1.26888943e+00 8.66221786e-01 5.44149756e-01 -1.22286928e+00 -1.94712028e-01 -3.26822817e-01 -9.51717794e-02 -1.46558487e+00 -3.25250506e-01 4.25783843e-02 -2.08119690e-01 1.66093647e+00 1.26596653e+00 1.20609856e+00 1.01401424e+00 1.26658809e+00 8.34431887e-01 1.04267764e+00 -5.13792276e-01 3.35295945e-01 3.66983831e-01 1.54683650e-01 6.33519173e-01 8.40953708e-01 5.26628852e-01 -7.06372619e-01 -9.13127720e-01 9.33553874e-01 -2.94925272e-01 1.71355158e-01 -5.05680561e-01 -9.05919552e-01 6.91228509e-01 1.78732842e-01 3.83959889e-01 -1.39880210e-01 9.89067405e-02 1.26390755e-01 5.30987144e-01 -2.58292928e-02 6.47037446e-01 -9.11868811e-01 -1.33165747e-01 -8.71728659e-01 5.10332465e-01 1.25398111e+00 1.52653182e+00 1.24482810e-01 2.94908643e-01 -9.34252143e-02 3.17179203e-01 8.92314315e-01 1.01808000e+00 4.28362608e-01 -1.36146402e+00 -6.87414408e-02 1.72361732e-01 5.01781464e-01 -8.52631688e-01 -6.33224547e-01 -9.64177120e-03 -8.93263519e-01 4.49267089e-01 3.49161088e-01 4.57367361e-01 -8.02827001e-01 5.07305264e-01 4.33481112e-02 -2.34125629e-01 4.53833073e-01 5.55570945e-02 4.99930978e-01 3.76208365e-01 -1.34477139e-01 -5.73289394e-01 1.06082785e+00 -1.36716676e+00 -1.35299087e+00 2.33215362e-01 9.05734658e-01 -1.07320261e+00 4.35900748e-01 5.33875942e-01 -1.55548143e+00 -1.37560293e-01 -1.08699942e+00 1.78573877e-01 -7.27255583e-01 -3.14239264e-01 8.57801437e-01 1.43120694e+00 -1.60129595e+00 9.73287821e-01 -4.91727620e-01 6.59165755e-02 1.20568443e-02 8.24621081e-01 -2.64718989e-03 4.62812334e-01 -1.33193445e+00 1.08501506e+00 2.22979754e-01 -1.21242590e-01 -1.65216476e-01 -2.13068098e-01 -8.23704481e-01 -5.63443303e-01 -4.78693932e-01 -5.29636025e-01 1.44139910e+00 -2.59346128e-01 -1.65295815e+00 9.71794367e-01 -1.42069459e-01 -1.97814897e-01 6.14786744e-01 -1.28011424e-02 -8.31891418e-01 2.42498964e-01 -1.89849049e-01 5.76383233e-01 9.28263724e-01 -1.35132408e+00 -7.59897232e-01 -1.67359829e-01 -1.23336017e-01 2.66287565e-01 -1.25510961e-01 1.89734384e-01 2.11616129e-01 -1.12999000e-01 3.27147305e-01 -7.20919967e-01 -2.53068686e-01 -5.32041907e-01 -1.46512717e-01 -7.10518599e-01 7.70373225e-01 -4.51523662e-01 1.83705616e+00 -1.67618537e+00 -2.06720144e-01 3.98590982e-01 3.57815564e-01 -1.24705513e-03 2.40583986e-01 1.08380008e+00 -2.76906848e-01 7.32199550e-01 4.11965609e-01 -1.10722095e-01 2.24991128e-01 4.85861301e-01 -4.16602850e-01 3.05609167e-01 -1.29282743e-01 1.15307164e+00 -1.16605783e+00 -5.23096442e-01 4.11106765e-01 9.42391157e-02 -4.58732933e-01 4.79237735e-01 2.99364805e-01 1.47170946e-01 -3.56553018e-01 1.39399457e+00 1.15709066e+00 -1.31984919e-01 1.45911396e-01 5.30878425e-01 -3.79135728e-01 3.55090618e-01 -6.96863770e-01 1.05554795e+00 7.08333924e-02 5.00173986e-01 1.02364108e-01 -7.94621468e-01 3.33247900e-01 8.61540735e-01 4.37155962e-01 -9.67555881e-01 -2.26398129e-02 6.92409754e-01 1.12803578e-01 -6.07703328e-01 7.58228302e-01 3.94563079e-02 -3.64872098e-01 6.40070081e-01 -2.37588286e-01 -6.59476995e-01 9.64643434e-02 3.08100313e-01 6.22585893e-01 -5.18246442e-02 5.62923312e-01 -1.05613089e+00 7.86340594e-01 -1.82965681e-01 -1.81299388e-01 1.03415680e+00 -3.09923887e-01 3.19085121e-01 2.99841821e-01 -6.65102363e-01 -6.45341039e-01 -1.12307119e+00 -4.89381433e-01 1.30636716e+00 3.24267983e-01 -4.39044595e-01 -9.54439282e-01 -2.49762803e-01 1.77620783e-01 6.89606130e-01 -5.90509653e-01 3.84124845e-01 -5.03739953e-01 -8.32535863e-01 7.39044368e-01 3.45434904e-01 -5.07752821e-02 -1.33414865e+00 -6.58416986e-01 1.25490099e-01 -2.20292807e-01 -6.63697243e-01 -6.23428151e-02 4.48765576e-01 -1.35989368e+00 -5.18594682e-01 -6.66252747e-02 -8.20914626e-01 5.87345481e-01 2.46782884e-01 1.27047324e+00 5.39230824e-01 -2.31483161e-01 4.26904231e-01 -1.21292919e-01 -4.95818377e-01 -4.59671497e-01 -8.00336525e-02 5.28869390e-01 -5.87835789e-01 5.19427478e-01 -2.50617653e-01 -7.29350567e-01 5.37953973e-01 -6.88540697e-01 1.62748516e-01 1.79803044e-01 1.04410267e+00 1.35816500e-01 -9.34035778e-02 1.22507080e-01 -6.38007045e-01 8.72274399e-01 -1.69219792e-01 -3.78732830e-01 5.77745810e-02 -6.77108407e-01 -3.74140263e-01 3.21430594e-01 -3.25342178e-01 -1.01981449e+00 -4.87835288e-01 -9.82677937e-02 2.45538145e-01 1.11353043e-02 -1.46784872e-01 6.47139177e-02 -5.24923325e-01 8.02199244e-01 9.25758183e-02 1.99174434e-02 -6.80815242e-03 3.01039815e-01 7.09525108e-01 -6.82967342e-03 -6.68678164e-01 8.44880998e-01 4.91470337e-01 7.98524171e-02 -9.57177758e-01 -1.52186140e-01 -2.60129690e-01 -9.51962709e-01 -6.54426932e-01 6.56643391e-01 -6.78531289e-01 -9.10833478e-01 3.91110867e-01 -9.38691139e-01 -3.38627815e-01 -3.91645581e-01 4.25431967e-01 -1.01278400e+00 2.75717527e-02 -3.90154392e-01 -1.27895141e+00 -5.10977268e-01 -1.02017939e+00 9.43384409e-01 5.30070923e-02 -5.10597289e-01 -1.26927447e+00 5.87685481e-02 2.71537274e-01 1.81734428e-01 -1.73075795e-01 6.90226793e-01 -2.38256708e-01 -4.24233019e-01 -1.53791070e-01 2.34436691e-02 -1.39755070e-01 1.70832314e-02 4.95917559e-01 -9.81751978e-01 -5.31145096e-01 6.65065646e-02 -1.92070693e-01 -1.08835101e-01 6.52520418e-01 5.91872573e-01 -2.29931593e-01 -8.56000841e-01 5.40386558e-01 1.38545322e+00 3.85070026e-01 5.32770038e-01 7.28214979e-01 1.41836226e-01 5.53460240e-01 9.17806149e-01 4.63203549e-01 1.30579369e-02 3.28798652e-01 2.40537539e-01 1.49327129e-01 1.11720070e-01 -1.54819340e-01 3.77893507e-01 1.16112018e+00 -8.18235934e-01 -2.69281328e-01 -5.07867396e-01 4.42987174e-01 -1.72482407e+00 -1.40330648e+00 -4.32368398e-01 6.90478683e-01 6.25676990e-01 1.56016424e-01 -1.48347050e-01 3.35214496e-01 4.99015123e-01 -2.03574806e-01 -1.19133167e-01 -1.06291151e+00 -1.43546045e-01 3.15233678e-01 7.37729073e-01 1.00061214e+00 -7.20721722e-01 1.03317809e+00 1.29781246e+01 1.02230716e+00 2.21112028e-01 1.03134915e-01 5.16071796e-01 3.48020852e-01 -4.36954498e-01 -4.56139445e-02 -1.04416132e+00 2.72933897e-02 1.38140702e+00 -4.30666685e-01 6.85999811e-01 5.44219851e-01 3.44648361e-01 -4.23268199e-01 -1.26188684e+00 5.26221812e-01 9.73738134e-02 -1.40886843e+00 -2.83300440e-04 6.85225725e-01 7.73699820e-01 -5.08050561e-01 6.22419357e-01 3.24184299e-01 6.09259963e-01 -1.14389277e+00 8.60300779e-01 2.53660440e-01 1.03040910e+00 -6.05088234e-01 5.67372203e-01 1.68872893e-01 -1.14389896e+00 -2.20873043e-01 -8.77727985e-01 -1.00755692e+00 3.93533185e-02 -1.81779593e-01 -4.29956943e-01 3.48861217e-01 9.58353162e-01 2.99398601e-01 -3.93658698e-01 9.95779395e-01 -4.78694476e-02 1.04875881e-02 -2.71853864e-01 -4.48467314e-01 4.83122796e-01 -3.54241252e-01 4.66730654e-01 1.00164843e+00 2.48499006e-01 3.51035744e-01 -9.84472036e-02 4.01770771e-01 5.45058846e-01 3.29446048e-02 -1.19659424e+00 -1.78908288e-01 2.83276141e-01 9.16795909e-01 -4.83487815e-01 -4.22520459e-01 -2.00212970e-01 8.62069130e-01 -3.55488248e-02 5.01107454e-01 -6.11489356e-01 -4.35615242e-01 9.72222984e-01 -1.27327025e-01 -1.14700586e-01 -3.48497719e-01 -6.23769283e-01 -7.30352640e-01 -5.89872956e-01 -4.54965204e-01 5.93606755e-02 -5.53365827e-01 -1.39813089e+00 5.79277515e-01 -2.27688253e-02 -1.40553558e+00 -6.99901402e-01 -1.27676582e+00 -4.76714373e-01 4.92853165e-01 -1.11898029e+00 -1.10984349e+00 2.50124663e-01 4.52870727e-01 1.64141744e-01 -5.34416080e-01 1.39563632e+00 3.57715860e-02 1.00637585e-01 9.24474537e-01 6.69434488e-01 -7.37814724e-01 5.56605101e-01 -1.27867436e+00 5.68737745e-01 -1.37897313e-01 -4.31265175e-01 9.05828118e-01 6.28349900e-01 -5.39804697e-01 -1.41196322e+00 -3.66917729e-01 1.08350635e+00 -9.83769417e-01 6.55218959e-01 -3.86345625e-01 4.23767231e-02 7.88592756e-01 7.15902448e-01 -6.18741751e-01 8.21781039e-01 -1.83753878e-01 1.80774391e-01 5.75296998e-01 -1.39248300e+00 6.12354755e-01 1.66275799e+00 -4.63594139e-01 -6.25784039e-01 7.60327101e-01 8.13696027e-01 -6.94087505e-01 -1.30082703e+00 3.34633321e-01 8.65424156e-01 -8.75409484e-01 1.61978090e+00 -1.32660246e+00 -4.43697497e-02 2.81152606e-01 -2.61993498e-01 -9.32519078e-01 -5.96193194e-01 -1.23518765e+00 -5.33532679e-01 -5.83747849e-02 5.96577883e-01 -1.13057327e+00 3.42365682e-01 8.74560475e-01 -2.82833427e-01 -6.42737269e-01 -1.06996536e+00 -1.32016802e+00 -3.35779637e-02 -1.45572275e-01 4.90409225e-01 7.63798356e-01 6.83744550e-01 1.09839931e-01 -6.36873543e-02 -1.00294888e-01 5.33176839e-01 9.55312885e-03 4.41501856e-01 -1.34294486e+00 3.86843324e-01 -5.75816095e-01 -3.07655483e-01 -9.45992947e-01 -8.85957032e-02 -8.12076271e-01 -6.53862000e-01 -1.28511906e+00 -8.32044985e-03 -1.91056758e-01 -1.11109078e-01 -1.65725678e-01 3.67937148e-01 2.13746816e-01 1.20859891e-02 1.03788137e-01 -3.71160030e-01 6.18435517e-02 1.29639816e+00 6.91750320e-05 -1.62315920e-01 4.85058486e-01 -4.81304944e-01 7.84440815e-01 8.58408585e-02 -2.99253196e-01 -6.78878546e-01 6.11881316e-02 6.69384480e-01 4.61409837e-02 3.24159935e-02 -7.42885649e-01 5.37211418e-01 -3.75702560e-01 4.78586555e-01 -1.32223868e+00 1.30741090e-01 -9.61415648e-01 6.95283338e-02 9.40189242e-01 2.74610907e-01 1.20424610e-02 8.66204947e-02 5.39500564e-02 -1.44871444e-01 -5.70943117e-01 9.21121240e-01 -4.07591403e-01 -4.92852688e-01 -5.20386267e-03 -1.03226590e+00 8.97834301e-02 9.92593169e-01 -7.84614205e-01 -3.59281451e-01 -4.20183957e-01 -8.29068601e-01 -1.95836127e-02 6.50830388e-01 3.03609259e-02 7.30431557e-01 -1.51530886e+00 -2.30721906e-01 7.18729138e-01 -3.22939813e-01 -3.74400020e-01 -1.70157343e-01 6.58265352e-01 -1.32361674e+00 1.02442718e+00 -5.41665435e-01 -4.55340147e-01 -1.14228773e+00 4.78126436e-01 4.28307921e-01 -2.41845414e-01 -2.15481281e-01 1.11954463e+00 2.71224789e-02 -8.23025763e-01 1.85185194e-01 -9.21545625e-02 -7.54407048e-01 3.55081353e-03 6.88606799e-01 1.05194807e+00 -2.91290224e-01 -6.04341030e-01 -4.56784427e-01 6.65885091e-01 2.32151806e-01 -2.87484169e-01 9.17833567e-01 -2.19243199e-01 -9.89108324e-01 4.28274393e-01 8.38715494e-01 -1.36269778e-01 -3.69319022e-02 4.16855574e-01 1.25943512e-01 -8.02164078e-01 -4.32406247e-01 -3.55811834e-01 -1.85641110e-01 5.54822803e-01 5.34874737e-01 8.99602413e-01 8.57008278e-01 -3.02566767e-01 8.18335712e-01 9.66778398e-01 5.72402716e-01 -1.68019545e+00 -2.13140488e-01 6.89524531e-01 9.12339568e-01 -9.28350806e-01 5.44190466e-01 -7.27165341e-01 -4.14997995e-01 1.32979155e+00 4.68304873e-01 -1.55325383e-01 1.27306652e+00 5.74917436e-01 1.14069022e-02 -3.70670199e-01 -9.44949508e-01 1.12705544e-01 3.75366658e-01 1.11147714e+00 5.06513238e-01 5.07374525e-01 -9.66500878e-01 3.21953118e-01 -7.28706717e-01 -2.34555230e-01 4.90474731e-01 1.41972518e+00 -6.43810987e-01 -1.20391917e+00 -7.23931909e-01 4.61561680e-01 -5.49773455e-01 -1.16372630e-01 -5.28106689e-01 8.46754074e-01 -5.76629937e-02 1.49448860e+00 -1.97535474e-03 -5.03491640e-01 4.11356747e-01 1.41089618e-01 7.21762300e-01 -1.23501487e-01 -9.04846430e-01 4.15413082e-01 3.84890139e-01 -1.23056793e+00 -8.58632207e-01 -1.05834293e+00 -1.40667629e+00 -1.19437599e+00 -5.12782812e-01 1.89310342e-01 3.83317530e-01 3.90289724e-01 -2.06836104e-01 2.85260603e-02 9.80917513e-01 -1.07949340e+00 -3.90341938e-01 -9.39418614e-01 -1.00026262e+00 -7.84516707e-02 2.89751232e-01 -8.00943017e-01 -7.83523321e-01 2.83909619e-01]	[-7.540960788726807, 3.5181708335876465]
efddb8ce-59d4-4ba3-be69-4f6a8964aa62	breaking-the-object-in-video-object	2212.06200	null	https://arxiv.org/abs/2212.06200v2	https://arxiv.org/pdf/2212.06200v2.pdf	Breaking the "Object" in Video Object Segmentation	The appearance of an object can be fleeting when it transforms. As eggs are broken or paper is torn, their color, shape and texture can change dramatically, preserving virtually nothing of the original except for the identity itself. Yet, this important phenomenon is largely absent from existing video object segmentation (VOS) benchmarks. In this work, we close the gap by collecting a new dataset for Video Object Segmentation under Transformations (VOST). It consists of more than 700 high-resolution videos, captured in diverse environments, which are 21 seconds long on average and densely labeled with instance masks. A careful, multi-step approach is adopted to ensure that these videos focus on complex object transformations, capturing their full temporal extent. We then extensively evaluate state-of-the-art VOS methods and make a number of important discoveries. In particular, we show that existing methods struggle when applied to this novel task and that their main limitation lies in over-reliance on static appearance cues. This motivates us to propose a few modifications for the top-performing baseline that improve its capabilities by better modeling spatio-temporal information. But more broadly, the hope is to stimulate discussion on learning more robust video object representations.	['Adrien Gaidon', 'Jie Li', 'Pavel Tokmakov']	2022-12-12	null	http://openaccess.thecvf.com//content/CVPR2023/html/Tokmakov_Breaking_the_Object_in_Video_Object_Segmentation_CVPR_2023_paper.html	http://openaccess.thecvf.com//content/CVPR2023/papers/Tokmakov_Breaking_the_Object_in_Video_Object_Segmentation_CVPR_2023_paper.pdf	cvpr-2023-1	['video-object-segmentation']	['computer-vision']	[ 4.39251810e-01 -2.68442839e-01 -2.52768755e-01 -1.87011942e-01 -4.04736936e-01 -1.02998209e+00 6.24508679e-01 -1.94152579e-01 -2.59526074e-01 5.27947187e-01 -7.83470869e-02 6.46719411e-02 2.06769541e-01 -3.39114338e-01 -9.85143185e-01 -6.78661823e-01 5.30046560e-02 3.78682703e-01 6.32409930e-01 -1.82545260e-01 4.68309298e-02 5.73204160e-01 -1.62667429e+00 3.03202301e-01 5.42968571e-01 8.01423132e-01 -8.45596939e-03 6.88694477e-01 -7.73754250e-03 5.87054968e-01 -4.69928831e-01 -6.00597322e-01 4.97991115e-01 -3.65802914e-01 -1.10117090e+00 4.65407759e-01 1.03648078e+00 -4.14988071e-01 -3.26899976e-01 1.18052888e+00 -2.82859318e-02 2.80851603e-01 7.45935559e-01 -1.34222698e+00 -6.67580664e-01 4.04800087e-01 -7.58575022e-01 4.46286201e-01 3.44236642e-01 3.10386211e-01 8.91450644e-01 -7.35153437e-01 1.18430960e+00 1.19174969e+00 8.04426551e-01 6.02093577e-01 -1.37361515e+00 -3.37075680e-01 5.76163352e-01 1.58678129e-01 -1.20142615e+00 -4.88637090e-01 7.60792911e-01 -7.02088058e-01 6.86877429e-01 5.23418069e-01 9.33687449e-01 1.37670398e+00 -6.65598433e-04 1.20879447e+00 1.02261746e+00 -1.69253320e-01 6.37410656e-02 -6.18079230e-02 9.75977927e-02 4.89108413e-01 3.46654177e-01 -2.64771432e-01 -4.34294909e-01 1.33563429e-01 7.83041477e-01 2.02608094e-01 -4.21327502e-01 -7.74504125e-01 -1.37651026e+00 4.25999194e-01 1.80986136e-01 5.93552709e-01 -5.38471453e-02 1.61328152e-01 2.68045872e-01 2.72011906e-01 6.34328842e-01 4.00890261e-01 -5.19069612e-01 -2.06467643e-01 -1.26797342e+00 4.28870618e-01 6.49005473e-01 9.98816073e-01 8.02517772e-01 7.31696635e-02 -1.88451126e-01 6.43016279e-01 8.60246271e-02 3.32083464e-01 2.45374411e-01 -1.11862648e+00 1.48450449e-01 3.71948928e-01 2.56029405e-02 -1.02201712e+00 -1.27126709e-01 -1.87111109e-01 -5.73368251e-01 1.05738819e-01 7.11180329e-01 1.40596628e-01 -1.33759022e+00 1.57119668e+00 4.71865803e-01 5.75905979e-01 -3.09266776e-01 8.89149249e-01 9.20985222e-01 4.66049969e-01 -5.74422665e-02 -7.20708594e-02 1.38689137e+00 -1.18359184e+00 -7.44698346e-01 -3.01450551e-01 9.03855860e-02 -8.94023836e-01 9.41309810e-01 3.87446523e-01 -1.24518871e+00 -5.16760886e-01 -1.07024539e+00 -9.79432315e-02 -5.41177154e-01 -2.24634498e-01 8.35225701e-01 5.54969847e-01 -1.19627249e+00 7.47608125e-01 -9.50645387e-01 -6.58956289e-01 7.41660178e-01 3.17586690e-01 -4.70097035e-01 -1.09831877e-01 -7.00721681e-01 5.33581793e-01 1.59837484e-01 7.44385421e-02 -7.76796460e-01 -8.39137852e-01 -9.26985741e-01 -3.12478662e-01 5.53169787e-01 -6.72089994e-01 1.22581351e+00 -1.34388208e+00 -1.25538528e+00 1.15197313e+00 -2.77945876e-01 -2.06158519e-01 9.36529934e-01 -4.37826999e-02 -2.70445526e-01 3.78801554e-01 1.23990595e-01 8.67166162e-01 1.31568587e+00 -1.47734320e+00 -5.67154944e-01 -3.44165295e-01 1.49914935e-01 -6.35971455e-03 -2.15672120e-01 2.28673548e-01 -1.11203897e+00 -1.03338969e+00 1.75712496e-01 -9.91632938e-01 -8.05000737e-02 6.53099939e-02 -4.00352478e-01 4.66464236e-02 9.25812542e-01 -6.32068515e-01 1.04392803e+00 -2.20761442e+00 3.64367187e-01 -8.55949596e-02 3.26437175e-01 3.10376346e-01 -2.99139231e-01 1.47168383e-01 -1.14985211e-02 3.44311982e-01 -4.09536779e-01 -4.72759515e-01 -8.83825645e-02 2.36539930e-01 -2.90335447e-01 5.73024988e-01 3.66769433e-01 1.24471021e+00 -8.61873269e-01 -5.85947812e-01 1.31018311e-01 4.04726416e-01 -5.16705275e-01 -1.02123149e-01 -2.47615278e-01 6.12161815e-01 -2.81381100e-01 1.04653549e+00 8.12994659e-01 -2.54922628e-01 -1.41738012e-01 -3.20272237e-01 -6.89773187e-02 -2.16602743e-01 -1.09133291e+00 1.78722370e+00 2.94402748e-01 9.78081107e-01 2.33743727e-01 -9.86179054e-01 3.61654460e-01 5.26547767e-02 9.54503953e-01 -4.90974575e-01 1.66047603e-01 1.99733302e-02 -2.01951072e-01 -6.06613576e-01 5.92851818e-01 1.64929420e-01 2.09248647e-01 2.85099119e-01 1.56035900e-01 -2.65815258e-01 4.85723615e-01 2.76916742e-01 8.72062385e-01 3.91414165e-01 7.34990090e-02 -3.25260103e-01 1.74698785e-01 1.75320178e-01 5.73989153e-01 7.41708279e-01 -4.33253229e-01 9.76314187e-01 3.95232826e-01 -5.80660999e-01 -9.95140553e-01 -1.08836305e+00 -1.58649310e-01 1.12263393e+00 4.54037398e-01 -2.03055575e-01 -9.91110206e-01 -8.38911116e-01 9.05158445e-02 2.01731578e-01 -9.63019073e-01 2.68401466e-02 -6.49276793e-01 -7.68807471e-01 4.07433838e-01 5.56863904e-01 2.07262516e-01 -1.12325263e+00 -4.80529666e-01 4.23270985e-02 -2.75892973e-01 -1.38577461e+00 -7.03944683e-01 -1.22341879e-01 -8.87546897e-01 -1.19013655e+00 -9.29192543e-01 -7.32763290e-01 6.93289161e-01 5.70535183e-01 1.23545980e+00 2.16909274e-01 -4.72012430e-01 7.51451731e-01 -4.12247926e-01 -3.14709365e-01 -1.46145791e-01 -3.71531099e-02 -5.23189940e-02 3.08746338e-01 2.09159344e-01 -5.23700416e-01 -4.58490342e-01 3.11322510e-01 -1.22897732e+00 9.01765153e-02 3.33562583e-01 5.73927999e-01 6.23574376e-01 -2.81234562e-01 6.51672110e-02 -1.03476489e+00 3.06167677e-02 -4.16135103e-01 -4.39639062e-01 3.16310018e-01 -1.09141707e-01 -2.85535902e-01 2.37320513e-01 -7.93765068e-01 -9.14432883e-01 1.64575830e-01 1.24380872e-01 -6.50125504e-01 -2.28722900e-01 -5.78104965e-02 9.74948984e-03 -3.42395306e-01 2.44490638e-01 1.98256925e-01 -2.06879407e-01 -5.46338141e-01 3.65314245e-01 1.79757625e-01 8.41910779e-01 -5.81107497e-01 1.11870122e+00 9.54983711e-01 -3.17378670e-01 -9.49639499e-01 -7.49715686e-01 -5.87657273e-01 -1.02320766e+00 -3.21241587e-01 9.93314207e-01 -7.63005257e-01 -5.08613527e-01 7.01600015e-01 -1.04077613e+00 -6.93511426e-01 -3.20963860e-01 2.21393496e-01 -5.21384835e-01 5.65881670e-01 -6.27970755e-01 -4.80097890e-01 1.35847583e-01 -1.08842576e+00 1.12180161e+00 2.24947929e-01 -8.05647895e-02 -9.46600914e-01 -4.08465695e-03 5.04764378e-01 3.55387986e-01 4.32449907e-01 4.21428531e-01 -4.31780964e-01 -7.69581020e-01 2.06087932e-01 -2.55613744e-01 2.65271783e-01 2.31699169e-01 5.17378032e-01 -9.42177355e-01 -4.25800979e-01 -1.00993827e-01 -1.40881941e-01 1.24066532e+00 4.33561146e-01 1.09882486e+00 -1.31758824e-01 -3.65121782e-01 1.08072460e+00 1.21560967e+00 1.46832779e-01 4.34070498e-01 4.02765572e-01 1.05484474e+00 6.08829379e-01 6.28523707e-01 1.88963309e-01 2.99354076e-01 8.43650579e-01 4.36896592e-01 -3.59844476e-01 -4.13418084e-01 3.10453437e-02 4.11470324e-01 5.38895965e-01 -3.96775246e-01 -2.62517810e-01 -8.09380054e-01 6.77605927e-01 -1.83897948e+00 -9.65245605e-01 -2.21086621e-01 1.94980645e+00 7.65327334e-01 -5.87717853e-02 3.25945199e-01 -7.54250139e-02 6.98211908e-01 3.64604741e-01 -6.58010483e-01 -1.11320755e-02 -3.46774995e-01 2.04505641e-02 5.91403842e-01 2.50305325e-01 -1.58554721e+00 1.19452631e+00 7.12307072e+00 6.50459886e-01 -1.17246246e+00 -3.90337259e-02 7.08152413e-01 -8.48159343e-02 -3.83318663e-01 -1.67443857e-01 -5.82299769e-01 4.58749712e-01 2.45999157e-01 8.90021622e-02 6.71626329e-01 6.52748406e-01 -8.31165984e-02 2.50827111e-02 -1.20114934e+00 1.17261362e+00 3.96895349e-01 -1.32645500e+00 -1.08914422e-02 -2.04668209e-01 1.09913337e+00 4.71872203e-02 2.89340228e-01 6.23770244e-02 1.50923312e-01 -9.90749419e-01 1.13575566e+00 4.62023407e-01 6.94740534e-01 -2.34690726e-01 4.28261429e-01 -2.38313183e-01 -1.36789584e+00 1.94643781e-01 -2.11812958e-01 1.36967406e-01 1.68939129e-01 1.43531591e-01 -4.93545145e-01 4.71373141e-01 1.02780950e+00 1.09086764e+00 -9.62448537e-01 1.09969747e+00 1.08988933e-01 5.76910496e-01 -2.77905315e-01 3.34109515e-01 3.78384560e-01 -3.46909940e-01 6.50365114e-01 1.38272572e+00 1.39673173e-01 7.60981143e-02 1.81107044e-01 8.10997307e-01 -1.71116233e-01 -2.02137157e-02 -6.04751766e-01 -2.41088554e-01 1.10831149e-01 1.26561511e+00 -1.24554694e+00 -4.41730767e-01 -6.43309593e-01 1.20081103e+00 9.68898237e-02 7.07504332e-01 -9.65892434e-01 1.19869217e-01 8.35894287e-01 1.24472015e-01 6.36924267e-01 -1.63969427e-01 -8.50404650e-02 -1.48880064e+00 1.61825523e-01 -9.35167491e-01 4.09105182e-01 -6.32882178e-01 -1.31291950e+00 4.43237871e-01 1.01039015e-01 -1.11770880e+00 -5.19421510e-02 -5.83124638e-01 -4.35441971e-01 1.45016477e-01 -1.51759362e+00 -1.42702031e+00 -4.32321131e-01 6.84409022e-01 8.97534132e-01 1.03213519e-01 2.66769081e-01 4.59505349e-01 -6.44652069e-01 4.31179971e-01 6.60983473e-02 3.29759568e-01 8.14215481e-01 -1.16252148e+00 6.55085623e-01 1.12112033e+00 6.56471312e-01 4.42101240e-01 7.56051064e-01 -6.01011693e-01 -1.54251587e+00 -1.10688138e+00 3.58331203e-01 -7.46255517e-01 6.24790668e-01 -5.68433404e-01 -1.06435990e+00 1.04630888e+00 4.70382795e-02 4.07204419e-01 2.90423930e-01 -1.54337138e-01 -3.98238212e-01 7.59258270e-02 -9.37027693e-01 7.15178788e-01 1.29357660e+00 -3.52239370e-01 -5.60452104e-01 2.53821254e-01 5.85430801e-01 -5.43525755e-01 -6.51372612e-01 4.52090740e-01 6.63927615e-01 -1.08960140e+00 1.24897206e+00 -8.97330701e-01 1.67646915e-01 -4.10161853e-01 -8.25219695e-03 -8.94745111e-01 -2.61536866e-01 -8.32942128e-01 -9.93124470e-02 1.37112617e+00 1.13494352e-01 -4.32950735e-01 9.05334473e-01 4.81367946e-01 -1.11133434e-01 -6.28923178e-01 -7.23840535e-01 -8.79444480e-01 -1.45386219e-01 -4.02094245e-01 4.19704854e-01 1.21065724e+00 -4.28900838e-01 -1.58063218e-01 -4.26186293e-01 -4.04069424e-02 5.54984391e-01 2.23468795e-01 8.73204112e-01 -1.24781525e+00 -2.09788948e-01 -6.50288880e-01 -5.85445166e-01 -1.17381155e+00 -3.42033524e-03 -6.50487959e-01 3.06498688e-02 -1.22949731e+00 5.01877666e-01 -1.43746793e-01 -3.06256533e-01 4.88918513e-01 -3.85615498e-01 9.29165661e-01 3.65185589e-01 1.99436009e-01 -1.01195157e+00 3.09104204e-01 1.50144303e+00 -4.38510954e-01 -1.00511760e-01 -2.44057141e-02 -4.67197865e-01 9.66995955e-01 7.04944253e-01 -4.17872429e-01 -2.42284387e-01 -5.38935661e-01 -1.41731232e-01 -4.09291595e-01 5.17583549e-01 -7.88078666e-01 3.54942195e-02 -3.73869091e-01 4.81218159e-01 -4.98302579e-01 4.04075027e-01 -7.65686929e-01 3.30125034e-01 3.01650673e-01 -2.39758031e-03 1.86869444e-03 2.57977575e-01 6.05199099e-01 -1.96801722e-01 -9.11305025e-02 7.97815025e-01 -1.22900985e-01 -9.47530508e-01 6.42844141e-01 -2.94248551e-01 4.00803924e-01 1.28941035e+00 -6.20472372e-01 -3.46072614e-02 -1.67846709e-01 -6.89111650e-01 -4.02124636e-02 1.02129400e+00 6.95030808e-01 3.60914379e-01 -1.18166125e+00 -6.16213799e-01 2.23241702e-01 6.93845525e-02 2.38578618e-02 3.60529631e-01 9.65691864e-01 -6.87348366e-01 1.83505908e-01 -3.25999409e-01 -8.02635789e-01 -1.54922688e+00 6.11608148e-01 1.39624134e-01 1.47187322e-01 -8.24309289e-01 9.90653276e-01 4.62016374e-01 5.48782833e-02 2.59270221e-01 -5.75604260e-01 -2.05956712e-01 2.34955892e-01 5.30918241e-01 2.92266279e-01 -1.20691903e-01 -7.99575746e-01 -4.39563245e-01 9.09149170e-01 -9.61941034e-02 3.93237220e-03 1.43074048e+00 -1.47542760e-01 -1.85300842e-01 5.38272142e-01 1.06003833e+00 2.36300960e-01 -1.75609350e+00 -1.58160076e-01 -5.87374680e-02 -8.00195873e-01 -3.56134176e-01 -4.76024747e-01 -1.39399827e+00 7.30563045e-01 3.15954775e-01 3.58319432e-01 1.03678131e+00 2.85488874e-01 7.71668494e-01 1.63511679e-01 1.32224530e-01 -1.05998874e+00 3.22858006e-01 4.79600698e-01 6.67764068e-01 -1.31200743e+00 6.30291924e-02 -6.51188552e-01 -6.82093143e-01 1.11812031e+00 4.76089090e-01 -1.26003101e-01 2.80384213e-01 1.77583829e-01 1.26726136e-01 -2.68480569e-01 -3.97722483e-01 -2.50560075e-01 5.00381649e-01 7.89664924e-01 1.76193580e-01 -1.55043870e-01 1.10036418e-01 4.20942128e-01 -8.13645422e-02 -4.53027844e-01 4.79390264e-01 7.21172214e-01 -1.76095098e-01 -9.26263869e-01 -3.78095150e-01 2.70411044e-01 -6.45859897e-01 5.60072996e-02 -5.23334682e-01 9.68877852e-01 2.89097399e-01 6.59003794e-01 8.88441578e-02 -9.63851362e-02 9.13734287e-02 -2.24837661e-02 7.55535603e-01 -4.22967285e-01 -3.65740329e-01 6.31774664e-02 -2.73277611e-01 -9.09542620e-01 -7.47529328e-01 -1.09934235e+00 -9.81486499e-01 -1.93936169e-01 1.82119291e-02 -2.93719262e-01 5.34505010e-01 8.80567610e-01 1.84891699e-03 6.17638469e-01 3.19899410e-01 -1.27011847e+00 -1.25376433e-01 -4.95456904e-01 -4.55474019e-01 9.36748087e-01 5.35689354e-01 -8.28978121e-01 -3.10316205e-01 6.08848751e-01]	[9.171525001525879, -0.21019823849201202]
ad81fb24-3d93-4743-a79a-65f94b7bdc23	sample-and-predict-your-latent-modality-free	2305.15924	null	https://arxiv.org/abs/2305.15924v1	https://arxiv.org/pdf/2305.15924v1.pdf	Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation	Unsupervised disentanglement is a long-standing challenge in representation learning. Recently, self-supervised techniques achieved impressive results in the sequential setting, where data is time-dependent. However, the latter methods employ modality-based data augmentations and random sampling or solve auxiliary tasks. In this work, we propose to avoid that by generating, sampling, and comparing empirical distributions from the underlying variational model. Unlike existing work, we introduce a self-supervised sequential disentanglement framework based on contrastive estimation with no external signals, while using common batch sizes and samples from the latent space itself. In practice, we propose a unified, efficient, and easy-to-code sampling strategy for semantically similar and dissimilar views of the data. We evaluate our approach on video, audio, and time series benchmarks. Our method presents state-of-the-art results in comparison to existing techniques. The code is available at https://github.com/azencot-group/SPYL.	['Omri Azencot', 'Nimrod Berman', 'Ilan Naiman']	2023-05-25	null	null	null	null	['disentanglement']	['methodology']	[ 2.71263838e-01 -1.86437070e-01 -3.88821959e-01 -2.38288686e-01 -1.21660495e+00 -6.18435681e-01 9.26171243e-01 -1.34088933e-01 -2.29096696e-01 6.27811491e-01 4.81514722e-01 -3.38071994e-02 8.14569890e-02 -3.44071716e-01 -5.66097617e-01 -7.53505945e-01 1.42304897e-01 5.82265198e-01 -3.32821429e-01 1.15693636e-01 -2.68873642e-04 3.47718745e-02 -1.55736828e+00 2.14247197e-01 6.30978584e-01 7.48597980e-01 5.84069528e-02 6.90263271e-01 2.08849907e-01 7.64450252e-01 -1.21474788e-01 -8.42440203e-02 1.99127063e-01 -7.25339234e-01 -5.58291435e-01 3.29150707e-01 4.44205403e-01 -2.69732744e-01 -4.73050952e-01 9.09101427e-01 5.56738555e-01 2.56099761e-01 7.95797706e-01 -1.37993455e+00 -5.83989859e-01 5.56693196e-01 -5.60199559e-01 1.45469829e-01 3.90097678e-01 3.08664609e-02 1.18436742e+00 -1.09013414e+00 5.66038609e-01 1.01928520e+00 4.39880759e-01 6.59511507e-01 -1.93864930e+00 -7.06993401e-01 1.75313741e-01 2.66042680e-01 -1.37089181e+00 -1.06150949e+00 1.09864974e+00 -5.56967020e-01 4.84828919e-01 2.91511118e-01 4.51035529e-01 1.86203194e+00 -5.32201171e-01 1.07414842e+00 1.21398938e+00 -5.42952657e-01 3.75132650e-01 1.55307129e-01 -1.69941172e-01 5.40950537e-01 -1.39321864e-01 1.00778505e-01 -7.86194444e-01 -4.96700436e-01 7.93280482e-01 2.06181839e-01 -3.48737091e-01 -9.22693729e-01 -1.38596511e+00 8.96192670e-01 -1.91290915e-01 1.00422487e-01 -3.10535312e-01 1.92790538e-01 4.98885274e-01 3.53317738e-01 8.47181261e-01 7.73067027e-02 -4.29886848e-01 -3.92191529e-01 -1.25828314e+00 1.37795284e-01 7.26221025e-01 8.32276583e-01 5.28529465e-01 3.24252635e-01 -1.94710746e-01 8.14345717e-01 3.99457365e-01 4.44734126e-01 7.43193686e-01 -1.12079132e+00 3.79039466e-01 -4.90308404e-02 6.82789013e-02 -5.87611914e-01 8.20885524e-02 -3.75266701e-01 -9.42712843e-01 1.55567210e-02 4.33112115e-01 -3.44078764e-02 -7.75120735e-01 2.07918000e+00 3.55822206e-01 7.90491819e-01 5.67959063e-03 7.23921895e-01 6.51315749e-01 5.20963192e-01 -2.35088304e-01 -4.27965879e-01 1.14498973e+00 -1.12866366e+00 -7.98986971e-01 -7.90455937e-02 2.86433965e-01 -6.28951728e-01 1.22531426e+00 5.55409014e-01 -1.15171587e+00 -5.25110662e-01 -8.27188075e-01 -6.84694126e-02 1.30436763e-01 3.46469760e-01 4.97517973e-01 4.85361010e-01 -9.00499523e-01 6.24629140e-01 -1.21886504e+00 -2.91559577e-01 4.85487878e-01 -2.26792395e-02 -4.06164140e-01 -9.42876190e-03 -7.80810475e-01 3.50895941e-01 9.89560857e-02 -1.55636206e-01 -1.33262277e+00 -7.11362064e-01 -9.94873345e-01 -2.17793971e-01 5.73900700e-01 -7.43337870e-01 1.32605350e+00 -9.69146669e-01 -1.75256395e+00 8.52796733e-01 -3.66251469e-01 -4.63197142e-01 6.23919725e-01 -4.78733927e-01 -2.40738988e-01 1.79028675e-01 8.36947113e-02 4.15700614e-01 1.31279850e+00 -1.24877071e+00 -1.61274821e-02 -1.72956422e-01 -3.51379402e-02 2.71571487e-01 -4.05699998e-01 -1.56009257e-01 -4.14908767e-01 -9.00384784e-01 7.57420361e-02 -9.66092646e-01 -1.77212626e-01 2.80671656e-01 -4.30750012e-01 -3.46092954e-02 4.64405596e-01 -5.02845287e-01 9.88480210e-01 -2.49495959e+00 4.81139094e-01 -6.62807226e-02 3.94364119e-01 -1.85152575e-01 -1.89033851e-01 5.63795269e-01 -3.06551367e-01 -2.54224807e-01 -4.18305427e-01 -1.13837731e+00 2.14913949e-01 1.52854055e-01 -6.03190839e-01 7.31717288e-01 -3.43905599e-03 5.75303257e-01 -1.06331527e+00 -4.75324780e-01 1.50938720e-01 4.85912561e-01 -7.72711813e-01 4.71447527e-01 -3.17892253e-01 9.44920838e-01 -1.49508789e-01 4.43928152e-01 3.94113213e-01 -5.46502531e-01 3.81612599e-01 -3.07735205e-01 1.64822146e-01 4.82691556e-01 -1.17091548e+00 2.35762763e+00 -4.61085111e-01 6.87115550e-01 8.88280571e-03 -1.29463315e+00 5.88242114e-01 6.35505080e-01 5.90317369e-01 -2.73788452e-01 4.32850160e-02 1.77933976e-01 -4.20250803e-01 -4.38000023e-01 3.08808506e-01 -1.27349228e-01 9.57659557e-02 7.09837377e-01 3.92854154e-01 -1.01819769e-01 1.51525453e-01 3.08220863e-01 8.78552675e-01 6.98231995e-01 4.29491460e-01 7.83730745e-02 2.41858497e-01 -3.58022153e-01 4.61454213e-01 6.69146061e-01 -1.89664420e-02 1.02046418e+00 4.35737371e-01 2.69422289e-02 -1.00885069e+00 -1.39083767e+00 -3.63567993e-02 9.02413905e-01 -2.39187330e-01 -6.82724774e-01 -4.42095429e-01 -6.09848082e-01 -3.10315907e-01 6.35609925e-01 -6.44575834e-01 1.14249391e-02 -2.53457308e-01 -5.10674357e-01 3.36247921e-01 5.16389549e-01 1.48153799e-02 -7.23579228e-01 -2.48968288e-01 1.30274683e-01 -4.99060243e-01 -1.20333278e+00 -5.39142251e-01 3.95713709e-02 -1.11003745e+00 -7.74954081e-01 -8.10707986e-01 -3.27609420e-01 6.86750650e-01 2.05343515e-01 1.20774722e+00 -4.79413390e-01 -1.01986073e-01 6.94957972e-01 -2.99075067e-01 -3.57344113e-02 -1.61743984e-01 8.86771977e-02 1.77682802e-01 3.91924322e-01 5.46632484e-02 -1.13358736e+00 -6.08196557e-01 1.16187267e-01 -9.42083895e-01 2.81489909e-01 2.28742406e-01 1.08501852e+00 7.70349681e-01 -5.93620121e-01 4.15987462e-01 -1.02076566e+00 3.60358596e-01 -7.54201412e-01 -4.72154737e-01 -1.08095549e-01 -5.97301245e-01 1.88785359e-01 5.64582884e-01 -7.84857333e-01 -9.05166030e-01 8.45507383e-02 1.45256400e-01 -9.48620081e-01 -2.60079056e-01 4.90679711e-01 -9.09221619e-02 5.00596941e-01 6.44346178e-01 4.62427765e-01 2.43170574e-01 -8.07932138e-01 7.27597773e-01 3.80670846e-01 4.44666684e-01 -8.41319203e-01 9.54237819e-01 9.16452289e-01 -3.67965400e-01 -5.96699536e-01 -9.74711120e-01 -4.26111042e-01 -6.22001290e-01 -6.30090293e-03 3.91765058e-01 -1.27645934e+00 -2.86778718e-01 2.96951324e-01 -8.75789881e-01 -5.50811946e-01 -7.74349213e-01 7.32410073e-01 -8.86245251e-01 5.48722744e-01 -5.30836046e-01 -8.64815950e-01 -9.08917412e-02 -7.89584875e-01 1.21279991e+00 -1.53145552e-01 -3.95087272e-01 -1.04268062e+00 6.30628526e-01 3.91528994e-01 3.00755978e-01 2.91296542e-01 3.40856284e-01 -7.30422318e-01 -4.80804592e-01 3.85956131e-02 1.43756047e-01 3.97494733e-01 2.66687900e-01 -1.83141932e-01 -1.26573217e+00 -5.11090517e-01 1.30006328e-01 -5.90549529e-01 9.09917772e-01 2.68438756e-01 1.26449740e+00 -4.21264231e-01 -1.16203457e-01 7.91195214e-01 1.22568595e+00 -3.84249955e-01 3.42732012e-01 -6.42315671e-02 6.75630331e-01 4.57468808e-01 3.92556071e-01 8.17869604e-01 5.14281988e-01 7.35456705e-01 2.69091278e-01 4.30125855e-02 7.81428907e-03 -3.25876057e-01 6.21709287e-01 1.03864896e+00 -1.47771299e-01 -1.63101941e-01 -5.60554504e-01 7.90886760e-01 -1.96589148e+00 -1.08658767e+00 1.56311691e-01 2.26058173e+00 1.14793289e+00 -1.21046290e-01 3.01880658e-01 1.87737525e-01 4.24283355e-01 5.80141783e-01 -5.94943762e-01 2.62617886e-01 -1.79173928e-02 2.85669506e-01 3.58338133e-02 4.16105151e-01 -1.11147499e+00 6.08840406e-01 5.58629751e+00 8.55373740e-01 -9.01958764e-01 5.17854512e-01 4.04655486e-01 -6.48588419e-01 -4.62930351e-01 1.65153652e-01 -3.33910137e-01 3.98099899e-01 1.12410927e+00 -5.95643334e-02 6.56771183e-01 5.47581673e-01 2.40934029e-01 1.73991159e-01 -1.54511869e+00 1.13972008e+00 2.59379655e-01 -1.22466457e+00 -3.30399692e-01 -2.92581487e-02 7.44375646e-01 2.10444376e-01 2.45756969e-01 2.07741246e-01 2.65284479e-01 -6.59104466e-01 8.52554142e-01 7.09681034e-01 9.35767293e-01 -2.98731595e-01 7.50718191e-02 2.96124309e-01 -1.14562476e+00 3.06867331e-01 -2.50312798e-02 1.69325080e-02 2.10613027e-01 6.69359028e-01 -2.46786624e-01 6.66445255e-01 5.26998222e-01 1.11939573e+00 -3.00327480e-01 7.47677088e-01 -3.04316998e-01 9.65472698e-01 -3.28672528e-01 3.72335315e-01 -1.96714938e-01 -2.59558290e-01 7.77937055e-01 9.52661932e-01 2.85302937e-01 -1.62447363e-01 2.37752646e-01 9.54198182e-01 -1.43696144e-01 -2.12920364e-02 -6.95387602e-01 -1.59774050e-01 4.80496764e-01 1.12231851e+00 -3.71740013e-01 -5.06304264e-01 -5.21019816e-01 1.18911350e+00 3.58077705e-01 5.92554748e-01 -8.39305937e-01 4.24120985e-02 5.62628627e-01 -7.61943907e-02 4.48634565e-01 -4.82834548e-01 9.72337127e-02 -1.81310284e+00 1.49296328e-01 -1.02686429e+00 4.70126808e-01 -7.62745500e-01 -1.47084224e+00 4.38892603e-01 3.18110228e-01 -1.62599194e+00 -5.66915393e-01 -2.35445842e-01 -4.08844441e-01 6.26369059e-01 -1.41813850e+00 -9.98385906e-01 -2.24104494e-01 7.38601506e-01 6.81805611e-01 -2.01139867e-01 1.06471360e+00 3.31930578e-01 -4.65909868e-01 5.27368605e-01 4.71744955e-01 1.60903502e-02 8.29713702e-01 -1.27732396e+00 2.08196715e-01 7.48640597e-01 7.47611821e-01 5.23797274e-01 7.05401421e-01 -2.02762991e-01 -1.40509629e+00 -8.14902365e-01 5.17307103e-01 -5.51555932e-01 9.45400298e-01 -7.90555477e-01 -7.84353197e-01 8.10348690e-01 4.77694720e-01 3.93686891e-01 1.10287631e+00 1.38410136e-01 -7.23099530e-01 -6.43294305e-02 -8.58924091e-01 7.36755967e-01 1.11511993e+00 -9.09553766e-01 -4.37013328e-01 4.65976387e-01 5.84491134e-01 -4.19418931e-01 -7.55532146e-01 5.29986732e-02 6.52864635e-01 -8.53681386e-01 9.90489423e-01 -5.56561053e-01 5.43404996e-01 -2.44361997e-01 -3.02720815e-01 -1.30244434e+00 -9.04927682e-03 -1.04309618e+00 -8.19531322e-01 1.33546937e+00 3.36130917e-01 -6.15101099e-01 7.17826545e-01 2.65009761e-01 2.36393765e-01 -5.11986673e-01 -8.48956525e-01 -8.40685964e-01 -1.71921074e-01 -5.06911993e-01 3.01639289e-01 1.05349219e+00 -9.56235230e-02 4.04763907e-01 -7.65387356e-01 1.39493361e-01 1.06536067e+00 3.23230773e-01 9.71856236e-01 -1.11462772e+00 -8.25719893e-01 -1.18340418e-01 -4.37133983e-02 -1.27984893e+00 3.13089341e-01 -8.93354237e-01 -7.41029717e-03 -1.15407395e+00 3.26523811e-01 -9.56113264e-02 -4.01357204e-01 3.53238344e-01 5.04242405e-02 4.24683958e-01 1.78997606e-01 5.83321452e-01 -6.53999150e-01 1.04310071e+00 8.97616863e-01 -1.16285577e-01 -9.02890489e-02 6.37032697e-03 -6.44864559e-01 5.90142488e-01 8.58970642e-01 -6.25912786e-01 -6.82718039e-01 -3.32242221e-01 4.96516973e-02 2.38805771e-01 6.49465501e-01 -6.58637822e-01 1.30665511e-01 -5.87826520e-02 5.47197228e-03 -5.97706497e-01 7.45495081e-01 -7.40461290e-01 2.45818824e-01 1.11164242e-01 -5.32453120e-01 -4.81246226e-02 8.84731114e-02 8.71206105e-01 -2.24578470e-01 -1.55933186e-01 4.77328390e-01 -1.15845650e-02 -2.29740724e-01 4.08513397e-01 -3.31994593e-01 3.16780627e-01 6.21977687e-01 8.41970146e-02 -5.91175072e-02 -6.87588573e-01 -1.00797915e+00 3.95832583e-03 3.24618161e-01 3.15981835e-01 6.17142260e-01 -1.53624320e+00 -8.54446113e-01 3.18083078e-01 3.72860253e-01 1.41908154e-02 2.39692539e-01 1.08391154e+00 1.46870032e-01 -4.19723988e-02 9.40244272e-02 -7.45893419e-01 -1.05717957e+00 4.06476110e-01 5.81642939e-03 -2.85753280e-01 -5.87659299e-01 6.11840367e-01 2.35271409e-01 -4.73285586e-01 2.09926039e-01 -1.91361800e-01 -1.31403893e-01 2.46120721e-01 3.23219210e-01 3.17534059e-01 -2.72596896e-01 -4.24799263e-01 -1.46476820e-01 2.28503764e-01 -6.23296909e-02 -6.47485018e-01 1.55723500e+00 -2.64923811e-01 7.94697106e-02 1.11104691e+00 1.26480210e+00 1.31334156e-01 -1.54906213e+00 -8.09801280e-01 -2.92202830e-01 -5.08787096e-01 -3.04897390e-02 -3.93612504e-01 -1.07781732e+00 8.21600437e-01 4.82412487e-01 2.91223675e-01 1.12084651e+00 1.38271838e-01 3.88227344e-01 1.41770884e-01 2.24859163e-01 -8.07052672e-01 2.90551513e-01 1.64174616e-01 9.28513467e-01 -1.24238896e+00 8.74682888e-02 -1.37287512e-01 -6.52201355e-01 7.23290622e-01 3.12720060e-01 -3.37294102e-01 7.82296419e-01 9.85113308e-02 -1.46661624e-01 -1.12553574e-01 -1.08201158e+00 -1.20949484e-01 3.76378238e-01 5.70785701e-01 5.27976513e-01 -2.15894282e-02 5.16582429e-02 4.44855422e-01 -1.99219286e-02 4.40378301e-02 4.64954495e-01 9.59745347e-01 2.35522494e-01 -1.28619444e+00 -1.76591203e-01 3.38471055e-01 -3.56765419e-01 -3.60005558e-01 5.18572666e-02 4.77208763e-01 -4.38123941e-01 7.45015740e-01 -1.01177292e-02 -5.79042062e-02 7.66574731e-03 1.86144665e-01 7.22151279e-01 -7.25883245e-01 5.67188812e-03 4.82240051e-01 1.01626456e-01 -6.10326707e-01 -9.28464174e-01 -1.17569280e+00 -6.88242018e-01 6.20161146e-02 -2.82802492e-01 1.35197118e-01 4.00632709e-01 8.51071656e-01 4.50964600e-01 4.11464989e-01 8.79994035e-01 -1.13769984e+00 -7.89919734e-01 -1.07875836e+00 -4.97972965e-01 5.20075977e-01 6.02456927e-01 -7.18274415e-01 -5.63500941e-01 3.98862153e-01]	[10.699224472045898, 0.3126383423805237]
e8dc52e8-a717-4b20-a71e-6c6b528c047d	a-geometric-analysis-of-deep-generative-image	null	null	https://openreview.net/forum?id=GH7QRzUDdXG	https://openreview.net/pdf?id=GH7QRzUDdXG	A Geometric Analysis of Deep Generative Image Models and Its Applications	Generative adversarial networks have emerged as a powerful unsupervised method to model the statistical patterns of real-world data sets, such as natural images. These networks are trained to map random inputs in their latent space to new samples representative of the learned data. However, the structure of the latent space is hard to intuit due to its high dimensionality and the non-linearity of the generator, which limits the usefulness of the models. Understanding the latent space requires a way to identify input codes for existing real-world images (inversion), and a way to identify directions with known image transformations (interpretability). Here, we use a geometric framework to address both issues simultaneously. We develop an architecture-agnostic method to compute the Riemannian metric of the image manifold created by GANs. The eigen-decomposition of the metric isolates axes that account for different levels of image variability. An empirical analysis of several pretrained GANs shows that image variation around each position is concentrated along surprisingly few major axes (the space is highly anisotropic) and the directions that create this large variation are similar at different positions in the space (the space is homogeneous). We show that many of the top eigenvectors correspond to interpretable transforms in the image space, with a substantial part of eigenspace corresponding to minor transforms which could be compressed out. This geometric understanding unifies previous results of GAN inversion and interpretation. We show that the use of this metric allows for more efficient optimization in the latent space (e.g. GAN inversion) and facilitates unsupervised discovery of interpretable axes. Our results show that defining the geometry of the GAN image manifold can serve as a general framework for understanding GANs.	['Carlos R Ponce', 'Binxu Wang']	2021-01-01	null	null	null	iclr-2021-1	['image-variation']	['computer-vision']	[ 4.66536731e-01 4.01199609e-01 7.33197667e-03 -2.35974893e-01 -3.01571518e-01 -1.14360607e+00 9.37323451e-01 -7.00220764e-01 1.67210191e-01 3.50690424e-01 4.87446219e-01 -1.63109377e-01 -1.58212453e-01 -8.33198249e-01 -8.59401882e-01 -1.03629506e+00 1.25555366e-01 6.68995380e-01 -3.98698717e-01 -2.61280358e-01 1.09233022e-01 5.86291730e-01 -1.24925327e+00 1.31537363e-01 5.64502299e-01 3.99854183e-01 -5.41628199e-03 7.91593909e-01 5.77372089e-02 2.84285873e-01 -5.13264000e-01 -2.75033355e-01 6.29822075e-01 -1.01543784e+00 -8.02683771e-01 4.34184641e-01 4.26413357e-01 -2.11732369e-02 -1.63365543e-01 1.05093086e+00 -1.25281855e-01 -1.41464159e-01 1.04664600e+00 -1.44927943e+00 -9.09864604e-01 2.30941772e-01 -2.98703521e-01 -2.65820861e-01 1.09949641e-01 1.24692194e-01 1.14759147e+00 -6.20543361e-01 8.95470083e-01 1.10486424e+00 3.96870881e-01 5.76682150e-01 -1.66073740e+00 -1.19880907e-01 -2.38811031e-01 -1.82513371e-01 -1.23055899e+00 -3.78332227e-01 9.05909359e-01 -7.56704688e-01 4.01664197e-01 5.88856399e-01 6.78862512e-01 9.92433310e-01 3.22553396e-01 4.16549534e-01 1.14000213e+00 -6.77530468e-01 2.48325467e-01 1.45921424e-01 -3.27543199e-01 6.31897628e-01 1.12085946e-01 8.28927457e-02 -3.25705886e-01 1.05820000e-01 1.06113839e+00 4.63147126e-02 -3.82575393e-01 -1.02867699e+00 -1.40441251e+00 1.08368444e+00 5.26365936e-01 4.22629267e-01 -2.17509791e-01 1.63708851e-01 -1.72723159e-01 3.11861604e-01 2.56906420e-01 9.29420531e-01 -2.24179596e-01 -1.31933495e-01 -6.32505298e-01 -6.57026423e-03 7.27085352e-01 8.65286529e-01 1.04874945e+00 1.88616753e-01 2.43794605e-01 5.07737935e-01 2.13677511e-01 5.28224885e-01 5.15912890e-01 -1.20210731e+00 2.57805109e-01 6.04392827e-01 -2.70814210e-01 -1.05607557e+00 -3.24037895e-02 -3.94080341e-01 -9.78048742e-01 4.66189623e-01 6.77308619e-01 3.48390937e-02 -1.00182199e+00 2.07146645e+00 -6.91065267e-02 -1.76344022e-01 -2.22730972e-02 6.11826777e-01 -7.60166124e-02 5.73665440e-01 -4.55902845e-01 1.07163735e-01 1.17015576e+00 -6.16801798e-01 -4.10193950e-01 -2.41041854e-01 5.30661047e-01 -6.31211162e-01 1.40953207e+00 -1.25465926e-03 -1.00074494e+00 -3.02820265e-01 -1.15723956e+00 7.07508847e-02 -4.36212927e-01 -6.16569014e-05 6.15546286e-01 8.19937885e-01 -1.28273523e+00 6.18879795e-01 -9.77111816e-01 -5.62216878e-01 3.13514680e-01 3.07554960e-01 -5.16897559e-01 1.22817390e-01 -6.66370332e-01 6.88803375e-01 1.50070667e-01 4.97322530e-02 -7.36861348e-01 -4.58063900e-01 -8.64988029e-01 -1.37296975e-01 5.23277335e-02 -8.53014946e-01 6.88879430e-01 -1.27071249e+00 -1.49450302e+00 9.52511728e-01 -2.98953772e-01 -7.27124736e-02 5.02197504e-01 1.49443805e-01 -2.28981480e-01 9.67120752e-02 9.20793042e-02 6.22314572e-01 1.36072993e+00 -1.44395816e+00 1.23843858e-02 -3.97207856e-01 1.37922719e-01 1.61454499e-01 -3.47058654e-01 -3.11331600e-01 -1.34602070e-01 -8.06704044e-01 4.68839437e-01 -1.33102906e+00 -2.13975325e-01 -1.02870621e-01 -6.94693863e-01 5.61652660e-01 8.18196535e-01 -4.88735765e-01 8.07652354e-01 -2.06288648e+00 6.86168075e-01 5.49040020e-01 4.95456308e-01 -3.12259346e-01 -1.12988785e-01 5.23307681e-01 -4.72146392e-01 4.71267641e-01 -4.57658917e-01 -1.50883213e-01 -2.08450641e-04 5.42949378e-01 -5.86914420e-01 5.26082456e-01 2.66959637e-01 1.14856398e+00 -7.33960032e-01 5.94677031e-02 8.40527341e-02 4.19631183e-01 -6.36155427e-01 2.32828930e-01 -1.30225331e-01 8.26399207e-01 -2.99438536e-01 9.86784771e-02 4.27383095e-01 -3.44287962e-01 1.44196495e-01 -3.01025897e-01 1.21320724e-01 2.46874183e-01 -9.27545607e-01 1.64091980e+00 -4.37934250e-01 8.94805014e-01 -2.55746156e-01 -1.07101536e+00 6.11845732e-01 7.38623366e-02 3.70378315e-01 -2.15463147e-01 -3.43195489e-03 -3.43085378e-02 2.11565629e-01 -1.43906847e-01 2.16587633e-01 -3.00451368e-01 1.87672284e-02 9.02897477e-01 9.96576846e-02 -3.31520140e-01 -3.73984016e-02 3.49951833e-01 1.05708086e+00 3.97131629e-02 1.35988936e-01 -4.54692900e-01 2.75682241e-01 -1.89034760e-01 1.80204466e-01 5.99728405e-01 4.09175247e-01 1.05213130e+00 6.97812915e-01 -5.63619673e-01 -1.41716003e+00 -1.52803040e+00 -4.73801978e-02 5.65166712e-01 -1.22854039e-01 -4.77579266e-01 -1.03755260e+00 -6.22758985e-01 -3.61450940e-01 6.94353044e-01 -9.90641177e-01 -4.50739056e-01 -4.70211357e-01 -7.62134731e-01 3.14775288e-01 3.39789122e-01 2.55403250e-01 -8.23791683e-01 -4.91516203e-01 -2.76769549e-01 -1.01184823e-01 -9.33879733e-01 -4.80770081e-01 1.80844724e-01 -9.44508612e-01 -8.83606851e-01 -5.13782680e-01 -4.43944156e-01 1.32856059e+00 2.17736587e-02 1.18282032e+00 -1.22822084e-01 -2.94173330e-01 6.96198881e-01 -6.79953769e-02 -1.58906758e-01 -8.06235313e-01 -8.36105421e-02 -7.07894098e-03 2.29763508e-01 1.02210224e-01 -9.49061334e-01 -3.53620559e-01 5.15222371e-01 -1.15074813e+00 3.04428875e-01 4.79128987e-01 8.81869316e-01 5.26198626e-01 1.17701136e-01 8.42656381e-03 -9.46313024e-01 4.87510592e-01 -3.35534245e-01 -4.39875424e-01 2.60916978e-01 -5.11205614e-01 6.49958789e-01 7.35969782e-01 -3.10606271e-01 -6.91134810e-01 1.45790488e-01 2.87392765e-01 -2.35205412e-01 -1.78876579e-01 2.31323212e-01 -4.89062637e-01 -3.97101603e-02 7.50207961e-01 3.26983422e-01 2.60824502e-01 -4.20811504e-01 8.42899323e-01 6.00560345e-02 4.58732933e-01 -5.80976009e-01 1.49586606e+00 7.49211788e-01 2.75860250e-01 -8.71486902e-01 -6.26225114e-01 6.87047318e-02 -1.15008819e+00 7.06036389e-02 1.19029987e+00 -5.10595381e-01 -1.69773221e-01 2.28471220e-01 -9.85743344e-01 -3.08109403e-01 -9.06135619e-01 2.31191739e-01 -8.83924544e-01 1.66679993e-01 -2.86887169e-01 -4.38975900e-01 1.93891466e-01 -1.30152380e+00 1.09795034e+00 -2.44828135e-01 -6.06264591e-01 -1.30159187e+00 1.98671177e-01 1.80633113e-01 3.31179500e-01 3.93154114e-01 1.32409573e+00 -3.19384605e-01 -8.90871406e-01 -8.38183239e-02 1.93707034e-01 3.88065487e-01 5.69861591e-01 9.40095559e-02 -9.39303279e-01 -2.82167852e-01 3.45111400e-01 1.22953609e-01 6.56200230e-01 3.51477444e-01 1.15834641e+00 -6.20885134e-01 -1.08641438e-01 1.04409611e+00 1.29355931e+00 1.25866547e-01 7.91376531e-01 2.30537876e-01 1.05261600e+00 5.23973048e-01 -2.99565285e-01 -1.39220878e-01 -1.25710322e-02 7.09670722e-01 3.33184481e-01 -3.12244892e-01 -1.80138573e-02 -4.69041198e-01 4.80292499e-01 8.59391451e-01 -2.78013021e-01 -6.72075376e-02 -7.97389805e-01 3.45603019e-01 -1.47656429e+00 -8.68630230e-01 2.07458869e-01 2.34374809e+00 5.85671961e-01 1.71507820e-01 1.45006711e-02 5.76963425e-02 4.92598474e-01 1.77640185e-01 -4.74997878e-01 -4.69389051e-01 -3.22644293e-01 3.98674786e-01 5.62503040e-01 6.47876143e-01 -7.30466723e-01 6.84599638e-01 7.43713140e+00 4.74849761e-01 -1.07162201e+00 -1.14908494e-01 6.76432550e-01 2.16550812e-01 -8.46304357e-01 3.05607677e-01 -2.31438443e-01 3.02226692e-01 7.33914971e-01 -2.25463778e-01 8.29642117e-01 7.04450667e-01 -1.03599116e-01 3.48394841e-01 -1.43522668e+00 8.68599415e-01 1.08993232e-01 -1.40392828e+00 3.99388969e-01 6.07551277e-01 1.02747345e+00 -1.72835782e-01 5.12072563e-01 -3.37964028e-01 4.41018164e-01 -1.31780481e+00 7.04191685e-01 5.11837006e-01 1.06213892e+00 -4.60506469e-01 2.28618592e-01 1.68171406e-01 -8.30999851e-01 2.68728167e-01 -3.36434841e-01 -9.92861539e-02 -7.46826679e-02 2.87666917e-01 -8.89793873e-01 2.29019627e-01 2.56833136e-01 7.89904296e-01 -7.86667883e-01 2.16962248e-01 -4.72798884e-01 5.48878193e-01 -3.11694115e-01 4.09122020e-01 5.73278256e-02 -9.18748975e-01 8.48416984e-01 6.42918468e-01 5.45571804e-01 -2.81716347e-01 -3.34430188e-01 1.43137765e+00 -1.51866555e-01 -2.33369559e-01 -1.07434678e+00 -3.03753644e-01 -2.56436318e-03 1.16886163e+00 -9.36684728e-01 -8.20111036e-02 -1.79585889e-01 1.28951263e+00 5.90655617e-02 6.08162820e-01 -5.96945822e-01 -2.13403329e-02 8.40556800e-01 2.51190126e-01 2.36592680e-01 -5.45050681e-01 -5.44994831e-01 -1.41428185e+00 1.07543923e-01 -1.00334668e+00 -4.36727814e-02 -8.33723247e-01 -1.12567115e+00 6.24942243e-01 3.45747396e-02 -1.29794359e+00 -7.33236372e-01 -6.87867820e-01 -8.36157858e-01 9.26748157e-01 -6.87219977e-01 -1.19084883e+00 -2.61850029e-01 6.17780030e-01 2.42153481e-01 -3.76211941e-01 1.07421470e+00 -3.30792457e-01 -2.36230448e-01 6.54727221e-01 4.98705298e-01 1.68832213e-01 2.68299401e-01 -1.58548355e+00 6.22372091e-01 1.03424692e+00 9.17837620e-01 9.63117599e-01 7.04020858e-01 -2.78881460e-01 -1.52725983e+00 -8.94050121e-01 4.27713811e-01 -9.93750274e-01 6.73488259e-01 -6.50821269e-01 -5.69476604e-01 1.12797606e+00 1.73717022e-01 -3.37020159e-01 7.61537552e-01 3.42555083e-02 -5.04638195e-01 2.71440893e-02 -9.10258055e-01 9.10696447e-01 1.11224711e+00 -8.76105607e-01 -3.64644200e-01 3.58320415e-01 5.58502376e-01 -1.00779265e-01 -5.46727836e-01 -1.01513285e-02 5.83317757e-01 -1.06870782e+00 9.41504538e-01 -7.93936372e-01 6.98864400e-01 -3.90223205e-01 -1.58578560e-01 -1.66045892e+00 -3.32108110e-01 -7.67116070e-01 1.39333874e-01 1.08063745e+00 4.60263371e-01 -7.69822896e-01 8.83132100e-01 6.96269393e-01 1.46947920e-01 -5.47301471e-01 -6.53215170e-01 -8.04397106e-01 1.68505073e-01 -2.89663494e-01 6.82723999e-01 1.00628078e+00 -3.13577533e-01 4.44416076e-01 -2.15728208e-01 1.76484429e-03 6.56713784e-01 1.90088451e-01 9.73716617e-01 -8.64210188e-01 -5.39073527e-01 -5.08533955e-01 -8.70529473e-01 -1.14322829e+00 4.07629870e-02 -1.11782694e+00 -3.25837791e-01 -1.09173703e+00 3.37898657e-02 -3.84508699e-01 5.34212478e-02 3.78355742e-01 2.60868162e-01 3.93196195e-01 2.36232281e-01 5.52671909e-01 -1.06512234e-02 5.74607968e-01 1.20488656e+00 -1.18067659e-01 -8.15011933e-02 -1.94985166e-01 -8.55308652e-01 9.05035675e-01 7.97155797e-01 -3.78541321e-01 -6.08187914e-01 -6.39771938e-01 3.92797768e-01 -4.19167429e-01 5.03118873e-01 -9.32172120e-01 -2.49816507e-01 -1.71220228e-01 5.03434837e-01 2.69041751e-02 3.06715071e-01 -9.06837702e-01 5.92363298e-01 2.84536362e-01 -4.05835360e-01 1.11576058e-01 -2.64690340e-01 4.13027197e-01 -2.20786139e-01 -1.95669800e-01 6.85365856e-01 -2.73851693e-01 -2.42405891e-01 2.53373504e-01 -2.86158413e-01 1.78209201e-01 8.59974384e-01 -4.62425590e-01 -1.26100957e-01 -8.05782557e-01 -6.55533731e-01 -3.95726681e-01 1.10238516e+00 3.58361244e-01 3.35282147e-01 -1.63384712e+00 -4.09545362e-01 6.53952062e-01 -6.60158042e-03 -2.17166655e-02 -1.37184992e-01 5.38082719e-01 -5.57382107e-01 2.08295986e-01 -5.14349461e-01 -8.33385706e-01 -8.54886651e-01 3.45038176e-01 4.70242471e-01 -2.28423640e-01 -5.01417220e-01 7.11871564e-01 7.98657179e-01 -3.60805064e-01 -4.60743695e-01 -2.63475567e-01 1.66240469e-01 -1.72069848e-01 1.78218707e-01 -2.12604692e-03 -1.30183041e-01 -9.52658474e-01 -1.97973307e-02 8.54288459e-01 2.03115150e-01 -2.92672247e-01 1.39674509e+00 -1.04289770e-01 -4.66264814e-01 5.57571769e-01 1.56680739e+00 3.48249257e-01 -1.25319839e+00 1.27741143e-01 -1.45230591e-01 -6.57507598e-01 -3.67230266e-01 -3.24718356e-01 -1.19416046e+00 9.52831686e-01 3.86058956e-01 5.01885831e-01 1.11228204e+00 1.66319653e-01 3.02136809e-01 1.36335149e-01 1.35743245e-01 -6.89559460e-01 2.35595107e-01 3.54040146e-01 1.09512770e+00 -8.98057044e-01 -1.42943487e-01 -4.09916997e-01 -4.91264254e-01 1.21271980e+00 2.08898664e-01 -2.38683924e-01 6.35372937e-01 8.68320651e-03 1.08228840e-01 -3.74046266e-01 -2.86714464e-01 1.67613477e-01 6.02438033e-01 7.46254623e-01 2.38856792e-01 2.03944728e-01 1.24946803e-01 6.97317813e-03 -9.32510018e-01 -7.02520847e-01 7.54446030e-01 5.75622201e-01 1.15407065e-01 -1.39155245e+00 -3.80644232e-01 2.57188350e-01 -2.05171555e-01 -6.27279431e-02 -5.95215559e-01 6.76399231e-01 6.35155067e-02 5.16421318e-01 2.03811437e-01 -4.36886728e-01 2.20613857e-03 3.01364601e-01 6.57258630e-01 -5.94834864e-01 1.49171501e-01 -9.63953361e-02 -3.54715556e-01 -5.80496252e-01 -3.57942164e-01 -6.61221206e-01 -9.56202149e-01 -9.62387919e-02 5.86356185e-02 2.11678986e-02 7.25382924e-01 9.06989574e-01 3.24269086e-01 3.07280570e-01 8.35412025e-01 -7.79866099e-01 -3.95488590e-01 -5.44083357e-01 -6.04926527e-01 9.37530994e-01 3.78459096e-01 -4.96585727e-01 -6.52699888e-01 6.39748275e-01]	[11.618754386901855, -0.1257167011499405]
c901c5c1-de37-4d5b-a649-d762d04451c7	comparing-approaches-to-dravidian-language	2103.05552	null	https://arxiv.org/abs/2103.05552v1	https://arxiv.org/pdf/2103.05552v1.pdf	Comparing Approaches to Dravidian Language Identification	This paper describes the submissions by team HWR to the Dravidian Language Identification (DLI) shared task organized at VarDial 2021 workshop. The DLI training set includes 16,674 YouTube comments written in Roman script containing code-mixed text with English and one of the three South Dravidian languages: Kannada, Malayalam, and Tamil. We submitted results generated using two models, a Naive Bayes classifier with adaptive language models, which has shown to obtain competitive performance in many language and dialect identification tasks, and a transformer-based model which is widely regarded as the state-of-the-art in a number of NLP tasks. Our first submission was sent in the closed submission track using only the training set provided by the shared task organisers, whereas the second submission is considered to be open as it used a pretrained model trained with external data. Our team attained shared second position in the shared task with the submission based on Naive Bayes. Our results reinforce the idea that deep learning methods are not as competitive in language identification related tasks as they are in many other text classification tasks.	['Marcos Zampieri', 'Tharindu Ranasinghe', 'Tommi Jauhiainen']	2021-03-09	null	https://aclanthology.org/2021.vardial-1.14	https://aclanthology.org/2021.vardial-1.14.pdf	eacl-vardial-2021-4	['dialect-identification']	['natural-language-processing']	[-3.39379102e-01 -1.06320642e-01 -4.45359154e-03 -2.38923103e-01 -7.89216399e-01 -6.89358234e-01 9.56335187e-01 2.16510162e-01 -9.33677495e-01 4.72584546e-01 3.60270411e-01 -6.87084854e-01 -1.71878673e-02 -2.34186351e-01 -1.41168058e-01 -3.25101495e-01 1.31949365e-01 1.03250909e+00 9.75338966e-02 -3.71414542e-01 4.07420993e-01 1.42658323e-01 -1.11601877e+00 5.80574214e-01 7.58372724e-01 6.10722721e-01 -1.67481765e-01 7.05176890e-01 -3.86890799e-01 1.09903872e+00 -3.88479829e-01 -8.41010094e-01 2.68411130e-01 -8.29128921e-02 -1.23093319e+00 -5.26339710e-01 4.68638986e-01 -1.27315775e-01 -2.82522857e-01 8.63963783e-01 6.81964457e-01 -1.20465927e-01 8.31883311e-01 -1.05100286e+00 -5.48969805e-01 1.07305992e+00 -3.25578272e-01 2.19443306e-01 5.58792830e-01 -2.43503958e-01 8.94634664e-01 -1.22231352e+00 6.71796024e-01 1.24210811e+00 1.09217143e+00 7.25279868e-01 -1.03745747e+00 -9.15923655e-01 -2.31824145e-01 9.66492891e-02 -1.67631483e+00 -6.00845516e-01 2.91641116e-01 -1.00148737e+00 1.30407786e+00 -1.68741904e-02 1.21175393e-01 1.09917295e+00 -2.48658612e-01 8.15519691e-01 1.10086322e+00 -7.42089808e-01 -7.85720721e-02 8.95568967e-01 2.02130154e-01 5.53742588e-01 -3.67808416e-02 -2.18195423e-01 -6.03300512e-01 -4.07833636e-01 -7.94276968e-02 -5.77357769e-01 -5.72423935e-02 -1.45554980e-02 -1.30381429e+00 1.13139772e+00 -1.05038859e-01 6.69968903e-01 4.79493253e-02 -4.36180562e-01 1.01601326e+00 5.02824426e-01 7.20500588e-01 3.19300562e-01 -5.46675682e-01 -4.05809730e-01 -1.12275398e+00 1.83297992e-01 1.13715076e+00 7.53142595e-01 3.86807084e-01 3.11836717e-03 7.63751268e-02 1.39916623e+00 4.50569272e-01 2.11146399e-01 9.75513697e-01 -4.59176481e-01 6.91105127e-01 5.80166399e-01 -4.89324844e-03 -6.80297613e-01 -4.78743970e-01 -8.62363949e-02 -7.65087426e-01 6.00124300e-02 8.12412858e-01 -4.75237310e-01 -4.50079709e-01 1.22251868e+00 -1.61728039e-01 -4.50457454e-01 8.56639072e-02 5.24763167e-01 1.06286252e+00 6.58251584e-01 1.35729671e-01 8.42723548e-02 1.21592474e+00 -8.28793347e-01 -4.72354442e-01 1.00407444e-01 1.03602481e+00 -1.15696836e+00 8.60744476e-01 4.76594716e-01 -7.59475648e-01 -6.90990388e-01 -9.20498490e-01 7.28107095e-02 -7.30726063e-01 3.80317003e-01 3.42055619e-01 1.11246026e+00 -1.44958150e+00 2.66009897e-01 -3.10357898e-01 -1.01028407e+00 1.30278677e-01 5.09570181e-01 -6.35283113e-01 2.50546813e-01 -1.30135059e+00 9.07180727e-01 4.05558765e-01 -4.15573388e-01 -4.80773598e-01 -5.70525765e-01 -5.10165989e-01 -4.24598694e-01 -1.15127653e-01 8.22114199e-02 1.16407001e+00 -8.31799090e-01 -1.48872721e+00 1.71658456e+00 -4.21638554e-03 -5.79068720e-01 9.30592656e-01 8.84274691e-02 -6.45075619e-01 -2.62169302e-01 3.21163565e-01 5.86167753e-01 4.89151537e-01 -7.60243237e-01 -7.59244025e-01 -4.21500981e-01 -1.34396285e-01 2.68643111e-01 -8.00022423e-01 7.22570539e-01 -3.07667404e-01 -5.66109061e-01 -3.40063840e-01 -9.23596025e-01 2.51929492e-01 -3.55769068e-01 -4.96592104e-01 -7.92784989e-01 6.80663109e-01 -9.32513118e-01 1.37896764e+00 -2.21355987e+00 -1.12014256e-01 1.32471040e-01 1.21129431e-01 5.22608459e-01 1.60655126e-01 7.58588791e-01 -2.13473827e-01 3.45937729e-01 1.03380643e-01 -6.86049402e-01 1.26975805e-01 -2.32264236e-01 -3.83692801e-01 4.57604825e-01 -3.30055267e-01 3.83537561e-01 -7.30449736e-01 -4.00265276e-01 1.14706799e-01 3.41866583e-01 -6.92085028e-02 7.36258477e-02 3.83139789e-01 1.65075451e-01 3.72368880e-02 2.33087420e-01 6.14814937e-01 2.46281326e-02 1.62936717e-01 6.82958663e-02 -4.39712256e-01 4.91770387e-01 -1.14403689e+00 1.46283388e+00 -4.24671829e-01 1.03463340e+00 3.51616070e-02 -9.05133486e-01 1.19141912e+00 5.35738587e-01 3.34638357e-01 -4.38880086e-01 -9.90009494e-03 6.55616164e-01 3.01506609e-01 -2.81441420e-01 5.64584136e-01 1.23701036e-01 -5.34550063e-02 7.99401820e-01 2.20909312e-01 7.67977014e-02 2.94287682e-01 4.28441614e-01 6.64520025e-01 1.74069107e-02 3.26410621e-01 -8.17665040e-01 1.02931738e+00 5.97946048e-02 2.54182816e-01 9.89186764e-01 -3.65387350e-01 6.15546346e-01 3.41482699e-01 -7.34195292e-01 -1.19629169e+00 -7.42084086e-01 -4.88468885e-01 1.46022749e+00 -5.31112671e-01 -7.53639579e-01 -8.72651637e-01 -6.86513186e-01 -2.59187251e-01 4.43768024e-01 -5.42983353e-01 2.34609649e-01 -4.05081540e-01 -8.09652746e-01 1.08864069e+00 1.44389540e-01 6.36390805e-01 -8.34236085e-01 -1.26963630e-01 2.36450493e-01 -2.73588568e-01 -1.03327870e+00 -6.65922761e-01 3.21402729e-01 -2.06843540e-01 -9.36600864e-01 -1.06204557e+00 -9.39060688e-01 2.39154071e-01 -1.88485697e-01 1.02161121e+00 -3.62284966e-02 -3.06782007e-01 3.49183857e-01 -5.37878752e-01 -6.35463357e-01 -9.09931779e-01 6.76246464e-01 4.03138727e-01 2.56981760e-01 1.05920362e+00 1.12809427e-01 -6.57622069e-02 3.08366269e-01 -3.96352053e-01 7.27638528e-02 -9.86422896e-02 7.93470383e-01 -3.00088882e-01 -1.57755151e-01 4.50845629e-01 -9.63026583e-01 7.91705310e-01 -3.83364677e-01 -3.46608937e-01 1.75655514e-01 -5.38613260e-01 -1.83030590e-01 6.16016388e-01 -3.75470549e-01 -9.86098647e-01 1.19209237e-01 -5.74162781e-01 2.69433379e-01 -1.94715977e-01 3.04018348e-01 1.82775646e-01 -2.30316833e-01 9.53884900e-01 2.91970462e-01 -1.21442145e-02 -5.99062443e-01 -1.38212100e-01 1.50204003e+00 2.07962662e-01 -4.13892299e-01 6.78773105e-01 2.29265019e-01 -6.99077547e-01 -9.40589488e-01 -4.91160303e-01 -9.47284400e-01 -1.05830300e+00 -1.23398826e-01 9.83578086e-01 -1.13670874e+00 -5.86799324e-01 1.08858395e+00 -1.23924744e+00 -4.26090151e-01 8.54480360e-03 5.41633189e-01 -5.58866449e-02 2.99243629e-01 -7.21804082e-01 -9.83249128e-01 -5.45245767e-01 -1.05205905e+00 7.57421970e-01 -8.78150463e-02 -7.38246977e-01 -1.34539115e+00 3.21435183e-01 3.49934131e-01 5.77196300e-01 -3.65424305e-01 9.52268660e-01 -1.48025310e+00 5.04634380e-01 -2.37104580e-01 -3.25363159e-01 4.39889252e-01 3.92882489e-02 9.34531018e-02 -1.15227294e+00 -4.95676994e-01 -2.75612622e-01 -5.24377406e-01 7.62924135e-01 -1.38428882e-01 6.97662473e-01 -4.52322885e-02 -2.55986124e-01 3.29118550e-01 1.24576485e+00 3.46196115e-01 2.72085309e-01 4.85025436e-01 8.12619805e-01 8.95867467e-01 1.30981877e-02 5.07922709e-01 7.51837611e-01 1.09898806e+00 -2.44906679e-01 -1.00608423e-01 -1.51006401e-01 -2.69894153e-01 5.01794219e-01 1.10918522e+00 1.22680828e-01 1.81662478e-02 -1.70871007e+00 7.69340813e-01 -1.74245727e+00 -8.25432420e-01 -5.29362917e-01 2.35048246e+00 8.83061826e-01 7.03735650e-02 7.60947287e-01 2.46282414e-01 7.23869383e-01 -2.01568127e-01 -1.88491680e-02 -8.65063310e-01 -1.78050667e-01 5.61951138e-02 4.90642488e-01 7.15778828e-01 -1.31067157e+00 9.70276415e-01 6.42010832e+00 1.15759122e+00 -1.20353544e+00 3.51596355e-01 5.96347630e-01 3.38073134e-01 5.29772565e-02 -1.83605447e-01 -1.30491436e+00 7.18819022e-01 1.31198239e+00 -4.19799358e-01 3.25973511e-01 5.67001224e-01 -9.51649845e-02 8.61824751e-02 -1.08322549e+00 1.16303718e+00 4.06264454e-01 -1.15345573e+00 -3.59816402e-02 1.35703281e-01 5.61449051e-01 6.66567862e-01 -6.92842677e-02 4.93190914e-01 5.37794471e-01 -1.13997757e+00 7.03958452e-01 1.54040217e-01 9.19251621e-01 -4.67199534e-01 9.01237369e-01 4.87152725e-01 -9.88560319e-01 -1.78101033e-01 -2.88828313e-01 -1.60089687e-01 -3.18387508e-01 2.15131536e-01 -1.10882390e+00 4.10609156e-01 9.36195850e-01 6.95728958e-01 -8.50607872e-01 9.57247674e-01 2.83485502e-01 8.60444367e-01 -4.58753228e-01 -3.25702846e-01 3.30132544e-01 4.19930257e-02 5.04368484e-01 1.66452396e+00 -1.10719092e-02 -5.51523447e-01 1.57616228e-01 3.57084304e-01 1.34339891e-02 7.18121648e-01 -8.98137450e-01 4.74765338e-02 2.78943360e-01 1.20336962e+00 -5.72103024e-01 -3.50734025e-01 -5.29768050e-01 9.19238150e-01 1.93147689e-01 8.17131773e-02 -1.55969277e-01 -5.63101292e-01 3.16101938e-01 2.31930450e-01 -1.49587035e-01 -4.11327966e-02 -3.58455420e-01 -1.24681258e+00 -2.83332527e-01 -1.03067172e+00 7.50460446e-01 -4.46931034e-01 -1.42245495e+00 1.10073686e+00 -2.88983993e-02 -1.21165586e+00 -6.76701963e-01 -1.11708224e+00 -4.38913643e-01 1.21088743e+00 -9.74344432e-01 -1.26029623e+00 7.62571320e-02 6.92616880e-01 6.20342314e-01 -1.17084146e+00 1.12603152e+00 5.73444128e-01 -4.71632391e-01 9.36602175e-01 5.76156676e-01 6.91335201e-01 1.02100873e+00 -1.37547874e+00 5.06738782e-01 4.55585003e-01 3.26452792e-01 5.96893907e-01 3.86629790e-01 -3.35603565e-01 -8.57386827e-01 -7.82070458e-01 1.68833888e+00 -6.71307147e-01 9.08072531e-01 -7.59704173e-01 -7.56382465e-01 5.93173027e-01 4.57432687e-01 -4.66619998e-01 9.91696417e-01 1.75862208e-01 -5.15136659e-01 1.23557067e-02 -1.04521334e+00 3.02089006e-01 5.64797878e-01 -9.02564168e-01 -4.11925614e-01 6.96293533e-01 1.08504735e-01 -2.41333708e-01 -7.36539960e-01 -5.49635701e-02 6.12213373e-01 -7.33038962e-01 6.73893690e-01 -4.70955729e-01 1.74515903e-01 -2.79699937e-02 -1.32311970e-01 -1.21391535e+00 1.63885602e-03 -5.49254358e-01 6.77853942e-01 1.65918732e+00 6.34824812e-01 -7.39443302e-01 5.41959584e-01 5.16467214e-01 3.29802841e-01 -2.73741096e-01 -1.10649502e+00 -7.48571157e-01 7.67966509e-01 -5.28701067e-01 9.70383212e-02 1.23541069e+00 2.56246030e-01 5.84055185e-01 -3.49185854e-01 -7.25480199e-01 4.43279088e-01 -6.77579105e-01 8.42085123e-01 -1.46669579e+00 -6.24902286e-02 -6.95472896e-01 -3.41616899e-01 -6.35511756e-01 4.19020593e-01 -1.48869503e+00 -2.92236209e-01 -1.29513931e+00 2.19790787e-01 -4.49506462e-01 4.51332256e-02 6.29616559e-01 1.75825864e-01 4.88283038e-01 2.48258248e-01 6.05118275e-01 -4.43592191e-01 -7.54428729e-02 2.45641038e-01 -3.95106673e-01 1.15169352e-02 1.56343400e-01 -7.82019317e-01 7.63827145e-01 6.41409934e-01 -3.95060241e-01 -1.36523157e-01 -4.92587566e-01 3.42683285e-01 -5.12278616e-01 -7.95034394e-02 -9.43792105e-01 4.97093886e-01 4.81651753e-01 1.91611663e-01 -3.68597984e-01 4.33363989e-02 -5.31367123e-01 -1.46777198e-01 5.77557206e-01 -5.99084377e-01 2.29047686e-01 4.13485795e-01 -2.62639791e-01 -1.63877293e-01 -5.08201778e-01 8.03366184e-01 -1.64677978e-01 -7.89666831e-01 1.40717879e-01 -8.77082229e-01 2.69076139e-01 7.39356935e-01 -4.07735020e-01 -1.16898865e-01 -4.60937738e-01 -5.37929535e-01 1.01576440e-01 2.43193954e-01 7.14623511e-01 1.77617297e-01 -1.09043789e+00 -1.46706975e+00 2.13370949e-01 3.72113019e-01 -8.09327960e-01 -1.18659236e-01 6.79082870e-01 -6.58066034e-01 6.76002085e-01 -1.40041292e-01 -5.30780315e-01 -1.30999434e+00 6.84171766e-02 4.15866524e-01 -4.85364437e-01 -3.96904051e-01 8.81220579e-01 1.12318055e-04 -1.25963247e+00 3.79192650e-01 5.51050127e-01 -6.10747576e-01 3.12035114e-01 8.14594507e-01 3.85775536e-01 3.04539770e-01 -9.83085811e-01 -6.89834177e-01 4.70360368e-01 -4.69387472e-01 -3.87658536e-01 8.89665067e-01 -5.88646866e-02 -3.75549525e-01 8.23333204e-01 1.43480778e+00 6.52919188e-02 -3.30498368e-01 -4.23111141e-01 3.86601865e-01 -7.96909481e-02 -1.90393124e-02 -1.03731608e+00 -4.95655656e-01 1.11759305e+00 9.59502578e-01 3.72098356e-01 5.40407836e-01 -3.13621491e-01 4.02538925e-01 3.77906889e-01 3.50538135e-01 -1.43697107e+00 -3.56283009e-01 9.52266932e-01 7.89771438e-01 -1.51107001e+00 -2.99890518e-01 -4.50040475e-02 -7.31218815e-01 1.33448470e+00 5.87899685e-01 2.86140263e-01 9.13141310e-01 4.15905356e-01 3.60192567e-01 2.08814442e-01 -6.24854326e-01 7.92362839e-02 3.29473436e-01 8.54054391e-01 1.00875330e+00 -1.45469392e-02 -5.33173561e-01 4.52934533e-01 -3.32323432e-01 -1.66780666e-01 4.86125976e-01 2.13448331e-01 1.20786324e-01 -1.31233454e+00 -2.37900302e-01 5.07550240e-01 -8.04434955e-01 -5.05803287e-01 -6.49204969e-01 8.34124327e-01 1.40277535e-01 9.82303560e-01 2.45424330e-01 -6.37454987e-01 -1.62733272e-02 3.17813486e-01 -2.55659018e-02 -7.22250164e-01 -1.30565691e+00 -3.90012622e-01 3.83104652e-01 2.21257403e-01 -9.11007151e-02 -9.48794961e-01 -8.11591446e-01 -6.41459644e-01 3.65769155e-02 5.41318595e-01 8.77789438e-01 9.54174638e-01 -9.22073796e-03 -2.03026041e-01 5.23538888e-01 -5.39933145e-01 -4.56670195e-01 -1.17926919e+00 -5.54419219e-01 4.38149422e-01 6.46619275e-02 -1.34480566e-01 -3.80948663e-01 3.90729941e-02]	[10.22842025756836, 10.643775939941406]
bbd6f4c5-7433-4633-b6e1-7a32d76a0b70	on-a-notion-of-independence-proposed-by-teddy	2102.10342	null	https://arxiv.org/abs/2102.10342v1	https://arxiv.org/pdf/2102.10342v1.pdf	On a notion of independence proposed by Teddy Seidenfeld	Teddy Seidenfeld has been arguing for quite a long time that binary preference models are not powerful enough to deal with a number of crucial aspects of imprecision and indeterminacy in uncertain inference and decision making. It is at his insistence that we initiated our study of so-called sets of desirable option sets, which we have argued elsewhere provides an elegant and powerful approach to dealing with general, binary as well as non-binary, decision-making under uncertainty. We use this approach here to explore an interesting notion of irrelevance (and independence), first suggested by Seidenfeld in an example intended as a criticism of a number of specific decision methodologies based on (convex) binary preferences. We show that the consequences of making such an irrelevance or independence assessment are very strong, and might be used to argue for the use of so-called mixing choice functions, and E-admissibility as the resulting decision scheme.	['Gert de Cooman', 'Jasper De Bock']	2021-02-20	null	null	null	null	['decision-making-under-uncertainty', 'decision-making-under-uncertainty']	['medical', 'reasoning']	[ 4.84242067e-02 5.28302670e-01 -1.27093539e-01 -8.54859829e-01 -3.81607771e-01 -9.20388520e-01 8.51888061e-01 2.05268607e-01 -6.36255085e-01 9.43894148e-01 3.63708973e-01 -1.10119319e+00 -1.08613133e+00 -6.88555658e-01 -2.43388951e-01 -5.30311704e-01 -3.75114754e-02 6.43967807e-01 -1.26317829e-01 -2.30163991e-01 6.48854017e-01 6.98017836e-01 -1.44669580e+00 -2.35523600e-02 1.13805258e+00 1.08687782e+00 -4.88501012e-01 1.14673078e-01 -1.54093578e-01 5.69799721e-01 -3.57095897e-01 -1.01695991e+00 2.41295546e-01 1.92452723e-03 -8.12464714e-01 -1.22066520e-01 -4.41210240e-01 -2.15899289e-01 2.57388204e-01 1.20206904e+00 3.29033107e-01 3.22429746e-01 1.09070110e+00 -1.16940415e+00 -4.55332637e-01 1.06139302e+00 -2.01153040e-01 1.38362840e-01 1.16668962e-01 -1.30266890e-01 9.15715575e-01 -5.63834727e-01 1.24277800e-01 1.43939352e+00 5.03721952e-01 3.97512615e-01 -1.11719692e+00 -2.97903121e-01 2.51747608e-01 -9.88556743e-02 -1.38868976e+00 -5.76576114e-01 4.86143023e-01 -4.03656006e-01 2.32304975e-01 9.09679472e-01 2.81786263e-01 6.66537762e-01 3.95019382e-01 4.80249405e-01 1.49436283e+00 -6.82543635e-01 6.38022482e-01 2.26928011e-01 1.50326580e-01 -2.58800620e-03 9.02613640e-01 3.73560548e-01 1.96948633e-01 -6.32831573e-01 6.09266698e-01 -2.40989462e-01 -2.98514873e-01 -2.79125601e-01 -1.00440025e+00 1.08168793e+00 2.06431046e-01 4.56754357e-01 -2.60988116e-01 -7.14512616e-02 2.35166773e-01 4.80077028e-01 4.02998745e-01 5.38588464e-01 -3.33488166e-01 1.31039351e-01 -7.28962541e-01 5.45558572e-01 9.21725452e-01 5.42721033e-01 -2.11869150e-01 -9.70803872e-02 -4.37741121e-03 4.79717523e-01 7.95461118e-01 1.29921898e-01 2.87408829e-01 -1.26608968e+00 4.05343145e-01 -2.46202555e-02 8.18904877e-01 -8.57668281e-01 -4.02462065e-01 -5.33225685e-02 -5.84874868e-01 8.69967163e-01 7.33460903e-01 -4.86103624e-01 -6.97028220e-01 1.74054241e+00 2.39685811e-02 -6.18906081e-01 1.86246917e-01 8.68667543e-01 1.60139129e-01 3.31232965e-01 2.41374150e-01 -5.57274699e-01 1.01748765e+00 6.39930964e-02 -7.71281064e-01 1.56527996e-01 3.29329044e-01 -6.02851987e-01 6.21170580e-01 7.44245112e-01 -1.43535519e+00 2.37109721e-01 -1.12517154e+00 2.19950676e-01 -2.86002487e-01 -7.90615380e-01 1.17388272e+00 1.11100006e+00 -6.84325039e-01 7.79039145e-01 -4.12468791e-01 -1.36158429e-02 7.40741044e-02 3.46216887e-01 -3.41472290e-02 1.16823308e-01 -1.29478669e+00 1.42888832e+00 3.36242080e-01 5.75732350e-01 -1.30447164e-01 3.76232304e-02 -7.12485373e-01 1.22338720e-01 6.32598937e-01 -5.44052660e-01 1.14066625e+00 -8.78986299e-01 -1.30874085e+00 6.54780328e-01 2.49962270e-01 -2.87942588e-01 1.10891664e+00 2.22214431e-01 -8.60942900e-01 -4.38630104e-01 -6.04742616e-02 7.85754770e-02 4.47532862e-01 -1.22871459e+00 -5.44103205e-01 -6.44638360e-01 4.59055036e-01 3.54147553e-01 6.29520893e-01 3.55491310e-01 6.07150197e-01 -6.74303770e-01 6.54371321e-01 -7.09887743e-01 -4.85589921e-01 -1.65346533e-01 -2.21509084e-01 -3.79008323e-01 -1.68604493e-01 -7.35718459e-02 1.22927856e+00 -1.85252106e+00 -2.14929014e-01 7.26443529e-01 -1.34691477e-01 -1.17605232e-01 3.77579331e-01 1.66273132e-01 -2.66090959e-01 7.44152606e-01 -5.60859382e-01 2.39548251e-01 7.34872878e-01 2.68603414e-01 -4.66524601e-01 6.44105017e-01 9.07438621e-02 6.82818174e-01 -8.87246013e-01 -3.72627765e-01 2.99658775e-01 1.09121412e-01 -6.33389652e-02 -5.09673774e-01 9.62768048e-02 1.06332548e-01 -6.19786859e-01 7.94777095e-01 7.37785757e-01 2.01176643e-01 4.74378258e-01 1.85084060e-01 -4.78372931e-01 4.77250993e-01 -1.60085905e+00 1.05475676e+00 2.49251369e-02 1.51436523e-01 1.14231348e-01 -8.74806643e-01 6.09699845e-01 6.01531148e-01 1.02719754e-01 -4.32232440e-01 4.88831609e-01 7.31845856e-01 3.82543981e-01 -3.06568563e-01 3.50994289e-01 -9.27266955e-01 -5.01924217e-01 5.36165595e-01 -2.93329716e-01 -5.51748037e-01 -5.58585562e-02 -3.60739946e-01 3.81156892e-01 1.43712033e-02 3.38734359e-01 -9.50633109e-01 3.68957520e-01 -1.88320860e-01 6.44488811e-01 7.37177730e-01 -2.37589687e-01 6.88535511e-01 6.15158558e-01 -4.24329340e-01 -8.18920612e-01 -1.21255291e+00 -8.28427136e-01 4.66292322e-01 9.75252092e-02 4.03485596e-01 -1.11905493e-01 -4.33932126e-01 2.49244496e-01 1.40530670e+00 -7.08413780e-01 1.16897263e-01 8.07500780e-02 -1.10120714e+00 2.44924217e-01 3.02319080e-01 -9.02990904e-03 -7.02451050e-01 -8.17804456e-01 2.74317890e-01 2.74241328e-01 -1.55479059e-01 1.26547366e-01 5.45153141e-01 -8.40924799e-01 -8.03860962e-01 -8.24625075e-01 1.66940898e-01 3.33850652e-01 -2.45069906e-01 1.05943453e+00 -2.49402732e-01 4.75131214e-01 2.60232657e-01 -2.38988146e-01 -8.42109561e-01 -3.67954522e-01 -7.23988414e-01 3.06630850e-01 -4.81336899e-02 4.58483100e-01 -6.74328387e-01 -3.40852082e-01 3.82327467e-01 -1.19563925e+00 -7.00468123e-01 2.91746914e-01 6.22738183e-01 7.09980875e-02 2.72294879e-01 8.03177536e-01 -1.05163562e+00 1.10506070e+00 -6.21041119e-01 -7.73318410e-01 5.41210890e-01 -9.81257558e-01 2.38499105e-01 -2.08347976e-01 -6.27611279e-02 -1.41807818e+00 -6.86958849e-01 -2.11519445e-03 2.30216041e-01 -6.60132542e-02 9.42303002e-01 -4.53741193e-01 -1.66414037e-01 6.76673293e-01 -4.63464230e-01 -1.31793141e-01 -3.38453352e-01 4.86906797e-01 8.90610278e-01 5.14804959e-01 -1.02368855e+00 2.70895541e-01 3.91938061e-01 2.86216229e-01 -1.55635819e-01 -5.08451760e-01 -1.78330729e-03 -4.00473386e-01 1.73211858e-01 4.51818973e-01 -4.95244265e-01 -8.81518722e-01 3.55412588e-02 -8.36616099e-01 1.51979821e-02 -6.29963398e-01 6.66092396e-01 -9.70203638e-01 3.58721107e-01 -6.30088001e-02 -1.58493888e+00 2.93139338e-01 -9.54677880e-01 1.19694822e-01 -9.24967453e-02 -6.20065391e-01 -1.29372811e+00 -2.88634986e-01 1.37587562e-01 4.27249730e-01 5.78594744e-01 1.02862704e+00 -8.65790904e-01 -9.05658677e-03 -3.34314048e-01 -4.57624905e-02 4.33171950e-02 3.66541632e-02 2.29730576e-01 -8.93720388e-01 1.15817696e-01 6.98926687e-01 -2.16920823e-01 6.40743256e-01 5.40474117e-01 6.62586093e-01 -5.83536625e-01 1.31554082e-02 5.49216084e-02 1.61527240e+00 5.42952299e-01 7.97201514e-01 3.73588681e-01 -1.10679448e-01 1.01328564e+00 6.86290562e-01 5.96067488e-01 3.92112464e-01 4.48629439e-01 4.53895450e-01 3.96622956e-01 8.42930198e-01 1.93897620e-01 -1.94858044e-01 -4.46493030e-02 -4.52907026e-01 -4.54356521e-01 -7.81847954e-01 6.48265600e-01 -1.91637385e+00 -1.13023603e+00 -1.40060857e-01 2.72178650e+00 8.16475749e-01 4.50575113e-01 1.69096664e-01 2.61158347e-01 7.80589223e-01 2.70579848e-02 -1.37945652e-01 -1.05291200e+00 -2.87949532e-01 -1.81783020e-01 7.41338909e-01 8.52617621e-01 -8.14303279e-01 7.32442737e-02 7.24914169e+00 6.83142304e-01 -6.23039663e-01 -1.76315367e-01 1.00148177e+00 4.38181534e-02 -1.16519952e+00 2.69678384e-01 -1.88448116e-01 8.07726145e-01 8.82719815e-01 -5.81144631e-01 8.79584327e-02 4.47730273e-01 1.80935711e-01 -4.91886795e-01 -1.19095826e+00 5.15723765e-01 -5.05226314e-01 -9.21553373e-01 -1.89994127e-01 5.33595346e-02 6.02265298e-01 -5.02103448e-01 1.89451113e-01 -1.15793854e-01 1.03664458e+00 -1.41901994e+00 1.07331550e+00 4.32805091e-01 4.45704192e-01 -1.06824756e+00 1.01600969e+00 3.30497235e-01 -2.30802268e-01 -3.05038244e-01 -3.82293671e-01 -3.87739837e-01 4.75042820e-01 8.34092200e-01 -1.14710361e-01 7.75955379e-01 1.93412706e-01 -2.28487551e-01 6.64211810e-02 1.19949102e+00 -8.27001855e-02 1.06696732e-01 -7.88955212e-01 2.18377754e-01 6.10165656e-01 -3.34818304e-01 4.70625758e-01 7.67429769e-01 4.89308029e-01 5.06707966e-01 -7.42447793e-01 1.00000942e+00 5.12536466e-01 -2.71285415e-01 -5.93687356e-01 5.48813120e-02 6.08402252e-01 7.98082173e-01 -8.13430548e-01 -1.23225115e-01 -3.68102193e-01 3.12115818e-01 -3.85718167e-01 2.40856275e-01 -6.10994875e-01 -6.78668842e-02 3.39754999e-01 -1.04755685e-02 -2.85743885e-02 6.26115128e-02 -9.84452784e-01 -1.15991807e+00 1.36738122e-01 -5.85399926e-01 6.72908545e-01 -4.16728407e-01 -1.29130602e+00 2.64181614e-01 5.80216467e-01 -1.00970316e+00 -5.10409713e-01 -5.79801619e-01 -7.68550158e-01 1.28796697e+00 -1.23260391e+00 -7.04321563e-01 6.37890756e-01 2.41516039e-01 -2.06352305e-02 3.60867560e-01 6.41881049e-01 -2.41442174e-01 1.59851536e-02 2.71722049e-01 3.44440252e-01 -5.30935705e-01 3.89044404e-01 -1.47499621e+00 1.27184376e-01 7.69661009e-01 -1.21390685e-01 8.02354395e-01 1.20777571e+00 -4.24443156e-01 -6.84933662e-01 -3.59330177e-01 1.13860679e+00 -7.37067282e-01 6.20039165e-01 1.69084042e-01 -6.23092115e-01 6.86241686e-01 -1.27358928e-01 -3.68373364e-01 6.78091943e-01 3.28389019e-01 -5.37723908e-03 2.55309939e-01 -1.82537937e+00 6.36348009e-01 7.19178438e-01 -6.74231350e-02 -1.37384546e+00 8.94699395e-02 2.84945071e-01 -2.26905923e-02 -9.99617994e-01 7.04262316e-01 9.07379568e-01 -1.21441090e+00 9.26666319e-01 -6.31517231e-01 2.08156127e-02 -1.57713398e-01 -5.46084762e-01 -1.11725879e+00 -4.96294498e-01 -7.70994842e-01 5.46462297e-01 1.22862566e+00 6.63925409e-01 -1.10412586e+00 1.88667431e-01 1.67896211e+00 -1.61393993e-02 -6.37459219e-01 -1.33970940e+00 -7.17447817e-01 6.23647630e-01 -5.81843734e-01 8.31898391e-01 1.18122661e+00 5.45973897e-01 -1.71692535e-01 -1.92132339e-01 -2.14601561e-01 8.14343333e-01 2.55262796e-02 -1.63919702e-01 -1.72658038e+00 -1.16239220e-01 -7.61227667e-01 -3.26628804e-01 -3.43135506e-01 -1.90215200e-01 -2.97032416e-01 -1.39629766e-01 -1.22990608e+00 -1.78550303e-01 -9.95343268e-01 -7.60304093e-01 9.64578986e-02 1.59058273e-01 -1.70346826e-01 2.19542414e-01 1.28902480e-01 -1.93453610e-01 1.80966720e-01 1.02509499e+00 -7.16281077e-03 -9.50644817e-03 6.00893855e-01 -1.44686234e+00 1.04808414e+00 5.64609230e-01 -1.78742751e-01 -6.30512238e-01 -2.39830822e-01 7.90228426e-01 4.57744926e-01 4.77286428e-01 -4.92747605e-01 5.03895693e-02 -7.37168014e-01 5.03105581e-01 -3.00555497e-01 1.70072779e-01 -1.04960525e+00 6.80839658e-01 2.41201147e-01 -5.72796583e-01 -1.93609864e-01 5.57601489e-02 3.80174637e-01 5.60946204e-02 -9.36941087e-01 5.16530454e-01 -4.44823742e-01 -5.65539479e-01 -9.83207896e-02 -3.05935502e-01 -2.60004371e-01 9.51272607e-01 -4.64371920e-01 -1.67224512e-01 -4.49018955e-01 -1.20403349e+00 3.31597805e-01 7.38955379e-01 8.01232979e-02 2.64646709e-01 -1.27225721e+00 -6.80465460e-01 -2.86762536e-01 -1.16160870e-01 -9.99088511e-02 2.42675737e-01 7.89123714e-01 -2.73304671e-01 7.00470865e-01 -3.53949875e-01 8.56951699e-02 -5.64545095e-01 7.80831873e-01 3.10912877e-01 3.62048596e-02 -2.17803210e-01 8.65558147e-01 9.94553566e-02 -1.27934322e-01 -5.92858233e-02 -3.84634048e-01 -2.22659662e-01 1.45853713e-01 2.97781289e-01 6.31051600e-01 -1.16101459e-01 -5.80344021e-01 -5.22769213e-01 1.41143054e-01 2.90009320e-01 -7.47000992e-01 1.17502141e+00 -5.65253854e-01 -2.48651400e-01 7.86592305e-01 2.75228769e-01 1.29008219e-01 -1.09694481e+00 2.20565602e-01 2.61034966e-01 -6.56581342e-01 1.49306701e-02 -1.18775570e+00 -1.94783598e-01 7.86446929e-01 3.81851703e-01 7.12862492e-01 8.86820853e-01 -1.88347936e-01 -1.51620835e-01 2.18972653e-01 8.35996151e-01 -9.89606738e-01 -1.23505521e+00 -8.79243612e-02 1.28820598e+00 -1.19644368e+00 2.70560622e-01 -3.46864939e-01 -6.61960602e-01 1.02321351e+00 -2.38661647e-01 1.34719685e-01 6.48516178e-01 1.19889982e-01 -1.00274451e-01 3.23843621e-02 -5.98797917e-01 -1.28209755e-01 2.07875803e-01 6.19203568e-01 3.63826483e-01 6.27636909e-01 -1.06519270e+00 9.52025712e-01 -2.57247258e-02 3.44445884e-01 7.14882433e-01 1.11480498e+00 -5.40886045e-01 -1.15627396e+00 -6.89312041e-01 4.51005906e-01 -9.06039000e-01 4.16910425e-02 -2.70477444e-01 8.15233648e-01 1.39147744e-01 1.12250590e+00 2.36006286e-02 1.15161333e-02 1.06417634e-01 1.36077896e-01 5.63933790e-01 -2.74299532e-01 -2.51170725e-01 2.73887943e-02 4.95275021e-01 -1.48868367e-01 -3.83740395e-01 -7.32653022e-01 -7.32281268e-01 -5.15115142e-01 -4.69067395e-01 5.69217265e-01 5.33880889e-01 1.05169666e+00 -1.12860836e-01 -9.32551473e-02 3.05283457e-01 -6.99283123e-01 -1.34707320e+00 -8.62931311e-01 -1.23902905e+00 8.21902901e-02 3.04430902e-01 -8.88774395e-01 -7.70681083e-01 -5.62530637e-01]	[8.19632625579834, 5.233717441558838]
21bd29b2-cb4a-42bc-9254-eabadf67c7d3	nsurl-2019-shared-task-8-semantic-question	1909.09691	null	https://arxiv.org/abs/1909.09691v1	https://arxiv.org/pdf/1909.09691v1.pdf	NSURL-2019 Shared Task 8: Semantic Question Similarity in Arabic	Question semantic similarity (Q2Q) is a challenging task that is very useful in many NLP applications, such as detecting duplicate questions and question answering systems. In this paper, we present the results and findings of the shared task (Semantic Question Similarity in Arabic). The task was organized as part of the first workshop on NLP Solutions for Under Resourced Languages (NSURL 2019) The goal of the task is to predict whether two questions are semantically similar or not, even if they are phrased differently. A total of 9 teams participated in the task. The datasets created for this task are made publicly available to support further research on Arabic Q2Q.	['Hussein T. Al-Natsheh', 'Hesham Al-Bataineh', 'Wael Farhan', 'Ahmad Mustafa', 'Haitham Seelawi']	2019-09-12	null	null	null	null	['question-similarity']	['natural-language-processing']	[ 2.20325403e-02 1.83370844e-01 4.68736231e-01 -6.02675200e-01 -8.71433139e-01 -9.92926002e-01 3.98025125e-01 7.81595170e-01 -4.64358419e-01 5.31685352e-01 4.48054314e-01 -2.79234499e-01 -1.99493676e-01 -4.64796454e-01 -4.21378374e-01 1.36480018e-01 3.37901175e-01 7.28516281e-01 6.85634136e-01 -1.03474176e+00 9.08967078e-01 9.33988243e-02 -1.64052022e+00 9.56159711e-01 1.31870222e+00 6.62818730e-01 2.19739795e-01 5.85343301e-01 -6.41226947e-01 8.79740357e-01 -7.70542443e-01 -9.00382757e-01 -8.06254372e-02 -6.98781252e-01 -1.75055957e+00 -4.54125762e-01 8.11352134e-01 2.82657057e-01 2.35016659e-01 1.14301467e+00 5.12910187e-01 4.20199335e-01 4.93296683e-01 -1.28289974e+00 -9.67392206e-01 5.10424256e-01 2.90678203e-01 5.52783310e-01 9.85264301e-01 -5.50055265e-01 1.44312727e+00 -1.09589636e+00 5.97556889e-01 1.37813699e+00 5.63500106e-01 3.11135530e-01 -5.88793337e-01 -3.39530706e-01 -4.34764534e-01 7.03892231e-01 -1.34131646e+00 -4.77514386e-01 1.71229124e-01 -3.71383205e-02 1.28652477e+00 5.27642608e-01 -1.61594838e-01 4.19520795e-01 2.00550277e-02 5.66089928e-01 1.07267344e+00 -8.12007844e-01 2.19819233e-01 3.47818434e-01 5.30912757e-01 5.07774770e-01 -9.78092626e-02 -9.07016158e-01 -6.36563182e-01 -4.10972476e-01 -8.14972967e-02 -7.10210145e-01 -2.56863266e-01 3.02235901e-01 -1.03083134e+00 1.11627471e+00 3.83548498e-01 8.53990018e-01 -1.64255843e-01 -4.33544546e-01 1.66882858e-01 9.77906406e-01 3.01207453e-01 1.29250133e+00 -6.68588400e-01 -1.64479449e-01 -3.26834679e-01 7.18375802e-01 1.34188402e+00 1.02071381e+00 7.16071069e-01 -7.79400885e-01 -1.71755731e-01 1.15780175e+00 3.91918749e-01 4.53009844e-01 9.06404734e-01 -1.35123718e+00 6.16346955e-01 8.73057187e-01 4.42757845e-01 -1.17517364e+00 -5.69934070e-01 3.83696735e-01 1.60876438e-01 -6.56281292e-01 7.05317080e-01 -6.07879944e-02 -3.99277747e-01 1.35524857e+00 3.63951683e-01 -3.40670019e-01 5.71595907e-01 7.39082575e-01 1.67552364e+00 7.35347331e-01 -2.44886540e-02 2.83054799e-01 1.98726475e+00 -9.70296979e-01 -8.84673476e-01 -2.88589865e-01 1.03851676e+00 -1.55653942e+00 1.27264678e+00 -1.35935903e-01 -1.13837659e+00 -3.46167803e-01 -4.42798376e-01 -4.51502621e-01 -8.35914493e-01 -7.22135678e-02 -1.26317032e-02 6.35801256e-01 -1.14690828e+00 2.65687138e-01 9.37480703e-02 -1.12735343e+00 -1.84073284e-01 -2.08260179e-01 -3.05207938e-01 -4.61764127e-01 -1.66653311e+00 1.45848703e+00 4.68815416e-01 -2.87067235e-01 -6.41415268e-02 -5.20699263e-01 -7.59701014e-01 -5.86605780e-02 2.81096399e-01 -2.55569071e-01 1.59584439e+00 -1.08115923e+00 -1.14440131e+00 1.40087223e+00 -4.55380052e-01 -2.74041057e-01 -1.77093044e-01 -2.50011474e-01 -7.76448905e-01 2.83991128e-01 7.08485603e-01 6.44053519e-01 4.71050978e-01 -7.71286547e-01 -7.21075594e-01 -5.76708913e-01 3.07253212e-01 5.75964868e-01 -1.13701954e-01 1.08579218e+00 -9.03962702e-02 -6.53050363e-01 2.98664838e-01 -9.30180967e-01 1.77264288e-01 -3.31698358e-01 1.76774725e-01 -9.04409885e-01 4.24306870e-01 -1.31569946e+00 8.80318165e-01 -1.85311651e+00 -1.07063420e-01 -1.60599425e-01 -3.12737226e-01 3.09083611e-01 -5.44754803e-01 9.03597414e-01 8.72436240e-02 1.31803557e-01 -4.66462016e-01 2.29368195e-01 1.71197373e-02 1.56746402e-01 -4.53823715e-01 -2.01781720e-01 2.62293100e-01 8.44325781e-01 -1.06017399e+00 -3.97643358e-01 -6.26542568e-01 -3.08892071e-01 5.76246865e-02 3.42484295e-01 -5.29343903e-01 1.94882005e-01 -2.53522366e-01 5.44251263e-01 4.83289480e-01 -1.22668520e-01 -1.06307538e-02 -2.07003251e-01 1.15000039e-01 8.60048890e-01 -1.05872750e+00 1.70531642e+00 -2.95892119e-01 5.03848374e-01 -1.30933046e-01 -8.76691043e-01 1.16825843e+00 5.73583245e-01 7.76571129e-03 -1.19330680e+00 -7.35486001e-02 6.25548005e-01 -2.20543686e-02 -9.28676248e-01 9.46358860e-01 -1.50786489e-01 -2.27009356e-01 8.34392309e-01 6.67037591e-02 -6.82203174e-01 5.90210736e-01 3.81897420e-01 1.00996685e+00 -1.81051344e-01 4.18110996e-01 -5.60927808e-01 9.21898246e-01 4.90895450e-01 1.27880916e-01 5.17316043e-01 -4.44951236e-01 5.41312039e-01 4.22393948e-01 -2.50492152e-02 -6.74856782e-01 -9.16742742e-01 -7.84387514e-02 1.41046512e+00 2.56731659e-01 -4.81826216e-01 -6.28330648e-01 -9.93361294e-01 -4.83091287e-02 1.07287180e+00 -4.22244459e-01 -5.97451143e-02 -7.24605322e-01 -2.73823798e-01 8.32964778e-01 1.52702063e-01 2.85749704e-01 -1.20572340e+00 -3.10228109e-01 2.28670582e-01 -9.52997327e-01 -1.36500239e+00 -4.33766752e-01 -2.65715480e-01 -6.26288891e-01 -1.36366558e+00 -7.06171453e-01 -1.25938570e+00 1.90375134e-01 5.84621429e-01 1.64130747e+00 2.34519392e-01 -1.79709084e-02 7.97402978e-01 -1.15996861e+00 -7.44910300e-01 -6.86072826e-01 1.52005002e-01 -3.94432783e-01 -3.72826487e-01 8.42192054e-01 1.61711559e-01 -2.41888940e-01 5.47757626e-01 -1.03225613e+00 -6.44067407e-01 -1.32982925e-01 3.30553442e-01 1.44788295e-01 -2.42931649e-01 1.25983202e+00 -5.45237482e-01 1.25026262e+00 -7.82549381e-01 -2.21269324e-01 9.21685398e-01 -1.26856774e-01 1.79452050e-04 5.34511745e-01 3.58926713e-01 -1.07661545e+00 -4.69953716e-01 -4.43902791e-01 5.91134667e-01 -1.70108646e-01 5.15031934e-01 2.43670382e-02 -2.46730521e-01 9.07522619e-01 -5.21163605e-02 1.03562698e-01 -5.51512122e-01 4.61011499e-01 1.04965234e+00 1.25369340e-01 -3.27453375e-01 2.61440903e-01 8.19550455e-02 -3.52548540e-01 -1.05460644e+00 -1.13416004e+00 -8.98051560e-01 -3.60358745e-01 -9.56318974e-02 8.04552674e-01 -8.02726388e-01 -3.04810971e-01 1.09175086e-01 -1.29652786e+00 1.39802277e-01 -1.67505577e-01 8.56137276e-02 -1.72915474e-01 6.14686489e-01 -3.22501481e-01 -2.65768856e-01 -4.82698441e-01 -5.74211240e-01 7.83641517e-01 3.49278390e-01 -7.24792778e-01 -1.04816258e+00 5.37926912e-01 1.14204085e+00 4.83831733e-01 -3.90916109e-01 1.20442176e+00 -1.44826090e+00 2.73869008e-01 7.72996396e-02 -1.72755465e-01 3.15639704e-01 2.73135543e-01 -3.09732407e-01 -6.16961777e-01 -1.63543314e-01 2.64532864e-01 -7.94460177e-01 2.99328834e-01 -2.52064884e-01 5.96168876e-01 -2.12226510e-01 2.72453517e-01 -5.12043357e-01 1.09924185e+00 -8.13967139e-02 5.65803051e-01 5.10350049e-01 2.06798211e-01 1.63289499e+00 9.39904392e-01 6.18237332e-02 9.02520061e-01 6.51711345e-01 2.46451184e-01 7.59276271e-01 -2.08424136e-01 1.30951777e-01 2.43904233e-01 9.81268704e-01 5.23859918e-01 -3.13569218e-01 -1.35951400e+00 8.30795944e-01 -1.74197483e+00 -5.53695202e-01 -7.26826847e-01 1.96428323e+00 9.57566440e-01 -7.54324853e-01 4.07973789e-02 -1.21476002e-01 7.48255134e-01 -1.98428959e-01 -3.65924686e-02 -8.67692709e-01 -4.37573344e-01 5.74816287e-01 -2.57487059e-01 5.64790010e-01 -7.59060323e-01 1.17764378e+00 6.19763184e+00 5.20989776e-01 -4.60567474e-01 3.51930052e-01 7.79902339e-02 4.65988606e-01 -5.76613724e-01 1.29648551e-01 -7.94360876e-01 4.29763079e-01 1.21429825e+00 -3.82768899e-01 1.55624136e-01 2.39678770e-01 -1.45100653e-01 -2.68318415e-01 -7.41597295e-01 4.57265824e-01 7.03921139e-01 -1.01056218e+00 3.36172760e-01 -9.00056124e-01 4.96445537e-01 1.81442127e-01 -2.48018935e-01 3.22975129e-01 4.20671582e-01 -1.05855274e+00 2.99044490e-01 2.09386796e-01 7.87544399e-02 -5.92720926e-01 1.07939076e+00 2.11704090e-01 -8.08951318e-01 -7.83222467e-02 -5.82086205e-01 -1.27588864e-02 1.31739125e-01 1.62622228e-01 -8.96865368e-01 6.35167420e-01 1.16965771e+00 5.20796120e-01 -1.04128015e+00 1.06745923e+00 -4.09128904e-01 4.44683075e-01 -8.08932483e-02 -3.26790571e-01 4.14513320e-01 -1.32021263e-01 5.13413608e-01 1.07256496e+00 2.83997267e-01 3.10217023e-01 -1.94843605e-01 5.13310909e-01 -1.70357615e-01 8.56692493e-01 -3.25800449e-01 -2.23028585e-01 5.85199416e-01 1.07988179e+00 -6.85434699e-01 -8.56022984e-02 -5.39542019e-01 1.12839890e+00 3.13445538e-01 5.86371087e-02 -3.45323771e-01 -9.60999429e-01 4.06500846e-01 -1.58821657e-01 1.39126480e-01 1.16511285e-01 4.41201450e-03 -1.05018878e+00 2.45040476e-01 -1.24662685e+00 8.42077613e-01 -1.19199824e+00 -1.82584584e+00 5.27059078e-01 -3.16263258e-01 -7.75682092e-01 -2.81291336e-01 -5.89517176e-01 -4.59442198e-01 1.07993066e+00 -1.66511977e+00 -8.73314798e-01 -5.18333972e-01 7.46121883e-01 4.27339435e-01 -1.68592006e-01 1.14758313e+00 2.02123314e-01 5.41871674e-02 4.31079239e-01 3.20887327e-01 7.45594054e-02 1.54845583e+00 -1.17003906e+00 4.91730064e-01 4.93943155e-01 4.03753847e-01 3.70916605e-01 5.39291799e-01 -6.65474951e-01 -1.00983262e+00 -8.16676795e-01 2.06662178e+00 -6.84930921e-01 8.17432046e-01 2.52753973e-01 -1.43819571e+00 2.73609251e-01 6.67897165e-01 -3.84024233e-01 1.19367957e+00 -3.46709192e-01 -5.00795007e-01 2.38484100e-01 -1.38758063e+00 2.56532192e-01 4.49681550e-01 -7.59260416e-01 -1.61280179e+00 8.02051783e-01 1.00220370e+00 -7.75367916e-02 -9.86910403e-01 1.32810444e-01 9.75449309e-02 -7.78235257e-01 7.62066424e-01 -1.01437497e+00 3.54537904e-01 -3.29611719e-01 -5.87883532e-01 -1.32108855e+00 -1.48338778e-02 -3.17723334e-01 3.06269705e-01 1.24659503e+00 4.63097125e-01 -7.66197205e-01 4.39274907e-01 5.15864193e-01 -1.64852381e-01 -1.20327652e-01 -1.14616430e+00 -8.55061710e-01 5.05905151e-01 9.39937122e-03 5.82289219e-01 1.26028717e+00 1.88426241e-01 7.52770662e-01 5.71433067e-01 2.58671194e-01 3.67569067e-02 1.49563938e-01 2.75448561e-01 -1.19415402e+00 2.45331153e-01 -3.92796129e-01 -2.91146606e-01 -6.99685156e-01 4.64827031e-01 -1.25089514e+00 1.43491909e-01 -1.78303146e+00 -2.33622640e-01 -3.87944609e-01 9.17938352e-02 2.99837798e-01 -6.78256452e-01 2.21499011e-01 2.86086470e-01 2.56197184e-01 -7.54639924e-01 4.71403807e-01 8.37743223e-01 9.74589363e-02 1.26303196e-01 -1.01962671e-01 -8.84375811e-01 4.58770603e-01 1.04130745e+00 -7.05161929e-01 -2.36319289e-01 -7.84031510e-01 7.11848736e-01 -1.86055735e-01 1.60078585e-01 -6.04261756e-01 3.31290185e-01 3.30288112e-02 -3.20796430e-01 -3.28524262e-01 7.54320920e-02 -7.36872315e-01 -5.97548187e-01 4.78279799e-01 -4.86797214e-01 7.09125280e-01 3.14124048e-01 1.99666084e-03 -6.97241724e-01 -1.21401274e+00 5.00730217e-01 -3.46500784e-01 -8.40977848e-01 -3.31428528e-01 -6.30995274e-01 1.02135468e+00 9.90660250e-01 1.41573235e-01 -4.60882515e-01 -6.51629686e-01 -3.51246953e-01 5.13766050e-01 2.38800585e-01 8.11371982e-01 6.93654537e-01 -1.18840194e+00 -1.39007115e+00 -4.60453033e-01 6.94868326e-01 -6.09315097e-01 6.53659850e-02 4.79204863e-01 -6.56043530e-01 8.15307558e-01 -2.98856229e-01 -1.18011139e-01 -1.45840609e+00 1.50770724e-01 3.29834610e-01 -2.05622632e-02 2.50971522e-02 1.04526818e+00 -6.25634134e-01 -1.17422056e+00 -2.04585522e-01 2.55194306e-01 -9.37934220e-01 3.73996854e-01 8.64216864e-01 6.69510365e-01 4.72780228e-01 -9.11190152e-01 -4.73705471e-01 5.33864915e-01 -8.70288387e-02 -2.42664397e-01 1.02484310e+00 -3.90766203e-01 -9.71587002e-01 3.95931959e-01 1.27569830e+00 -1.65410504e-01 9.11916196e-02 -5.67134380e-01 7.30827451e-01 -3.48124385e-01 -4.79281545e-01 -1.01752961e+00 -2.44853139e-01 6.48642063e-01 4.71213222e-01 5.67560315e-01 6.86550915e-01 3.28716397e-01 1.13724351e+00 9.50962961e-01 -6.73040748e-02 -1.36271656e+00 3.41974944e-01 1.26576638e+00 1.29029596e+00 -1.43951416e+00 -3.51670533e-01 -5.64189553e-01 -7.07065046e-01 1.21184337e+00 7.03746319e-01 2.22257465e-01 4.44684446e-01 -6.57580853e-01 3.12687248e-01 -4.09179837e-01 -4.32841629e-01 -3.68676186e-01 5.44437051e-01 6.43908083e-01 8.78853798e-01 -3.69817615e-01 -7.51572192e-01 6.93849087e-01 -4.71598685e-01 -3.92392606e-01 6.32508755e-01 1.39294589e+00 -6.66543722e-01 -1.13214362e+00 -4.81321454e-01 3.09449613e-01 -5.51641166e-01 -4.68488246e-01 -1.07716751e+00 2.54415005e-01 -2.05165520e-01 1.61223471e+00 1.64543346e-01 2.32176594e-02 6.02426171e-01 3.20855588e-01 4.54406977e-01 -9.21579480e-01 -1.28233016e+00 -1.03669631e+00 5.56175709e-01 -5.39452612e-01 -4.81932759e-01 -6.35237873e-01 -1.32285976e+00 -1.14872240e-01 -2.59621829e-01 7.36236930e-01 7.18587399e-01 1.10942554e+00 6.20368540e-01 -1.24520145e-01 4.84212995e-01 2.50971228e-01 -6.42808259e-01 -9.82950449e-01 -2.94237584e-01 5.45286298e-01 -1.95172191e-01 -1.38563514e-01 -3.06913614e-01 -5.11007644e-02]	[11.366737365722656, 8.050127983093262]
c1908367-23b9-48fc-ad00-bea1806f589c	fair-decision-making-under-uncertainty	2301.12364	null	https://arxiv.org/abs/2301.12364v1	https://arxiv.org/pdf/2301.12364v1.pdf	Fair Decision-making Under Uncertainty	There has been concern within the artificial intelligence (AI) community and the broader society regarding the potential lack of fairness of AI-based decision-making systems. Surprisingly, there is little work quantifying and guaranteeing fairness in the presence of uncertainty which is prevalent in many socially sensitive applications, ranging from marketing analytics to actuarial analysis and recidivism prediction instruments. To this end, we study a longitudinal censored learning problem subject to fairness constraints, where we require that algorithmic decisions made do not affect certain individuals or social groups negatively in the presence of uncertainty on class label due to censorship. We argue that this formulation has a broader applicability to practical scenarios concerning fairness. We show how the newly devised fairness notions involving censored information and the general framework for fair predictions in the presence of censorship allow us to measure and mitigate discrimination under uncertainty that bridges the gap with real-world applications. Empirical evaluations on real-world discriminated datasets with censorship demonstrate the practicality of our approach.	['Jeremy C. Weiss', 'Wenbin Zhang']	2023-01-29	null	null	null	null	['decision-making-under-uncertainty', 'marketing', 'decision-making-under-uncertainty']	['medical', 'miscellaneous', 'reasoning']	[ 4.29070950e-01 5.04093111e-01 -5.71971953e-01 -9.17366385e-01 -2.13660270e-01 -5.70634246e-01 5.25114596e-01 3.47089410e-01 -4.15353388e-01 1.20639598e+00 6.77484497e-02 -3.95217985e-01 -6.38282597e-01 -6.72452629e-01 -3.26053858e-01 -4.92143840e-01 5.28209880e-02 2.72014767e-01 -4.93255377e-01 1.27817001e-02 3.42361152e-01 5.15603304e-01 -1.31557512e+00 -1.56537250e-01 1.20137978e+00 1.01534712e+00 -9.29508448e-01 6.28203303e-02 6.97802156e-02 8.52530122e-01 -3.36917907e-01 -1.17118108e+00 3.76113594e-01 -1.89601809e-01 -6.77177787e-01 -1.38221040e-01 5.12277782e-01 -4.63136971e-01 9.50146690e-02 1.30034995e+00 4.95464087e-01 -2.84798797e-02 7.19331741e-01 -1.78876364e+00 -7.42780626e-01 7.94898987e-01 -5.07834792e-01 -1.68964431e-01 8.10969919e-02 -7.91971534e-02 1.08154345e+00 -1.93714485e-01 2.58845270e-01 1.39772677e+00 5.94547749e-01 8.85893106e-01 -1.08928835e+00 -7.22031832e-01 1.90061495e-01 -7.71596208e-02 -9.70135689e-01 -6.19592667e-01 7.42092311e-01 -6.95947468e-01 -9.38106850e-02 7.22807229e-01 1.67574763e-01 1.17554533e+00 3.91111702e-01 3.64528924e-01 1.30922890e+00 -3.08446169e-01 7.71603703e-01 3.02593708e-01 5.94521344e-01 2.17573524e-01 9.59251344e-01 6.11953676e-01 -3.97759169e-01 -6.91258788e-01 1.90410614e-01 2.24053815e-01 6.70713000e-03 -5.58768570e-01 -7.45261490e-01 1.20568037e+00 1.63436621e-01 -6.13820516e-02 -3.44529033e-01 -1.57242298e-01 2.47380510e-01 4.72370118e-01 7.57915378e-01 4.24940407e-01 -2.43405148e-01 2.30507389e-01 -9.43675578e-01 3.32878709e-01 9.74344850e-01 6.20949924e-01 1.49230808e-01 -1.34459302e-01 -5.55006862e-01 4.75661010e-01 2.30858117e-01 2.61489183e-01 3.09802871e-02 -1.39503741e+00 2.20090583e-01 4.49425459e-01 5.90704143e-01 -9.50326622e-01 -2.36266255e-01 -6.06331348e-01 -8.19332719e-01 7.19857395e-01 7.39717185e-01 -3.94986451e-01 -9.53428373e-02 2.13059807e+00 2.90228784e-01 -2.54923612e-01 6.33595064e-02 1.04118717e+00 5.86672351e-02 -1.96822062e-01 4.08006310e-01 -5.30324578e-01 9.81622100e-01 -2.60423183e-01 -8.56181979e-01 -2.20650241e-01 2.50420600e-01 -2.30631292e-01 8.94818306e-01 3.41706544e-01 -1.00103712e+00 2.10289165e-01 -8.78128231e-01 8.31993818e-02 -7.00061172e-02 -4.29104716e-01 9.59408283e-01 1.31919122e+00 -4.91123229e-01 9.21389580e-01 -3.02481592e-01 -4.67710972e-01 9.48721528e-01 2.31905043e-01 -1.33089051e-01 1.35413468e-01 -1.24540782e+00 7.79855192e-01 -1.25299677e-01 1.36097103e-01 -5.60252488e-01 -6.51939392e-01 -3.84672076e-01 2.03259662e-01 5.99435508e-01 -8.28631163e-01 9.21276450e-01 -1.48522222e+00 -1.11179459e+00 1.09786320e+00 3.86554599e-01 -7.82107532e-01 1.46820450e+00 -1.16917022e-01 -2.89567351e-01 -4.82211947e-01 1.69524014e-01 1.10476755e-01 8.02802682e-01 -9.85974908e-01 -4.78539914e-01 -9.31972682e-01 1.40929446e-01 1.14985429e-01 -3.92122298e-01 1.74799979e-01 7.89632499e-01 -6.49253011e-01 -3.30219448e-01 -9.25753772e-01 -2.82576591e-01 4.53125596e-01 -4.34417874e-01 -2.27439433e-01 3.85478139e-01 -2.51566797e-01 9.91303563e-01 -2.02310491e+00 -3.52678955e-01 1.43124700e-01 1.72286555e-01 5.32198995e-02 1.82111055e-01 1.64043471e-01 1.05723694e-01 3.83900553e-01 -4.86554027e-01 -1.51608855e-01 4.93613213e-01 1.10234618e-01 -5.12685895e-01 7.50695407e-01 -1.00980930e-01 6.32532537e-01 -7.16607630e-01 -3.51048112e-01 -4.77848351e-02 -1.38921645e-02 -4.23620105e-01 1.53409436e-01 -8.61325189e-02 3.50825787e-01 -6.21724963e-01 6.50157511e-01 6.85737967e-01 5.13412729e-02 1.94096908e-01 5.36388457e-01 -3.70424651e-02 -2.06987858e-01 -9.21203256e-01 1.09306121e+00 1.41610324e-01 2.45984897e-01 2.52405494e-01 -9.03159857e-01 7.74833083e-01 1.46532536e-01 1.26766503e-01 -3.21805745e-01 3.61635536e-01 1.23243883e-01 -7.00548245e-03 -2.67350137e-01 2.97741175e-01 -7.49079585e-01 -2.78589278e-01 5.96248031e-01 -4.56098765e-01 -1.40093993e-02 -4.80067611e-01 -1.99020505e-02 6.44414902e-01 -2.61330068e-01 4.36119974e-01 -6.14509523e-01 3.40442985e-01 -2.03764930e-01 9.51633096e-01 1.02884722e+00 -9.88391399e-01 3.85725886e-01 8.06651652e-01 -3.96467447e-01 -6.88844204e-01 -9.96330202e-01 -3.58487189e-01 1.20229256e+00 3.03882896e-03 6.03193879e-01 -7.18505502e-01 -8.58253539e-01 4.82862651e-01 1.26970875e+00 -8.80795300e-01 -3.80189449e-01 2.10950553e-01 -7.94595242e-01 5.04201412e-01 1.58013150e-01 1.86308235e-01 -7.17410326e-01 -6.60578132e-01 -1.38050869e-01 1.41738579e-01 -7.06398964e-01 -4.53772813e-01 -2.29240894e-01 -7.82958686e-01 -1.13886058e+00 -6.93655133e-01 -5.96250258e-02 4.43454355e-01 -2.72919655e-01 1.02828360e+00 -6.46800026e-02 -8.94474536e-02 4.68719333e-01 -2.82251253e-03 -7.44986355e-01 -4.73681003e-01 -3.60047817e-01 1.94893166e-01 3.10903221e-01 5.66282690e-01 -5.22839844e-01 -5.58543861e-01 2.60581106e-01 -8.24030340e-01 -1.92000553e-01 4.47956957e-02 6.02548718e-01 -5.34372106e-02 -8.55537578e-02 1.22488248e+00 -1.31711853e+00 9.19354141e-01 -7.66295552e-01 -7.48613477e-01 4.84531879e-01 -1.19673645e+00 -8.80467668e-02 2.92927772e-01 -3.48250061e-01 -1.25149059e+00 -2.91314304e-01 6.87532961e-01 5.03913388e-02 -1.64855912e-01 2.74311870e-01 -4.18084472e-01 -7.59956315e-02 5.99906206e-01 -5.10451972e-01 2.50062495e-01 -2.72261411e-01 4.77255642e-01 8.74522388e-01 3.33275706e-01 -7.71634698e-01 4.40531015e-01 5.99425972e-01 3.94550085e-01 -2.28506595e-01 -1.16144300e+00 2.19765216e-01 -2.27625743e-01 -2.39543706e-01 6.58692479e-01 -5.62824607e-01 -1.21981692e+00 2.72108555e-01 -8.58831406e-01 1.76922545e-01 -5.79783618e-01 4.82197255e-01 -6.50345206e-01 4.56690431e-01 -2.52309769e-01 -1.41553998e+00 -4.15104806e-01 -6.55083776e-01 3.50235075e-01 2.44813204e-01 -2.76616752e-01 -9.00988042e-01 -1.72735646e-01 8.10888290e-01 5.09293973e-01 5.16837716e-01 1.02313113e+00 -9.60722804e-01 -1.88278690e-01 -4.00391668e-01 -1.11173972e-01 3.13043624e-01 1.09057702e-01 -2.75365353e-01 -1.03575706e+00 -1.55339941e-01 1.09127402e-01 -3.09875876e-01 6.38071597e-01 3.49163026e-01 1.01645219e+00 -7.37526596e-01 1.39205396e-01 2.57817190e-02 1.09234571e+00 1.70486397e-03 1.85900301e-01 -4.08197641e-02 2.28435710e-01 1.41306686e+00 5.89905381e-01 9.89015281e-01 4.22302932e-01 4.90496486e-01 6.61404133e-01 2.98267156e-01 3.40874612e-01 -1.46377757e-01 1.35953143e-01 -7.00206310e-02 2.58349478e-02 -1.67274892e-01 -8.00654054e-01 5.24611294e-01 -2.04082131e+00 -1.05734801e+00 5.69534600e-02 2.82817459e+00 8.62644792e-01 -9.09706391e-03 2.71349877e-01 1.20716929e-01 1.07838309e+00 -8.70911554e-02 -8.60995770e-01 -8.06879878e-01 -1.72142550e-01 -4.23312873e-01 6.24114335e-01 6.04909301e-01 -1.00141668e+00 4.04012054e-01 5.98291016e+00 5.70726812e-01 -7.39682436e-01 -1.78035232e-03 1.16806948e+00 -2.43766978e-01 -5.89012206e-01 1.67794079e-01 -2.38492265e-01 5.46882629e-01 6.82632744e-01 -7.29463935e-01 3.81058604e-01 6.70761049e-01 3.73317301e-01 1.02239102e-01 -1.37825966e+00 4.89588827e-01 -2.15864584e-01 -6.43580675e-01 -2.33054474e-01 2.57504404e-01 7.78208673e-01 -5.07076740e-01 3.34201097e-01 7.33535066e-02 6.38189256e-01 -1.18079078e+00 7.82302499e-01 8.53140414e-01 5.44296086e-01 -8.79665732e-01 6.92512333e-01 5.00110507e-01 3.18172909e-02 -3.58583361e-01 -2.62016237e-01 -5.78393161e-01 -1.02543220e-01 1.01293433e+00 -4.33682084e-01 3.57665300e-01 1.66099891e-01 3.19429904e-01 -2.60238945e-01 8.16118300e-01 -9.22834873e-02 6.52578056e-01 5.02337515e-02 3.17064114e-02 -1.17723942e-02 -2.74509460e-01 5.58006465e-01 5.95695496e-01 1.53903767e-01 1.13349915e-01 -2.65531719e-01 1.19896746e+00 -1.88013196e-01 1.41937837e-01 -6.49221718e-01 -8.45014155e-02 4.23530042e-01 8.47742200e-01 -2.32799098e-01 3.86820659e-02 -2.82500416e-01 6.71392024e-01 1.18006349e-01 3.31373870e-01 -5.41358411e-01 6.49628937e-02 6.63801193e-01 1.23907596e-01 -4.07922655e-01 2.63370901e-01 -9.11446095e-01 -1.19150591e+00 -1.70746911e-02 -6.22183621e-01 7.65833795e-01 -3.50799114e-01 -2.06135821e+00 -2.74838991e-02 -1.57382905e-01 -9.42650020e-01 -1.01657689e-01 -1.46015316e-01 -6.08683884e-01 7.84841537e-01 -1.58530521e+00 -9.73500669e-01 6.11861311e-02 4.18931335e-01 -1.16001546e-01 -1.04185253e-01 7.24262476e-01 4.74408306e-02 -5.94831824e-01 6.63476229e-01 1.68802425e-01 -2.29566172e-01 8.25611770e-01 -1.11582530e+00 -1.19945249e-02 6.67748630e-01 -3.23640645e-01 4.63148892e-01 8.54676425e-01 -6.85744882e-01 -9.81287122e-01 -1.15619707e+00 1.16088879e+00 -5.39042950e-01 5.72792113e-01 -2.48586133e-01 -7.46246099e-01 6.18945181e-01 -1.47484615e-01 2.56432563e-01 9.53109443e-01 2.89108872e-01 -4.85693604e-01 -1.03566982e-01 -1.84745836e+00 5.16741812e-01 1.03529441e+00 -4.33374703e-01 -7.21157193e-01 2.06174865e-01 5.68835139e-01 2.51987159e-01 -7.87903309e-01 3.45448256e-01 8.50883245e-01 -1.02148724e+00 6.10642672e-01 -1.20748651e+00 2.49228254e-01 2.15928838e-01 -3.72172445e-01 -9.60510910e-01 -2.12719530e-01 -6.71715081e-01 3.05293858e-01 1.50877213e+00 1.61669403e-01 -8.87715638e-01 7.60188341e-01 1.67977607e+00 5.49762845e-01 -2.61266023e-01 -1.38190579e+00 -6.89044774e-01 7.58663118e-01 -3.39335561e-01 8.70101154e-01 1.38275087e+00 1.01821691e-01 -1.59590617e-01 -6.98631525e-01 1.53596118e-01 1.36060631e+00 3.88471544e-01 2.53921568e-01 -1.90636241e+00 6.25213282e-03 -3.36618245e-01 -3.65941405e-01 6.61605299e-02 5.69180489e-01 -5.92802465e-01 -2.98068970e-01 -8.23177695e-01 4.89448696e-01 -5.86078405e-01 -5.96336424e-01 3.44631314e-01 -2.65693635e-01 -1.59175038e-01 3.70258063e-01 2.10141703e-01 -4.71276373e-01 6.35530293e-01 8.57519865e-01 -7.46660531e-02 1.54576033e-01 5.58561921e-01 -1.32327271e+00 7.15935230e-01 6.92913294e-01 -8.03969800e-01 -2.78519362e-01 -6.66090697e-02 2.54012108e-01 2.81247586e-01 7.74799228e-01 -4.67181623e-01 1.17843725e-01 -7.79652655e-01 -3.59886847e-02 2.60303408e-01 -6.31585941e-02 -1.15861893e+00 1.30173922e-01 4.19846952e-01 -9.74239409e-01 -7.34011710e-01 -3.78868908e-01 7.86272645e-01 3.25861186e-01 -2.10000426e-01 8.70812654e-01 1.82556346e-01 9.42715928e-02 3.38870347e-01 1.30441235e-02 3.23105693e-01 1.18062234e+00 6.24923222e-02 -5.48299253e-01 -6.38956726e-01 -7.91352749e-01 3.76306593e-01 6.13938570e-01 4.04001147e-01 1.12904437e-01 -1.20061898e+00 -9.49186146e-01 -3.77851389e-02 1.15275264e-01 -7.19519436e-01 2.01746687e-01 5.72459757e-01 2.32266396e-01 4.02928293e-01 -2.67400384e-01 9.17644054e-02 -1.03798711e+00 5.82585812e-01 3.93634111e-01 1.53793916e-01 -1.34524971e-03 3.66786957e-01 2.86819249e-01 -3.64402384e-01 4.17153001e-01 7.47694671e-02 -9.14184451e-02 1.15641281e-01 3.28124195e-01 9.49513376e-01 -1.89517707e-01 -5.46880841e-01 -4.40411985e-01 1.44046962e-01 1.23618364e-01 -2.53149003e-01 1.09582686e+00 -5.59312701e-01 -1.05103739e-01 5.71066141e-01 5.53741634e-01 9.20862257e-02 -1.38415766e+00 -2.30815813e-01 3.63396555e-01 -7.16865301e-01 1.39737008e-02 -1.20950496e+00 -9.27668035e-01 7.94158757e-01 6.40478611e-01 4.55180109e-01 8.16747308e-01 -3.58070195e-01 1.79576859e-01 1.07065462e-01 4.96615529e-01 -1.02793467e+00 -7.78640449e-01 -2.35145018e-01 9.14641261e-01 -1.43198216e+00 6.00458272e-02 -2.33579502e-01 -9.01301026e-01 6.95602238e-01 2.12491333e-01 7.51946643e-02 6.12423897e-01 -2.50779092e-01 1.11381218e-01 1.68882653e-01 -6.23673916e-01 1.83781520e-01 2.79235631e-01 5.22750378e-01 3.84631097e-01 7.55075157e-01 -9.46272016e-01 1.25952005e+00 -1.13838419e-01 5.03025949e-01 7.73256898e-01 8.46377671e-01 -3.19574445e-01 -8.63335490e-01 -4.12319750e-01 5.82458258e-01 -9.02095437e-01 1.06692433e-01 -7.37772822e-01 2.61654913e-01 6.37269095e-02 1.37932992e+00 -1.94668800e-01 2.61462629e-01 1.66457638e-01 1.20623864e-01 1.52741447e-01 -2.91366339e-01 -6.58518672e-01 -4.76487190e-01 1.60657451e-01 -6.09661162e-01 -5.29663146e-01 -8.44744980e-01 -7.24660456e-01 -5.96683860e-01 -2.90343314e-01 3.34945291e-01 4.71523404e-01 9.20777202e-01 4.93982017e-01 -1.46736905e-01 8.38892162e-01 -1.81702878e-02 -1.33438373e+00 -4.17638659e-01 -1.12407589e+00 5.42309761e-01 5.65646350e-01 -5.07540882e-01 -7.80613959e-01 -4.19525981e-01]	[8.820112228393555, 5.332359313964844]
eca022a2-f884-4044-833b-765bb27ed226	learning-noise-invariant-representations-for-1	null	null	https://openreview.net/forum?id=ryz4mqPx9m	https://openreview.net/pdf?id=ryz4mqPx9m	Learning Noise-Invariant Representations for Robust Speech Recognition	Despite rapid advances in speech recognition, current models remain brittle to superficial perturbations to their inputs. Small amounts of noise can destroy the performance of an otherwise state-of-the-art model. To harden models against background noise, practitioners often perform data augmentation, adding artificially-noised examples to the training set, carrying over the original label. In this paper, we hypothesize that a clean example and its superficially perturbed counterparts shouldn't merely map to the same class--- they should map to the same representation. We propose invariant-representation-learning (IRL): At each training iteration, for each training example, we sample a noisy counterpart. We then apply a penalty term to coerce matched representations at each layer (above some chosen layer). Our key results, demonstrated on the LibriSpeech dataset are the following: (i) IRL significantly reduces character error rates (CER)on both `clean' (3.3% vs 6.5%) and `other' (11.0% vs 18.1%) test sets; (ii) on several out-of-domain noise settings (different from those seen during training), IRL's benefits are even more pronounced. Careful ablations confirm that our results are not simply due to shrinking activations at the chosen layers.	['Anonymous']	2018-10-02	null	null	null	null	['robust-speech-recognition']	['speech']	[ 7.46208668e-01 3.08175474e-01 1.15649112e-01 -4.20971185e-01 -1.12390065e+00 -6.58017337e-01 6.47673726e-01 7.98896477e-02 -7.24242389e-01 7.63303518e-01 3.68348986e-01 -2.52817988e-01 1.27622426e-01 -4.29102540e-01 -9.13945198e-01 -7.55093873e-01 2.00774167e-02 3.08357954e-01 2.27159187e-01 -2.42589116e-01 1.39436200e-01 4.25617665e-01 -1.44788194e+00 6.77937269e-01 6.74316883e-01 6.56816959e-01 9.94222015e-02 6.31218255e-01 -5.49310260e-03 7.20155895e-01 -9.43376780e-01 -4.06851262e-01 1.50532275e-01 -4.38861758e-01 -8.14147592e-01 -9.91053358e-02 6.69853926e-01 -4.20345552e-02 -4.22013104e-01 1.13860309e+00 5.21601617e-01 2.97657460e-01 6.09005332e-01 -8.06941926e-01 -7.98958957e-01 8.51465642e-01 -3.48500013e-01 3.12497377e-01 8.70095789e-02 2.21028045e-01 9.55751538e-01 -9.12876785e-01 6.47739947e-01 1.04543507e+00 8.70685220e-01 1.04936850e+00 -1.70010722e+00 -5.23036003e-01 4.27789241e-01 -2.06101816e-02 -1.23772371e+00 -9.80595291e-01 5.72010398e-01 -1.08885951e-01 1.10587382e+00 6.24661028e-01 3.21457624e-01 1.52160251e+00 -3.55410933e-01 8.08524847e-01 1.26495063e+00 -4.86936897e-01 2.25557402e-01 1.70948595e-01 1.12133414e-01 2.92056799e-01 2.18371540e-01 7.75312111e-02 -6.42866671e-01 -3.55810635e-02 4.52153593e-01 -5.61665833e-01 -5.24969876e-01 4.47803773e-02 -1.03028202e+00 4.02258039e-01 4.46189106e-01 4.28887248e-01 -2.99494445e-01 1.99139312e-01 3.99642527e-01 3.14106762e-01 3.71358603e-01 7.56665409e-01 -4.97518867e-01 -2.73568839e-01 -8.37459564e-01 1.79996625e-01 6.83799624e-01 7.53428102e-01 4.85176027e-01 2.97973782e-01 -1.58288851e-01 1.19132662e+00 -5.55692334e-03 2.12413937e-01 7.14103580e-01 -7.07668841e-01 5.96656322e-01 2.55425751e-01 -1.34236977e-01 -5.86052656e-01 -1.95596203e-01 -6.54842675e-01 -7.59109139e-01 2.13322356e-01 6.64680958e-01 -7.75634497e-02 -1.22509944e+00 2.13228631e+00 -1.77726060e-01 5.31497709e-02 1.90345347e-01 6.42374516e-01 6.35346889e-01 6.22666478e-01 1.83672965e-01 1.31944828e-02 1.02918923e+00 -6.26409113e-01 -5.87153673e-01 -8.73580158e-01 7.25802362e-01 -6.84418321e-01 1.44431412e+00 5.03316402e-01 -1.10661900e+00 -4.83109534e-01 -1.01515472e+00 4.50713746e-02 -4.03459489e-01 2.94443406e-03 2.59706140e-01 6.70088649e-01 -9.54538226e-01 6.42911077e-01 -5.53262591e-01 -1.82662264e-01 6.39338851e-01 1.75311118e-01 -5.70697367e-01 -1.64892524e-01 -1.09678066e+00 1.08184302e+00 2.18358681e-01 1.31595775e-01 -9.88504410e-01 -7.19562709e-01 -7.31716275e-01 7.01491684e-02 3.16182256e-01 -3.29550356e-01 1.27412796e+00 -1.14620352e+00 -1.27296519e+00 9.78223801e-01 -2.40143940e-01 -4.69069988e-01 4.28157419e-01 -5.30015349e-01 -4.67202902e-01 -1.21712990e-01 -2.20289491e-02 5.93296766e-01 9.03756618e-01 -1.63757777e+00 -2.21311063e-01 -6.95282891e-02 -2.35773921e-01 1.92588359e-01 -2.81396180e-01 -2.81769466e-02 -3.59572560e-01 -1.01461899e+00 2.97253191e-01 -7.45298624e-01 -2.99441852e-02 -1.34062454e-01 -6.21866107e-01 9.11284313e-02 5.48046768e-01 -7.34993041e-01 1.10834479e+00 -2.42871642e+00 1.35536730e-01 2.19078451e-01 4.54716757e-02 7.68014252e-01 -4.33727711e-01 2.24779084e-01 -4.19671148e-01 3.88969809e-01 -5.47870636e-01 -5.52574039e-01 -9.52046737e-02 3.36992979e-01 -4.47702974e-01 4.18585688e-01 5.07777750e-01 7.72897005e-01 -8.09076786e-01 8.12812001e-02 -1.53462589e-03 4.69239920e-01 -6.60890102e-01 -4.10996983e-03 -1.41792879e-01 2.05883443e-01 1.87452033e-01 1.82686746e-01 5.08379400e-01 2.51602113e-01 2.87357438e-02 -4.28875461e-02 1.00426249e-01 7.69224286e-01 -1.10324311e+00 1.59555531e+00 -3.68919313e-01 8.15685928e-01 1.42887369e-01 -9.49901342e-01 9.03177321e-01 2.07435384e-01 -2.18261406e-01 -7.01568127e-01 -7.01947510e-02 3.00819904e-01 4.90759671e-01 -3.75321060e-01 2.44754285e-01 -3.79903257e-01 3.68848294e-02 4.09010768e-01 -5.87581545e-02 -8.61342028e-02 -1.00500710e-01 8.92020687e-02 1.26639366e+00 -1.40257716e-01 -1.23353541e-01 -1.73722625e-01 2.25133866e-01 -3.55053335e-01 6.59442723e-01 1.01766491e+00 -2.24031731e-01 9.64436054e-01 5.83955765e-01 -1.72120884e-01 -1.16291296e+00 -1.18201375e+00 -3.01625013e-01 1.05999148e+00 -3.90980601e-01 -3.14358652e-01 -8.77083719e-01 -5.86814404e-01 1.53816836e-02 9.16152596e-01 -5.81462562e-01 -6.01698101e-01 -6.85838938e-01 -8.16501260e-01 1.11425495e+00 6.06672287e-01 3.80330443e-01 -1.14848387e+00 -2.55591959e-01 9.67169106e-02 -5.55310166e-04 -1.02741230e+00 -2.68929809e-01 6.96640849e-01 -6.60898626e-01 -6.66754425e-01 -5.26885748e-01 -7.75460720e-01 8.19936991e-01 5.79463281e-02 9.71058130e-01 2.86741495e-01 -7.49375522e-02 -8.09718445e-02 -3.75133753e-01 -1.01446092e-01 -7.66147196e-01 1.89887255e-01 2.42156371e-01 -1.60885032e-03 2.68348932e-01 -5.56177080e-01 -1.96794033e-01 1.78126454e-01 -9.48370099e-01 -1.59935117e-01 5.91415405e-01 1.04141772e+00 4.06668693e-01 -2.02897526e-02 7.46883512e-01 -1.04431403e+00 7.61138737e-01 -2.74257541e-01 -1.39743015e-01 6.08923137e-02 -2.45882168e-01 1.67903543e-01 8.07239354e-01 -7.30623066e-01 -8.44726145e-01 -1.66832983e-01 -3.38320404e-01 -2.94139057e-01 -5.45498431e-01 3.75218332e-01 -3.71613175e-01 2.84823865e-01 1.10746562e+00 2.40512967e-01 -1.03817895e-01 -6.66199207e-01 4.34637934e-01 7.57014334e-01 7.90036857e-01 -5.98643243e-01 9.77460742e-01 1.54786110e-01 -5.41389883e-01 -1.00341129e+00 -8.12696338e-01 -2.34341584e-02 -4.67643589e-01 1.36408404e-01 5.83215952e-01 -7.63367534e-01 -2.97607422e-01 5.75240910e-01 -1.02802110e+00 -7.52707064e-01 -4.98275638e-01 3.71471882e-01 -2.33609006e-01 2.65848339e-01 -5.60017288e-01 -8.79714489e-01 -8.84299874e-02 -9.89446402e-01 5.92296779e-01 -1.27715804e-02 -6.15512609e-01 -7.27162838e-01 -1.40342265e-01 3.37349415e-01 5.79570532e-01 -1.45742700e-01 1.07119370e+00 -9.16247964e-01 -4.72426638e-02 -3.80759478e-01 -1.19470567e-01 8.24291527e-01 9.24769118e-02 5.25835454e-02 -1.66617692e+00 -3.31168979e-01 5.92088923e-02 -5.13890505e-01 1.13180614e+00 1.10457100e-01 1.31422329e+00 -3.71450484e-01 -1.13732055e-01 6.63939297e-01 9.28641081e-01 8.47025514e-02 8.63860726e-01 4.99204755e-01 5.21753311e-01 5.75373054e-01 -1.33768171e-02 2.10289378e-02 -3.08055311e-01 6.69510782e-01 2.75600195e-01 -9.75473523e-02 -6.04095221e-01 -3.73207420e-01 5.42588949e-01 7.80250311e-01 2.44326144e-01 -2.50915378e-01 -9.01403010e-01 7.06253946e-01 -1.46258211e+00 -1.06591797e+00 3.33164446e-02 2.32827115e+00 1.21963251e+00 6.60355926e-01 -1.43530993e-02 4.43269223e-01 7.13432848e-01 1.45275161e-01 -6.15538239e-01 -4.62404490e-01 -4.43935394e-01 3.46573889e-01 1.90688223e-01 6.68864787e-01 -1.12177920e+00 1.07886636e+00 6.48201466e+00 6.99282169e-01 -1.12967324e+00 -1.41003385e-01 7.57598996e-01 -3.71078491e-01 -4.84066516e-01 -2.08267644e-01 -6.91842914e-01 4.88277674e-01 9.83077109e-01 1.61341414e-01 7.02655435e-01 7.08964229e-01 -5.45496158e-02 1.08045004e-01 -1.11690879e+00 7.62486875e-01 1.51357591e-01 -1.20943379e+00 3.80957648e-02 -8.37468058e-02 6.13261521e-01 1.62123457e-01 3.20641130e-01 4.36024725e-01 3.67747068e-01 -1.34613192e+00 9.04167712e-01 3.13237906e-01 9.35882688e-01 -6.97174311e-01 6.02859259e-01 3.97879839e-01 -6.01976991e-01 6.87367916e-02 -4.73670393e-01 -7.02923983e-02 -8.57604742e-02 5.71120739e-01 -8.42742026e-01 -5.43249138e-02 6.78605378e-01 3.32675666e-01 -7.32465863e-01 9.22736406e-01 -5.99831760e-01 9.35747683e-01 -4.36576605e-01 1.40266418e-01 1.62115797e-01 2.04750896e-01 5.07000268e-01 1.43581831e+00 -1.15417801e-01 -1.35087192e-01 -3.57091069e-01 9.35933411e-01 -3.86418551e-01 -2.93754399e-01 -6.97348237e-01 -4.75116707e-02 8.07893634e-01 8.61095726e-01 -4.11082268e-01 -2.58411407e-01 -2.21329972e-01 1.07745767e+00 6.72075927e-01 5.05459249e-01 -5.87858379e-01 -6.40938103e-01 9.35299098e-01 2.11902335e-02 3.46279204e-01 7.90363476e-02 -5.87836266e-01 -9.35056448e-01 2.23170519e-01 -1.16987598e+00 -1.05212731e-02 -7.16171682e-01 -1.37204742e+00 8.69132459e-01 -3.70879680e-01 -8.02122056e-01 -4.94903848e-02 -6.44136012e-01 -5.93692124e-01 1.16395068e+00 -1.22693121e+00 -6.01579785e-01 -2.48685423e-02 2.46157005e-01 4.51038510e-01 -2.21646979e-01 1.11134648e+00 3.55553687e-01 -8.51657093e-01 1.05209374e+00 1.42040849e-01 4.57907468e-01 6.68521404e-01 -1.28218424e+00 8.37945163e-01 1.11987042e+00 4.51654702e-01 9.52558398e-01 7.03777850e-01 -5.24303794e-01 -9.55341339e-01 -9.81131852e-01 8.24886322e-01 -5.97693264e-01 6.40381634e-01 -6.63137436e-01 -1.47014260e+00 7.56350458e-01 -3.99957187e-02 1.55889153e-01 6.35728538e-01 3.07097077e-01 -8.81824255e-01 -1.14316102e-02 -1.04972112e+00 9.23646390e-01 1.10430169e+00 -8.96472454e-01 -7.73199618e-01 4.94385660e-02 6.59703732e-01 -3.05392742e-01 -5.13481021e-01 1.94106862e-01 3.92087221e-01 -8.35491955e-01 8.91125441e-01 -1.05544078e+00 2.25103542e-01 -3.15216899e-01 -4.59284157e-01 -1.56227851e+00 -3.83796364e-01 -6.99967861e-01 5.49026094e-02 1.30779517e+00 7.23758817e-01 -4.05545592e-01 7.43002832e-01 5.92683136e-01 -4.89163846e-01 -6.27592981e-01 -1.24869668e+00 -8.97197247e-01 3.20758581e-01 -8.29831004e-01 3.23592186e-01 1.02911627e+00 7.51804709e-02 5.56445301e-01 -1.69362485e-01 2.59831905e-01 2.08631620e-01 -7.17065573e-01 6.36728823e-01 -9.33630288e-01 -4.02095079e-01 -6.42565012e-01 -2.72846222e-01 -8.23532581e-01 1.27138749e-01 -9.61345196e-01 2.79452890e-01 -1.29956925e+00 -1.34029731e-01 -6.67374909e-01 -3.44566196e-01 8.54753494e-01 -4.30228770e-01 3.48225296e-01 2.31114179e-01 4.49550450e-02 -7.14583173e-02 4.64425296e-01 7.39173651e-01 -1.22539103e-01 -2.36118380e-02 -7.04054832e-02 -9.61530805e-01 7.15130448e-01 9.79928613e-01 -5.50182223e-01 -3.60273838e-01 -6.98783755e-01 1.71600074e-01 -5.76042533e-01 3.42284292e-01 -1.20180202e+00 -9.20418724e-02 2.03190267e-01 3.81434560e-01 4.35848534e-02 5.29586375e-01 -4.98345375e-01 -1.08868867e-01 5.17831028e-01 -7.23234653e-01 -2.20229119e-01 6.87528968e-01 4.43570256e-01 3.44934314e-02 -6.28873467e-01 1.04933167e+00 -8.78072716e-03 -4.81497586e-01 -2.74623513e-01 -5.34691751e-01 3.36438656e-01 5.74907541e-01 -1.56959236e-01 -6.01375818e-01 -2.68521369e-01 -8.05741489e-01 -2.93302834e-01 4.68586653e-01 3.11465591e-01 5.55956662e-01 -1.09787321e+00 -8.30981672e-01 5.56927741e-01 1.11587822e-01 1.32531449e-01 -4.90334816e-03 5.31207144e-01 -2.54049867e-01 2.37047821e-02 1.31634057e-01 -4.06349212e-01 -1.18953979e+00 2.95560718e-01 4.87345070e-01 9.98598114e-02 -6.70865655e-01 1.36634696e+00 9.24246609e-02 -5.66857398e-01 6.77122235e-01 -3.32995683e-01 2.38513663e-01 -5.26623684e-04 6.49139285e-01 1.32359818e-01 2.74097890e-01 -4.18832541e-01 -4.08313751e-01 1.92183018e-01 -5.30030429e-01 -2.93406218e-01 1.43840814e+00 3.07091981e-01 2.69076079e-01 5.42988956e-01 1.12538385e+00 1.51546687e-01 -1.31562066e+00 -3.60628247e-01 7.72610307e-02 -3.51443410e-01 -3.95583175e-02 -1.12341571e+00 -8.99696112e-01 9.57844019e-01 4.14068460e-01 2.74777979e-01 8.31649005e-01 6.29716739e-02 4.38926578e-01 4.16827530e-01 -9.19987187e-02 -1.08144248e+00 -1.68893207e-02 6.07941568e-01 9.45429385e-01 -8.70881855e-01 -1.78035125e-01 -2.42072359e-01 -7.49470353e-01 7.03692019e-01 6.10888958e-01 -7.69671379e-03 1.37702405e-01 3.39056909e-01 2.29867578e-01 8.03937316e-02 -9.27181661e-01 -1.39760345e-01 8.84592682e-02 8.39360654e-01 5.46303272e-01 -1.41824976e-01 3.41575891e-01 5.40337324e-01 -3.95702302e-01 -4.57260013e-01 5.22418737e-01 7.80090094e-01 -6.08155310e-01 -1.00429392e+00 -5.40729046e-01 5.27146637e-01 -2.82225162e-01 -3.66754711e-01 -6.36276007e-01 6.51663303e-01 6.68679029e-02 8.87449026e-01 1.53100610e-01 -4.71488714e-01 5.97952187e-01 5.44479966e-01 3.57983589e-01 -9.13154900e-01 -6.84475780e-01 5.20943627e-02 3.45405072e-01 -2.87025779e-01 1.77036226e-01 -7.93590665e-01 -1.15780151e+00 -2.66752303e-01 -2.05476388e-01 4.90479358e-03 5.16391397e-01 8.19169998e-01 3.01396608e-01 7.91798055e-01 2.59131849e-01 -6.45631790e-01 -7.41311669e-01 -1.20226824e+00 -3.70930523e-01 7.33387291e-01 4.22394305e-01 -4.11863774e-01 -7.69602299e-01 1.56907588e-02]	[10.590235710144043, 8.090202331542969]
9dfb539e-6137-4c6c-b63f-9638e9ebfe47	template-based-named-entity-recognition-using	2106.01760	null	https://arxiv.org/abs/2106.01760v1	https://arxiv.org/pdf/2106.01760v1.pdf	Template-Based Named Entity Recognition Using BART	There is a recent interest in investigating few-shot NER, where the low-resource target domain has different label sets compared with a resource-rich source domain. Existing methods use a similarity-based metric. However, they cannot make full use of knowledge transfer in NER model parameters. To address the issue, we propose a template-based method for NER, treating NER as a language model ranking problem in a sequence-to-sequence framework, where original sentences and statement templates filled by candidate named entity span are regarded as the source sequence and the target sequence, respectively. For inference, the model is required to classify each candidate span based on the corresponding template scores. Our experiments demonstrate that the proposed method achieves 92.55% F1 score on the CoNLL03 (rich-resource task), and significantly better than fine-tuning BERT 10.88%, 15.34%, and 11.73% F1 score on the MIT Movie, the MIT Restaurant, and the ATIS (low-resource task), respectively.	['Yue Zhang', 'Sen yang', 'Jian Liu', 'Yu Wu', 'Leyang Cui']	2021-06-03	null	https://aclanthology.org/2021.findings-acl.161	https://aclanthology.org/2021.findings-acl.161.pdf	findings-acl-2021-8	['few-shot-ner']	['natural-language-processing']	[ 1.26541659e-01 -3.27720523e-01 -1.01241998e-01 -4.37525243e-01 -1.19918609e+00 -8.34562957e-01 3.66308808e-01 -7.81174973e-02 -1.05167937e+00 8.64546418e-01 3.45999062e-01 -7.38045126e-02 2.60876745e-01 -5.95937312e-01 -4.11139578e-01 -3.57322752e-01 4.83294666e-01 3.24992031e-01 4.48293746e-01 -3.72516751e-01 1.78995892e-01 3.48170102e-02 -1.12259543e+00 3.15924495e-01 1.08304846e+00 7.44087994e-01 5.03148735e-01 5.91006696e-01 -2.71618634e-01 7.92027712e-01 -7.30932891e-01 -6.01602197e-01 -1.73757002e-02 -5.91063082e-01 -8.75946939e-01 -4.20072913e-01 1.14738479e-01 9.48451832e-02 -1.74088255e-01 1.18849599e+00 8.25766265e-01 7.16383219e-01 6.05066419e-01 -6.03328109e-01 -6.79883897e-01 8.10248971e-01 -1.36576474e-01 5.19791543e-01 2.47818351e-01 -1.38660356e-01 1.20552969e+00 -1.15093327e+00 6.77784860e-01 8.68079424e-01 4.85950172e-01 8.92148554e-01 -7.16866195e-01 -5.93452215e-01 -3.46813686e-02 1.90326616e-01 -1.39746118e+00 -6.01298332e-01 3.04683834e-01 -2.31047973e-01 1.25498080e+00 1.32323921e-01 2.28885468e-02 1.10516155e+00 1.59676727e-02 7.38634467e-01 9.89479423e-01 -6.78853810e-01 2.55609035e-01 -3.88368592e-03 5.00393927e-01 6.99631751e-01 6.35300055e-02 -8.20837840e-02 -4.63802218e-01 -1.75186172e-02 4.51269269e-01 -2.69691080e-01 -3.05196196e-01 2.81737804e-01 -1.17923355e+00 6.68007851e-01 4.97142076e-02 7.19642043e-01 -4.49519128e-01 -2.55251199e-01 5.82281649e-01 1.29775330e-01 5.28577626e-01 6.25645101e-01 -8.88812780e-01 -4.62475598e-01 -8.40268254e-01 -2.17871130e-01 1.08972645e+00 1.28243601e+00 4.60862815e-01 1.24586508e-01 -5.75664401e-01 1.14744890e+00 5.70780523e-02 5.43371677e-01 9.40276504e-01 -7.20971704e-01 7.29392469e-01 1.49061799e-01 2.59433299e-01 -5.13007045e-01 -3.43071997e-01 -4.04317468e-01 -6.35627508e-01 -6.55388176e-01 3.22636485e-01 -3.54729325e-01 -9.48417664e-01 1.94852209e+00 2.47653276e-01 1.83825895e-01 4.45786178e-01 6.23747170e-01 9.56614017e-01 7.73916602e-01 3.07939142e-01 -3.42928976e-01 1.51754653e+00 -1.23466933e+00 -8.56340945e-01 -3.50988030e-01 8.96161497e-01 -7.42258132e-01 1.35400569e+00 8.68872702e-02 -8.17544639e-01 -5.99000633e-01 -8.48559260e-01 -1.22307852e-01 -3.92066509e-01 3.82496864e-01 4.25749645e-02 6.89832270e-01 -6.63197994e-01 5.48025072e-01 -4.57445562e-01 -5.45360863e-01 -2.14657411e-01 -1.59648061e-01 -1.72101945e-01 -3.45037490e-01 -1.73175251e+00 1.04037535e+00 6.93866134e-01 -8.28060508e-02 -7.53777862e-01 -5.53959787e-01 -9.01803017e-01 3.33138198e-01 3.38020205e-01 -4.09641206e-01 1.53890145e+00 -4.60033953e-01 -1.51714158e+00 6.92011237e-01 -2.19637945e-01 -2.95836776e-01 1.84540972e-01 -3.80704522e-01 -8.16041291e-01 -1.67157892e-02 2.63366520e-01 3.25144172e-01 2.37705812e-01 -5.89955926e-01 -8.05338085e-01 1.76196415e-02 -3.20718586e-02 2.79960930e-01 -4.43823546e-01 4.34224635e-01 -3.69367898e-01 -5.37212729e-01 -3.12012702e-01 -7.57238030e-01 -2.10883543e-01 -8.67545962e-01 -4.04623836e-01 -4.93595272e-01 1.42063037e-01 -8.34168494e-01 1.50417387e+00 -2.20094538e+00 -2.04277292e-01 -2.08652139e-01 -3.66747141e-01 5.05352855e-01 -5.35718381e-01 4.62860554e-01 2.52231266e-02 4.91468638e-01 4.88895699e-02 1.70222372e-02 -9.25417151e-03 -9.84869078e-02 -1.23597488e-01 -8.74606892e-02 -1.20364279e-02 6.16607785e-01 -1.24640441e+00 -5.37394106e-01 -1.93488911e-01 2.42713869e-01 -1.68100908e-01 2.63409287e-01 4.13285978e-02 1.73360988e-01 -5.50984204e-01 3.69651139e-01 1.49478525e-01 -1.42711744e-01 2.51127124e-01 -3.26104432e-01 -3.25584233e-01 5.93908846e-01 -8.72919559e-01 1.83291602e+00 -6.14275634e-01 2.58326322e-01 -4.39756930e-01 -5.71044862e-01 9.56638277e-01 6.76386833e-01 1.60307422e-01 -8.06172967e-01 1.03177205e-01 3.14066499e-01 1.77344292e-01 -5.59361756e-01 7.27134764e-01 -4.04634774e-01 -4.97136533e-01 2.27262303e-01 3.68204832e-01 3.35094661e-01 7.71283567e-01 6.74787313e-02 1.50894344e+00 2.82669127e-01 6.53252184e-01 -1.93275943e-01 4.24395829e-01 1.07588008e-01 9.36811328e-01 8.03784788e-01 -3.17200214e-01 4.93431389e-01 4.59658131e-02 -8.31405893e-02 -9.66235220e-01 -9.05476332e-01 7.21462369e-02 1.36502385e+00 1.10363197e-02 -4.97803688e-01 -8.23658824e-01 -9.62583065e-01 -7.21040845e-01 1.25086558e+00 -2.99806476e-01 -2.14961410e-01 -6.45595849e-01 -5.46166003e-01 8.29127014e-01 4.90010977e-01 5.33928156e-01 -1.19849455e+00 -2.72274494e-01 4.66662824e-01 -7.85606623e-01 -1.23795474e+00 -1.01997817e+00 1.85900122e-01 -7.15745270e-01 -8.32575202e-01 -8.58709574e-01 -8.51331711e-01 2.87414044e-01 2.35326245e-01 1.05226386e+00 -2.97010124e-01 1.70463264e-01 1.82437971e-01 -7.28173673e-01 -1.62446126e-01 -4.02688175e-01 3.60605210e-01 1.09868631e-01 -2.45640963e-01 6.04708612e-01 -1.97465405e-01 -1.26773149e-01 4.34466541e-01 -7.10468709e-01 -1.41311437e-01 6.93775713e-01 1.04140937e+00 6.38197660e-01 2.31836457e-02 8.60528946e-01 -9.92547035e-01 6.63830578e-01 -6.20746195e-01 -2.28416532e-01 6.77764535e-01 -4.63229358e-01 8.18950459e-02 8.51629615e-01 -5.02099693e-01 -1.43866956e+00 1.48877455e-02 -2.77304828e-01 -1.60031185e-01 -2.66289145e-01 8.48542154e-01 -4.70273405e-01 4.86533523e-01 7.92199194e-01 3.45442623e-01 -8.19005609e-01 -7.59783149e-01 2.42691875e-01 8.22941244e-01 3.71563315e-01 -5.50609171e-01 5.70132554e-01 -2.09852606e-01 -5.90259492e-01 -7.61698723e-01 -1.48893499e+00 -8.46645236e-01 -6.51786566e-01 3.15795131e-02 8.97732377e-01 -8.85302305e-01 -1.07307926e-01 1.19947650e-01 -1.45128942e+00 -1.53639913e-01 -2.53775567e-01 7.45686352e-01 -4.58720714e-01 3.86607498e-01 -8.69114876e-01 -7.29165375e-01 -5.62471032e-01 -6.90299690e-01 6.63893282e-01 4.25417036e-01 -2.57420778e-01 -8.34111094e-01 2.81985044e-01 3.35618913e-01 2.28824645e-01 -2.95692146e-01 9.49669242e-01 -1.35034382e+00 -1.73659176e-02 -3.47263604e-01 -5.39761186e-02 4.24417049e-01 1.76739395e-01 -4.15143490e-01 -9.00878668e-01 -3.58343869e-02 1.18747041e-01 -2.45626479e-01 5.34896791e-01 6.91038072e-02 7.36169875e-01 -2.03975335e-01 -9.19379443e-02 7.03592226e-02 1.37772191e+00 5.18090487e-01 7.09167600e-01 2.15309530e-01 5.03317773e-01 5.24093091e-01 1.01643717e+00 3.59764397e-01 2.34049588e-01 5.70487082e-01 -3.30895156e-01 2.10345834e-01 -1.75331607e-01 -4.31757450e-01 5.89241982e-01 1.41310239e+00 1.35211786e-02 -6.47843599e-01 -9.55531836e-01 6.10345006e-01 -1.77082253e+00 -1.16535509e+00 9.51875970e-02 2.18977118e+00 1.07409358e+00 2.09984228e-01 -7.13487044e-02 -2.93200284e-01 1.13995957e+00 4.57847677e-02 -5.28881013e-01 -1.87693030e-01 -6.96470216e-02 1.94876075e-01 3.41133714e-01 2.05717936e-01 -1.12054229e+00 1.16617465e+00 5.58836889e+00 1.22014987e+00 -5.57068884e-01 4.22329932e-01 2.97587246e-01 1.43223107e-01 -6.86986670e-02 -3.23492400e-02 -1.31151891e+00 5.69915473e-01 1.61502492e+00 -5.60560405e-01 2.68791646e-01 8.38484824e-01 1.42965302e-01 2.22811133e-01 -1.00178635e+00 7.07445800e-01 1.78715512e-01 -9.20785546e-01 -8.96611735e-02 -2.16321930e-01 6.68700635e-01 2.28127256e-01 -3.21087986e-01 9.77664053e-01 4.19131100e-01 -6.17583990e-01 6.58684134e-01 6.00169718e-01 7.55266488e-01 -7.49779046e-01 8.95428121e-01 7.97392070e-01 -1.36472750e+00 2.47404665e-01 -5.97053349e-01 2.20539600e-01 3.86373967e-01 5.21052837e-01 -7.60254204e-01 7.00794339e-01 5.01363993e-01 3.99628043e-01 -1.33650273e-01 1.10354924e+00 -4.53496575e-01 8.84854496e-01 -1.97806256e-03 -3.87872994e-01 1.28645301e-01 1.34780973e-01 4.53656435e-01 1.59055281e+00 4.59418416e-01 2.82125950e-01 3.50549906e-01 4.21866745e-01 -5.41920185e-01 5.17807066e-01 -4.19631779e-01 -2.94707507e-01 7.03220904e-01 1.34996176e+00 -5.83479762e-01 -4.58733290e-01 -5.52062213e-01 1.12525952e+00 5.36276400e-01 3.54914457e-01 -9.66620326e-01 -9.78019476e-01 2.72618800e-01 -4.94511038e-01 3.96919757e-01 -1.65232643e-01 1.55572370e-01 -1.50658107e+00 -1.98174253e-01 -7.87580669e-01 4.27567899e-01 -7.46303499e-01 -1.69711447e+00 9.04800296e-01 -2.95732975e-01 -1.33246887e+00 -3.48538429e-01 -4.13622469e-01 -4.86445993e-01 9.05537486e-01 -1.46431375e+00 -7.88356662e-01 9.95317698e-02 1.66788042e-01 9.42120194e-01 -8.46988261e-02 1.02338791e+00 4.92580235e-01 -6.01899981e-01 6.54158354e-01 2.86969662e-01 4.83966708e-01 9.25557911e-01 -1.03140199e+00 5.03646255e-01 1.10939550e+00 2.99707443e-01 6.64924979e-01 5.09060383e-01 -7.93273389e-01 -9.73100960e-01 -1.26632500e+00 1.55979729e+00 -4.46959436e-01 5.64634442e-01 -1.79614201e-01 -8.44647408e-01 5.55368483e-01 1.12810351e-01 -1.12971276e-01 1.02823210e+00 1.66929141e-01 -4.82527256e-01 1.09838121e-01 -1.13554895e+00 7.08554208e-01 1.21416104e+00 -5.84284663e-01 -9.63214397e-01 2.57945210e-01 9.80400860e-01 -2.89265543e-01 -1.08762014e+00 1.93409681e-01 2.76288539e-01 -4.47310030e-01 6.17196679e-01 -8.94876599e-01 3.58937800e-01 -1.71200112e-01 -4.52286810e-01 -1.50958717e+00 -6.58317864e-01 -2.32804656e-01 9.15218368e-02 1.64102817e+00 7.94604540e-01 -1.67004690e-01 3.08558375e-01 6.38871670e-01 -4.85128134e-01 -3.62400740e-01 -8.94446373e-01 -1.34255672e+00 -1.80818308e-02 -3.03077638e-01 4.12808359e-01 9.46765602e-01 7.21395612e-02 9.40088034e-01 -4.13246453e-01 3.68453451e-02 4.02496159e-01 -1.69877917e-01 2.73642600e-01 -1.12776780e+00 -1.59497544e-01 -1.33026809e-01 1.54113531e-01 -1.06019449e+00 3.97576690e-01 -9.74175751e-01 6.46877885e-01 -1.48524404e+00 3.94592822e-01 -2.63053566e-01 -7.76002288e-01 6.42547250e-01 -4.22652215e-01 -3.54538038e-02 2.97869653e-01 2.38431290e-01 -9.81994927e-01 5.77088296e-01 9.25136805e-01 4.82285507e-02 -5.14508896e-02 -7.32660294e-02 -5.96853614e-01 6.51303113e-01 9.03104126e-01 -8.26679349e-01 -2.04196766e-01 -5.06810009e-01 3.02811358e-02 1.87793210e-01 -3.35659355e-01 -1.02226007e+00 3.35915774e-01 -3.70793670e-01 1.51424110e-01 -3.82120192e-01 1.79806724e-01 -4.62962836e-01 -1.33420303e-01 3.39616567e-01 -7.04079270e-01 1.04014424e-03 4.32003289e-02 6.47068977e-01 -1.71584353e-01 -8.11962187e-01 6.84790015e-01 -3.38358283e-01 -1.06278539e+00 2.53107011e-01 -3.74450833e-01 6.13360584e-01 6.58836246e-01 1.68206152e-02 -4.25098747e-01 -1.50124282e-01 -5.48010647e-01 2.76318695e-02 9.02394950e-02 5.25733173e-01 4.82773483e-01 -1.30404401e+00 -8.54141116e-01 -3.30178410e-01 3.15497458e-01 -4.79528695e-01 4.67152834e-01 5.42599678e-01 1.97350606e-01 5.20335257e-01 2.20195390e-02 2.78393216e-02 -1.13077199e+00 4.05507594e-01 1.57519028e-01 -7.11487353e-01 -2.46444523e-01 7.82674015e-01 1.51681006e-01 -6.37729764e-01 -1.54180303e-02 3.76085229e-02 -4.17367876e-01 -1.79469418e-02 8.37866366e-01 5.39370894e-01 1.65332541e-01 -5.61636627e-01 -3.39000016e-01 2.97840804e-01 -2.07165822e-01 -2.90883154e-01 1.07663202e+00 -2.60449708e-01 2.41212010e-01 7.20667541e-01 1.02755725e+00 1.67653188e-01 -7.63148546e-01 -6.03899419e-01 6.01065159e-01 -4.40668464e-02 -1.77360356e-01 -1.17528498e+00 -5.88390887e-01 8.30640793e-01 4.01294500e-01 4.27573062e-02 8.75932574e-01 -9.10498053e-02 1.14763033e+00 6.83253109e-01 5.95374167e-01 -1.28785050e+00 -7.58634647e-03 1.31327462e+00 5.07359087e-01 -9.51820135e-01 -5.86772144e-01 -3.70707989e-01 -7.58471370e-01 9.51519072e-01 7.85629272e-01 1.73213705e-01 2.23859623e-01 -4.60239090e-02 1.90490782e-02 2.38659382e-01 -8.82659495e-01 -4.50577587e-01 3.99889469e-01 4.75985169e-01 8.03535044e-01 -1.15821786e-01 -5.68838716e-01 1.18204665e+00 4.85234223e-02 3.61772329e-02 4.94227886e-01 8.73676002e-01 -9.07297969e-01 -1.06141913e+00 9.32143405e-02 3.26913267e-01 -7.76383042e-01 -6.32862210e-01 -1.26811638e-01 4.97783333e-01 -8.28690827e-02 1.21613872e+00 -2.51606852e-01 -4.45120245e-01 6.39879704e-01 5.53684533e-01 1.90320954e-01 -1.15546095e+00 -6.47878885e-01 9.33552161e-02 5.89647949e-01 -2.43193239e-01 -2.72282273e-01 -3.66718322e-01 -1.36754990e+00 9.83093083e-02 -6.57426298e-01 7.10051596e-01 6.67559803e-01 1.10835516e+00 3.80771339e-01 4.59604532e-01 6.72219217e-01 -3.13263893e-01 -9.47561204e-01 -1.32839835e+00 -6.48965478e-01 2.78280795e-01 -3.23975056e-01 -4.07268673e-01 -2.97140509e-01 1.13556653e-01]	[9.802560806274414, 9.368378639221191]
6219ecbb-513b-44ac-af8c-9468a8d1e24d	real-time-webcam-heart-rate-and-variability	2012.15846	null	https://arxiv.org/abs/2012.15846v1	https://arxiv.org/pdf/2012.15846v1.pdf	Real-time Webcam Heart-Rate and Variability Estimation with Clean Ground Truth for Evaluation	Remote photo-plethysmography (rPPG) uses a camera to estimate a person's heart rate (HR). Similar to how heart rate can provide useful information about a person's vital signs, insights about the underlying physio/psychological conditions can be obtained from heart rate variability (HRV). HRV is a measure of the fine fluctuations in the intervals between heart beats. However, this measure requires temporally locating heart beats with a high degree of precision. We introduce a refined and efficient real-time rPPG pipeline with novel filtering and motion suppression that not only estimates heart rates, but also extracts the pulse waveform to time heart beats and measure heart rate variability. This unsupervised method requires no rPPG specific training and is able to operate in real-time. We also introduce a new multi-modal video dataset, VicarPPG 2, specifically designed to evaluate rPPG algorithms on HR and HRV estimation. We validate and study our method under various conditions on a comprehensive range of public and self-recorded datasets, showing state-of-the-art results and providing useful insights into some unique aspects. Lastly, we make available CleanerPPG, a collection of human-verified ground truth peak/heart-beat annotations for existing rPPG datasets. These verified annotations should make future evaluations and benchmarking of rPPG algorithms more accurate, standardized and fair.	['Jan van Gemert', 'Marian Bittner', 'Amogh Gudi']	2020-12-31	null	null	null	null	['heart-rate-variability']	['medical']	[ 2.06664011e-01 -2.55514145e-01 1.01723485e-02 -3.05602580e-01 -5.24858952e-01 -5.12226224e-01 5.15185259e-02 3.42542864e-02 -8.11068714e-02 7.02387929e-01 4.22741771e-01 5.18533707e-01 1.20327428e-01 -8.69661033e-01 1.36917874e-01 -5.96613526e-01 -3.03913146e-01 1.03737861e-01 -2.09795609e-01 5.08033745e-02 -7.18912333e-02 3.88128877e-01 -1.32844472e+00 -1.18545920e-01 4.91354764e-01 1.05287266e+00 -4.87608135e-01 1.16194022e+00 5.90207398e-01 4.98516947e-01 -5.72459161e-01 -1.91148669e-01 2.64465004e-01 -7.16868401e-01 -3.30540895e-01 -1.67867199e-01 6.05994463e-01 -4.52029526e-01 -4.07920152e-01 4.56338257e-01 1.13701153e+00 -2.19106171e-02 2.74908841e-02 -9.58680987e-01 -1.89299569e-01 6.65180832e-02 -1.41767308e-01 6.88770890e-01 7.64246821e-01 5.88165700e-01 5.25750339e-01 -2.14358747e-01 6.60358429e-01 7.74517298e-01 1.29018438e+00 4.17552173e-01 -1.44642365e+00 -4.05994594e-01 -7.61635125e-01 1.35614395e-01 -1.45113909e+00 -6.50246561e-01 8.65720212e-01 -4.67011929e-01 6.82486713e-01 8.33770633e-01 1.29904580e+00 1.10750186e+00 8.42818916e-02 4.44347365e-03 1.47061455e+00 -7.68132359e-02 1.22440271e-01 4.51269560e-02 8.21480080e-02 5.30763626e-01 1.72850322e-02 1.54851496e-01 -6.68171108e-01 -2.23130152e-01 9.32206035e-01 1.57480597e-01 -7.86044240e-01 2.03987435e-02 -1.48415971e+00 3.48749220e-01 -5.59808202e-02 1.82240516e-01 -5.57034373e-01 1.91379398e-01 6.12415373e-01 1.36951968e-01 3.29562634e-01 2.65951663e-01 -4.05093610e-01 -8.48646462e-01 -1.22472978e+00 1.99928805e-01 1.09200263e+00 3.93105745e-01 4.00149375e-01 -8.27149525e-02 -5.50011635e-01 6.57647789e-01 1.21250719e-01 7.78093159e-01 3.30794692e-01 -1.60480118e+00 4.27412055e-03 3.89489621e-01 1.49154916e-01 -1.31744242e+00 -7.26534605e-01 -3.80481213e-01 -9.66077089e-01 -1.24622092e-01 5.22068858e-01 -2.79518235e-02 -2.39359081e-01 1.63236058e+00 5.27096868e-01 4.42957461e-01 -4.29025143e-01 1.34483933e+00 1.00050604e+00 3.53314698e-01 -3.52949910e-02 -7.99559593e-01 1.64864385e+00 -3.11721593e-01 -8.32406461e-01 2.31384374e-02 5.20239398e-02 -3.89538467e-01 9.58695412e-01 4.13806647e-01 -1.04648876e+00 -7.82285273e-01 -7.55028427e-01 2.07869764e-02 2.52520945e-02 -5.54489531e-03 4.67827588e-01 9.26199973e-01 -7.76907444e-01 1.23373747e+00 -9.10927832e-01 -6.52123451e-01 2.86046207e-01 -2.22256005e-01 -3.20032299e-01 2.43586153e-01 -1.36044657e+00 6.51627481e-01 -1.38683408e-01 3.68292481e-01 -5.44026554e-01 -1.25824642e+00 -7.54257798e-01 -7.09844679e-02 -5.47299534e-02 -8.78218412e-01 7.49869406e-01 -3.53225201e-01 -1.66283667e+00 1.14780545e+00 -1.43947631e-01 -5.28577447e-01 7.64434934e-01 -3.02452236e-01 -6.89072609e-01 8.89892220e-01 -2.45373949e-01 3.44540030e-01 8.59768927e-01 -4.51682508e-01 3.05754602e-01 -3.84021670e-01 -7.02419996e-01 1.53047079e-02 -2.73762979e-02 3.24164927e-02 -3.67513686e-01 -4.44320530e-01 9.36388224e-02 -9.01832461e-01 1.58997923e-01 1.83224931e-01 -1.62746638e-01 4.22004491e-01 3.31684023e-01 -1.09517300e+00 1.46815145e+00 -2.04118109e+00 -1.97633207e-01 6.19555600e-02 5.52863419e-01 2.97192901e-01 4.37594056e-01 4.76607233e-01 4.98854928e-02 2.19238289e-02 -2.00128525e-01 -3.24652314e-01 -8.87406096e-02 1.03966303e-01 -2.26026490e-01 9.60092247e-01 -3.95641476e-01 1.06427562e+00 -8.02997172e-01 -6.34000301e-01 8.06327999e-01 8.93365979e-01 -2.28733435e-01 2.41909683e-01 4.24632400e-01 9.62616086e-01 1.18884750e-01 7.29161084e-01 4.25363958e-01 -5.95216937e-02 1.02646977e-01 -5.60337484e-01 -8.68876800e-02 8.38839933e-02 -9.53520298e-01 1.67640877e+00 -1.39447823e-01 9.52205837e-01 -2.40077659e-01 -5.72708547e-01 1.18075883e+00 6.24097645e-01 8.87628198e-01 -7.20374644e-01 1.57618020e-02 -2.75982201e-01 -3.45006257e-01 -9.19010580e-01 8.11193287e-02 -3.06043476e-01 4.73757535e-02 2.70961612e-01 -1.77275628e-01 -1.12736858e-01 2.02384189e-01 -1.90863311e-02 1.22021973e+00 1.78857729e-01 6.52737021e-01 -2.01109335e-01 4.74027216e-01 -4.28320587e-01 8.11385691e-01 6.65464878e-01 -9.85962808e-01 1.23514652e+00 3.36825460e-01 -7.64227629e-01 -8.47603321e-01 -1.28627467e+00 -3.25402379e-01 3.42833370e-01 -2.18402624e-01 -7.61626959e-01 -4.69974816e-01 -5.98298311e-02 1.49407104e-01 1.84719786e-01 -7.36671507e-01 3.34030837e-02 -5.08568227e-01 -7.71726906e-01 8.66730928e-01 4.65957582e-01 7.37677693e-01 -1.20462441e+00 -1.16384840e+00 2.47908577e-01 -7.03269064e-01 -1.35453153e+00 -2.64228672e-01 -5.03959537e-01 -1.11800826e+00 -1.33113527e+00 -6.11528397e-01 1.53235748e-01 5.93895912e-02 -6.67146891e-02 1.49367476e+00 -5.94341196e-02 -1.05310893e+00 8.81034613e-01 -1.51608020e-01 -1.39510766e-01 8.08867514e-02 -3.65476698e-01 1.21825881e-01 -8.31383690e-02 3.23248446e-01 -1.08091283e+00 -1.27122307e+00 2.67795950e-01 -9.89765897e-02 -1.86894506e-01 -7.61135444e-02 1.36305571e-01 8.40717316e-01 -2.87406713e-01 5.06787002e-01 -4.78262722e-01 4.57981050e-01 -5.44048585e-02 -2.89514333e-01 -2.27691934e-01 -5.69558799e-01 -6.81011736e-01 4.37847018e-01 -9.18502659e-02 -5.90303302e-01 -1.47602007e-01 -1.21260881e-02 -5.44896781e-01 -3.62769604e-01 -3.34930466e-03 3.64640057e-01 2.31783524e-01 9.09683764e-01 2.89448410e-01 2.50231087e-01 -2.95571297e-01 2.97356635e-01 3.58189374e-01 1.35582542e+00 -2.98272312e-01 4.65685606e-01 8.79812598e-01 2.38744318e-01 -1.19944048e+00 -7.99649239e-01 -8.33021104e-01 -7.53574252e-01 -6.60306513e-01 1.03755093e+00 -1.08355629e+00 -1.27430439e+00 4.92608190e-01 -5.15200257e-01 -3.16084146e-01 -6.21584415e-01 5.67376554e-01 -8.45630884e-01 6.05601013e-01 -8.15199971e-01 -1.04529428e+00 -9.60684717e-01 -1.58599049e-01 9.31457758e-01 4.33299631e-01 -8.09516251e-01 -1.04810941e+00 7.65072703e-01 6.96172059e-01 6.99895442e-01 1.15885174e+00 -6.81407228e-02 2.65598688e-02 -9.60227549e-02 -3.06359410e-01 6.88054413e-02 3.64465952e-01 7.00448826e-02 2.89186928e-02 -1.31388080e+00 -2.71249503e-01 2.51812071e-01 -1.11614376e-01 6.35489106e-01 6.21799767e-01 9.08946335e-01 -1.60485134e-01 3.18980739e-02 9.15486395e-01 1.37241018e+00 -4.34039086e-01 1.20298743e+00 3.87382023e-02 5.34344733e-01 4.26697791e-01 3.61296237e-01 8.23693275e-01 3.58074456e-01 7.10081995e-01 1.39176100e-01 -1.31643385e-01 -1.61715806e-01 -6.00689836e-02 3.40101540e-01 6.23278618e-01 -8.11408639e-01 4.00537342e-01 -5.98399401e-01 2.45072544e-01 -1.49964583e+00 -1.47875273e+00 -4.57073987e-01 2.45895553e+00 9.41448629e-01 -2.43103132e-01 5.56638956e-01 4.51337487e-01 7.06111491e-01 4.16619480e-01 -3.07187974e-01 -3.02661031e-01 2.48225015e-02 4.19969767e-01 3.30044508e-01 1.18139677e-01 -1.15408885e+00 1.75785437e-01 6.83021212e+00 -2.80732632e-01 -1.25742579e+00 1.01608103e-02 4.15164918e-01 -5.04974246e-01 2.55774140e-01 -1.37581408e-01 -3.83880973e-01 6.52296245e-01 1.36585355e+00 -1.04397863e-01 5.67332149e-01 5.67923248e-01 8.16958427e-01 -2.96270698e-01 -9.41538095e-01 1.54928303e+00 1.17209502e-01 -1.18540871e+00 -1.00158119e+00 -8.05998817e-02 1.04002409e-01 -4.60405387e-02 -5.16306460e-01 6.60870597e-02 -6.79570198e-01 -8.75608742e-01 7.65746385e-02 1.23511922e+00 9.94615376e-01 -4.60738122e-01 3.86237592e-01 -6.60346821e-02 -1.32347298e+00 2.20335484e-01 -2.58641094e-01 -2.85799652e-01 3.67970973e-01 1.28721368e+00 -5.34380078e-01 4.18818921e-01 8.12628627e-01 1.11254704e+00 -5.91321468e-01 1.09413850e+00 -3.91664803e-01 7.03430712e-01 -4.08876926e-01 5.57117164e-01 -8.82917523e-01 -2.82081008e-01 8.11396897e-01 1.24417043e+00 3.15283269e-01 4.21862751e-01 -1.45627698e-02 1.10523498e+00 3.58597130e-01 -2.02029441e-02 -4.88000870e-01 -4.13910188e-02 4.05518413e-01 1.82866216e+00 -5.74652553e-01 -4.22628611e-01 -2.18644366e-01 8.33794057e-01 -2.10286975e-01 6.97894022e-02 -1.00704539e+00 -3.14837515e-01 7.98018336e-01 4.35785741e-01 -2.42109314e-01 -2.53463626e-01 -2.38345534e-01 -1.31858909e+00 5.79273067e-02 -5.60577631e-01 5.97831607e-01 -1.01750445e+00 -1.07879663e+00 2.27323070e-01 -2.03516379e-01 -1.25814164e+00 -2.73671478e-01 1.54611260e-01 -8.42345417e-01 8.78711045e-01 -1.35563338e+00 -5.92638910e-01 -1.18174148e+00 6.46852851e-01 -6.01257458e-02 6.39892340e-01 1.11785388e+00 4.22602803e-01 -7.38907158e-01 2.49511942e-01 -7.26325035e-01 1.58252478e-01 1.14947915e+00 -1.31227589e+00 1.18753038e-01 6.91770852e-01 -1.52187273e-01 5.97106934e-01 8.54816139e-01 -5.12215972e-01 -1.59588385e+00 -1.01770341e+00 7.68277943e-01 -7.62280941e-01 2.67026335e-01 -1.06860355e-01 -8.13507915e-01 4.69378233e-01 -1.32866800e-01 6.36600792e-01 8.86418939e-01 -4.49727215e-02 4.40568328e-02 -5.43781877e-01 -1.35419512e+00 -2.75874473e-02 8.47329676e-01 -6.54027164e-01 -7.22377479e-01 3.58910747e-02 1.20895937e-01 -6.25742733e-01 -1.65206993e+00 3.79933208e-01 1.12785912e+00 -1.47973526e+00 1.14308012e+00 1.03521273e-01 1.70652464e-01 -3.35777640e-01 2.62267560e-01 -9.85897124e-01 -1.80755317e-01 -1.00084496e+00 -4.89321858e-01 1.31701422e+00 -4.62878257e-01 -7.39204347e-01 5.63120782e-01 8.72975528e-01 1.11533053e-01 -3.11451763e-01 -6.85041964e-01 -5.51208138e-01 -7.19322681e-01 -5.28720975e-01 -1.35169774e-02 1.08271420e+00 2.99657077e-01 -8.66625831e-02 -6.09530210e-01 -2.36170087e-02 9.60982323e-01 3.66995722e-01 9.08102691e-01 -1.43205166e+00 -3.08166027e-01 2.32238188e-01 -6.63926840e-01 -5.58536723e-02 -4.26302999e-01 -5.30654430e-01 -2.11971328e-01 -1.33499086e+00 2.19105169e-01 4.53849956e-02 -3.27750146e-01 3.71855676e-01 -1.19324453e-01 1.00310493e+00 2.23477915e-01 2.93125451e-01 -4.51591045e-01 1.48625433e-01 1.08093977e+00 4.35246259e-01 -6.95258379e-01 -8.87096897e-02 -3.38332236e-01 6.73649430e-01 7.68466771e-01 -2.11939290e-01 -2.70921737e-01 5.60150146e-01 2.81467736e-01 5.55269003e-01 8.76998305e-01 -1.46250975e+00 -1.83486566e-01 1.96836174e-01 7.88797438e-01 -5.47811270e-01 4.18860525e-01 -4.29797202e-01 7.20303178e-01 6.34674609e-01 -5.47346584e-02 -8.67734179e-02 -2.26639137e-02 3.87759835e-01 2.27182321e-02 4.28060204e-01 9.72267389e-01 -4.78710264e-01 -3.72697473e-01 2.55814821e-01 -1.12737328e-01 3.56783628e-01 7.10147917e-01 -3.73924941e-01 -6.02932334e-01 -4.95146692e-01 -1.11036623e+00 8.40933844e-02 5.49592972e-01 1.64291635e-01 4.88538831e-01 -1.29096127e+00 -7.38275051e-01 2.10469201e-01 6.63456246e-02 -5.38268030e-01 7.55269468e-01 1.58846653e+00 -7.32733309e-01 2.60238886e-01 -4.71640408e-01 -8.99610698e-01 -1.29712713e+00 3.73236626e-01 6.37897015e-01 -1.03822812e-01 -1.31785274e+00 1.75111935e-01 -4.83196676e-01 3.98239121e-02 -1.22962505e-01 -2.74858207e-01 -3.03807378e-01 3.23659450e-01 8.93129349e-01 9.55989897e-01 -4.62051332e-02 -3.38755429e-01 -4.99651104e-01 6.73101485e-01 7.59978831e-01 4.30734530e-02 1.01400113e+00 -7.11312473e-01 -2.26647481e-01 6.31570935e-01 1.00153303e+00 1.30098149e-01 -1.22687340e+00 2.39109412e-01 -5.72788239e-01 -5.91936827e-01 -5.00084832e-02 -7.77056456e-01 -1.20145643e+00 8.07924271e-01 9.54525232e-01 3.72593433e-01 1.41447067e+00 -5.47827363e-01 8.99125099e-01 -2.00757757e-01 1.80330351e-01 -1.06132197e+00 -8.20873454e-02 -2.09108219e-01 7.20988929e-01 -8.72740507e-01 4.04637218e-01 -4.67625290e-01 -5.45146048e-01 1.19506323e+00 1.71055019e-01 -7.47021064e-02 4.66983974e-01 1.33117348e-01 2.74561644e-01 -1.54359579e-01 -5.82605004e-01 -1.78926528e-01 1.32172570e-01 7.42480934e-01 5.72873116e-01 1.60531029e-02 -4.93705779e-01 2.41417512e-01 -5.05290866e-01 5.96807718e-01 5.40698946e-01 6.49908245e-01 -2.80049384e-01 -4.61730778e-01 -3.55565816e-01 3.27929854e-01 -6.90418661e-01 1.33973673e-01 -5.76722585e-02 5.75607359e-01 -1.25356942e-01 9.51398253e-01 1.67313926e-02 -9.39623192e-02 3.22720826e-01 4.81025398e-01 5.98774254e-01 -2.72037476e-01 -6.51595592e-01 -2.24764589e-02 2.55024940e-01 -1.17187297e+00 -7.49256730e-01 -6.76722050e-01 -1.02695024e+00 -4.48356181e-01 3.67306203e-01 -2.56777704e-01 5.00144064e-01 6.58001721e-01 5.33291101e-01 5.44508874e-01 5.98193049e-01 -7.17151999e-01 -2.20048800e-02 -7.89175868e-01 -7.98299909e-01 7.60957122e-01 2.50265747e-01 -1.55401632e-01 -5.85753858e-01 3.93004477e-01]	[13.907084465026855, 2.8632638454437256]
a979fb68-eb20-456a-8897-fcc28e88f507	connectivity-optimized-nested-graph-networks	2302.14102	null	https://arxiv.org/abs/2302.14102v1	https://arxiv.org/pdf/2302.14102v1.pdf	Connectivity Optimized Nested Graph Networks for Crystal Structures	Graph neural networks (GNNs) have been applied to a large variety of applications in materials science and chemistry. Here, we recapitulate the graph construction for crystalline (periodic) materials and investigate its impact on the GNNs model performance. We suggest the asymmetric unit cell as a representation to reduce the number of atoms by using all symmetries of the system. With a simple but systematically built GNN architecture based on message passing and line graph templates, we furthermore introduce a general architecture (Nested Graph Network, NGN) that is applicable to a wide range of tasks and systematically improves state-of-the-art results on the MatBench benchmark datasets.	['Pascal Friederich', 'Jan Stühmer', 'Patrick Reiser', 'Robin Ruff']	2023-02-27	null	null	null	null	['graph-construction']	['graphs']	[ 5.02349377e-01 3.65921229e-01 -3.27445835e-01 1.31851003e-01 2.61438370e-01 -1.26146808e-01 6.97067201e-01 1.51985958e-01 -7.74707720e-02 7.73785174e-01 8.02076161e-02 -7.46331215e-01 -1.95636258e-01 -1.27636015e+00 -8.56824577e-01 -9.76486087e-01 -3.04145604e-01 6.49494946e-01 3.90274793e-01 -5.18641174e-01 3.23694170e-01 7.50661254e-01 -1.22427714e+00 4.78807181e-01 3.51029128e-01 7.33684778e-01 1.01936378e-01 5.06251335e-01 -2.57758200e-02 8.04037929e-01 -2.51924455e-01 -3.43542635e-01 2.65492558e-01 -4.64280367e-01 -7.97327757e-01 -8.44968259e-02 2.92248458e-01 2.21372843e-01 -8.52694094e-01 8.58228266e-01 6.19012177e-01 1.93971783e-01 8.77481341e-01 -8.95276129e-01 -8.18236053e-01 1.01298451e+00 -2.32287079e-01 -1.13020629e-01 8.44045579e-02 2.78392434e-01 1.12171078e+00 -5.11043191e-01 1.12847924e+00 1.12026227e+00 6.02562368e-01 6.11622214e-01 -1.35273933e+00 -3.12350303e-01 1.12699173e-01 3.80116075e-01 -1.21135044e+00 -1.78064167e-01 8.94221544e-01 -2.17079654e-01 1.69379580e+00 -2.29593553e-02 8.80837500e-01 1.07124925e+00 7.50509679e-01 1.00167707e-01 7.86050022e-01 -4.56460327e-01 3.53247613e-01 -8.35984647e-01 1.43088862e-01 8.37719321e-01 8.10983479e-01 -1.74092174e-01 -4.86175418e-01 -3.97149511e-02 8.40892613e-01 -5.00547811e-02 -1.71043158e-01 -6.75730467e-01 -1.00349474e+00 9.75946844e-01 9.11465764e-01 4.08719212e-01 -2.99315125e-01 6.40825152e-01 4.89816368e-01 2.88237959e-01 2.74216801e-01 8.79107177e-01 -3.70282531e-02 4.22776222e-01 -5.31637847e-01 2.80353248e-01 1.09449923e+00 9.59876001e-01 5.84643066e-01 4.78445292e-01 -4.15564984e-01 5.83859980e-01 1.50912076e-01 1.21320188e-01 3.63710299e-02 -4.97342885e-01 4.65601534e-01 7.93801844e-01 -5.89386880e-01 -9.68390703e-01 -8.81904364e-01 -5.40040851e-01 -1.37795174e+00 -1.18123807e-01 2.55094200e-01 2.84579873e-01 -1.21344876e+00 1.32640934e+00 7.31931701e-02 -1.71835646e-01 -5.38830906e-02 4.50919747e-01 1.26465857e+00 7.56699800e-01 -2.60939956e-01 -6.77024797e-02 9.43816185e-01 -1.29176259e+00 -4.89438534e-01 -7.27539212e-02 8.70914519e-01 -2.79306203e-01 6.89654410e-01 5.44476509e-01 -1.15260601e+00 -2.56180227e-01 -1.30372167e+00 -1.95440456e-01 -7.98888326e-01 -3.89690697e-01 1.11693108e+00 5.80543041e-01 -1.47421539e+00 1.20771492e+00 -8.52035284e-01 -4.92108077e-01 3.86958838e-01 8.37023079e-01 -4.73992556e-01 -2.86437333e-01 -9.58428562e-01 5.31267524e-01 8.59448075e-01 2.74445057e-01 -6.62169993e-01 -1.76689193e-01 -9.14011776e-01 1.34491026e-01 4.86497253e-01 -1.01900220e+00 8.03698897e-01 -4.83431965e-02 -1.52973306e+00 5.81280231e-01 2.59572864e-01 -7.39617348e-01 1.76911905e-01 4.94314373e-01 -2.82082826e-01 1.11378334e-01 -4.64831531e-01 5.86123765e-01 5.36107361e-01 -8.84727538e-01 3.83726865e-01 -1.65083110e-02 -1.83796108e-01 -1.04626767e-01 -9.68358740e-02 -3.43179226e-01 -4.33492184e-01 -6.01063907e-01 3.55710685e-01 -1.03730011e+00 -4.98062938e-01 -6.28350317e-01 -8.83235931e-01 -1.84483320e-01 5.75940669e-01 -2.07447395e-01 1.29748392e+00 -1.36574829e+00 3.51847261e-01 6.09463692e-01 7.70842791e-01 2.79393345e-01 -3.23631525e-01 1.00990248e+00 -3.34878355e-01 2.01191172e-01 -3.17382693e-01 6.55996799e-02 6.81854086e-03 2.40146875e-01 2.85645276e-01 3.93216103e-01 8.35469961e-02 1.36541724e+00 -5.72362900e-01 1.96842358e-01 1.46251395e-01 3.95215631e-01 -8.54268730e-01 -6.97144344e-02 -7.20477581e-01 1.95020229e-01 -2.59590626e-01 5.18000484e-01 6.41149342e-01 -8.94527197e-01 6.39141262e-01 -1.61971837e-01 5.42760603e-02 6.74641073e-01 -9.21924412e-01 1.47587049e+00 1.78586602e-01 3.07600647e-01 -2.69089609e-01 -1.13176894e+00 1.04457712e+00 -1.25378668e-01 4.44909900e-01 -9.20346797e-01 1.24589287e-01 4.17639241e-02 7.29947567e-01 -2.12377131e-01 2.95990914e-01 4.49775606e-02 2.72468805e-01 5.70621490e-01 2.28473648e-01 -1.43060058e-01 7.30221450e-01 3.07381779e-01 1.55336487e+00 -1.05022922e-01 4.74479795e-01 -6.68915749e-01 5.64213812e-01 -1.47094548e-01 8.27836692e-02 9.62679505e-01 3.31337273e-01 5.99389672e-01 9.21689093e-01 -9.11913455e-01 -1.34477532e+00 -7.37854004e-01 3.69317710e-01 9.18624043e-01 -2.15587914e-01 -1.09332490e+00 -7.12083042e-01 -3.53417575e-01 -1.36067227e-01 3.40647310e-01 -5.53269923e-01 -4.27294552e-01 -8.15813005e-01 -1.14966238e+00 2.77361274e-01 4.14146364e-01 4.11648422e-01 -1.42757642e+00 -1.74712725e-02 4.38745171e-01 5.46341181e-01 -1.15844083e+00 -8.19665715e-02 5.08743882e-01 -7.30187714e-01 -1.07099342e+00 -2.82248616e-01 -7.72987664e-01 6.86027169e-01 3.54643762e-01 1.46570778e+00 5.77263117e-01 -1.93161294e-01 7.58964419e-02 -2.73105264e-01 -2.90572196e-02 -7.26420820e-01 7.21914411e-01 -3.64336744e-02 -2.85981685e-01 -1.18128834e-02 -6.36460304e-01 -4.49837714e-01 -3.01487558e-02 -1.02175486e+00 4.25975561e-01 4.55438912e-01 7.98043251e-01 5.22044301e-01 8.56283680e-02 2.92878360e-01 -1.39019608e+00 7.23418176e-01 -2.65794456e-01 -5.19109905e-01 1.27425253e-01 -7.82353938e-01 5.24938822e-01 8.88315976e-01 -7.81042948e-02 -3.33107322e-01 -2.39008963e-01 -3.72932732e-01 2.85620186e-02 2.77304679e-01 6.00043356e-01 -1.68624952e-01 -6.19100332e-01 4.63394076e-01 -3.11684534e-02 -5.01450412e-02 -1.20508961e-01 3.12593400e-01 2.34265383e-02 1.24667197e-01 -7.92732656e-01 6.36335909e-01 3.16353410e-01 9.53338146e-01 -1.07499719e+00 -3.22193205e-01 -4.22967859e-02 -6.59016788e-01 -8.27868730e-02 7.96444952e-01 -4.56789643e-01 -1.01080120e+00 6.09856606e-01 -1.23202109e+00 -6.28164113e-01 6.11619605e-03 1.62936002e-01 -5.22559047e-01 4.22561914e-01 -9.97127175e-01 -2.13055849e-01 -6.60067797e-01 -1.39042866e+00 7.14129210e-01 -4.57815193e-02 -4.00516391e-02 -1.21098256e+00 -1.64617836e-01 -1.28874496e-01 6.26737416e-01 5.13902664e-01 1.69021642e+00 -7.13119447e-01 -1.01195014e+00 1.92737117e-01 -2.82263428e-01 1.03147410e-01 1.75524756e-01 -2.79920753e-02 -5.80821753e-01 -4.80057418e-01 -2.88379729e-01 -5.13220057e-02 1.31594419e+00 5.10332525e-01 1.23056710e+00 -4.41255093e-01 -4.63778585e-01 7.56895304e-01 1.52049077e+00 8.65277946e-02 1.11393929e+00 4.20561522e-01 1.43658781e+00 3.14324230e-01 -6.00538909e-01 1.06110744e-01 1.32974043e-01 3.75896871e-01 7.33992159e-01 -9.39785987e-02 -3.28406543e-01 -1.30997062e-01 1.82400912e-01 1.14175224e+00 -4.28895950e-01 -9.38477278e-01 -1.14130592e+00 -1.44484594e-01 -1.80969048e+00 -7.40240872e-01 -4.04882520e-01 1.95484412e+00 3.86786938e-01 5.15392542e-01 4.90266681e-02 -2.49126535e-02 8.69083405e-01 6.63847983e-01 -6.00063562e-01 -6.02760434e-01 -3.20226938e-01 5.77500105e-01 9.07743990e-01 2.62148380e-01 -7.02276170e-01 1.17791045e+00 7.73716927e+00 7.79137671e-01 -1.16614902e+00 -3.70838165e-01 6.84953630e-01 1.85942411e-01 -3.76096189e-01 -5.76001965e-02 -7.69381523e-01 1.32181197e-01 1.00918233e+00 1.34146065e-01 8.19846213e-01 4.46911514e-01 -8.09263885e-02 3.43738854e-01 -1.21771932e+00 8.73536170e-01 1.87858380e-02 -2.20795321e+00 7.15556026e-01 2.24426359e-01 9.15568173e-01 3.01922381e-01 -2.04508498e-01 1.68554619e-01 2.10751697e-01 -1.29828072e+00 3.44561934e-01 1.82255939e-01 8.61615181e-01 -6.29815102e-01 4.87841636e-01 -1.97108716e-01 -1.28234661e+00 2.18539730e-01 -3.85234714e-01 -4.41910088e-01 -8.55914727e-02 4.20954108e-01 -1.05210853e+00 8.27923417e-01 3.78144354e-01 7.55992174e-01 -7.58534193e-01 8.70478511e-01 -1.71587944e-01 6.43152952e-01 -2.62552977e-01 -3.86217654e-01 5.56788564e-01 -6.35512531e-01 2.73987293e-01 1.07200909e+00 2.33365878e-01 -1.94683284e-01 1.08233970e-02 9.52540874e-01 -5.84887326e-01 -6.21046573e-02 -1.03888845e+00 -3.73996109e-01 1.46389395e-01 9.71839070e-01 -1.36308384e+00 -1.10339291e-01 -4.63851690e-01 4.63042319e-01 5.62907159e-01 5.14314413e-01 -3.51929218e-01 -2.45088488e-01 1.73755363e-01 5.46269655e-01 5.90786040e-01 -6.67762637e-01 -1.13249622e-01 -8.14906955e-01 -1.73775896e-01 -8.26797485e-01 2.85340995e-01 -7.16786742e-01 -1.07017756e+00 5.65047085e-01 -1.39244571e-01 -7.19836473e-01 -1.89875782e-01 -1.33433795e+00 -8.06948721e-01 3.46308053e-01 -1.43700027e+00 -1.04957950e+00 -1.49562985e-01 1.95203811e-01 -1.79924458e-01 -2.20282078e-01 6.64707541e-01 3.18069384e-02 -6.17076397e-01 2.28075609e-01 2.80233920e-01 4.96409014e-02 3.07051778e-01 -1.13054776e+00 1.22313118e+00 7.09817767e-01 -1.16736241e-01 7.56482005e-01 6.87008202e-01 -9.19769526e-01 -2.01216912e+00 -1.36905468e+00 4.90307271e-01 -2.36804392e-02 7.94072926e-01 -8.47550154e-01 -9.05752480e-01 6.59228861e-01 3.19909036e-01 -6.00716956e-02 3.45159024e-01 -1.66006237e-02 -3.89418036e-01 4.28525247e-02 -8.95994186e-01 9.33095396e-01 1.59433556e+00 -3.80892575e-01 2.48098552e-01 8.38321626e-01 1.07602942e+00 -5.19069791e-01 -8.92075598e-01 5.21370649e-01 2.28565589e-01 -1.03398669e+00 8.63453865e-01 -7.96828628e-01 5.26246965e-01 -2.37350278e-02 -4.05943766e-02 -1.07183814e+00 -8.13636303e-01 -1.10064673e+00 -3.20517778e-01 5.89255333e-01 4.77191061e-01 -9.50773895e-01 1.06445456e+00 2.35780418e-01 -4.54580396e-01 -1.10481524e+00 -7.82948017e-01 -8.80685747e-01 7.14250207e-02 -1.74529463e-01 7.36746788e-01 6.85875952e-01 -2.01213866e-01 7.91322231e-01 -2.76663452e-01 -2.04913661e-01 3.99706066e-01 -2.85689272e-02 6.62721694e-01 -1.33916748e+00 -1.79448590e-01 -6.39028370e-01 -5.58704972e-01 -9.01665449e-01 1.46635577e-01 -1.49718833e+00 -4.13188815e-01 -1.88234031e+00 1.11777700e-01 -8.21735859e-02 -3.50378513e-01 3.89309347e-01 3.14120561e-01 2.31515765e-01 2.40192220e-01 -6.20581470e-02 -8.20143521e-01 5.68636060e-01 1.51720667e+00 -3.85699004e-01 -1.39612079e-01 -4.38094974e-01 -8.15694034e-01 2.91576058e-01 7.04715669e-01 -4.42003876e-01 -1.94938540e-01 -4.21223611e-01 8.76503825e-01 -2.28845879e-01 8.38856772e-02 -1.20378733e+00 3.50952327e-01 1.41792536e-01 1.23308994e-01 -5.80275118e-01 1.21508017e-01 -5.58910608e-01 2.76477337e-01 7.88640797e-01 -2.64552515e-02 4.01248813e-01 1.82539254e-01 4.79474992e-01 2.36389399e-01 -2.44921163e-01 6.10583961e-01 -4.29423600e-01 -2.95129091e-01 6.60336554e-01 -2.87320256e-01 -3.31863761e-01 6.39674425e-01 -2.54392743e-01 -7.99052715e-01 -1.42624021e-01 -5.81172168e-01 -1.34260599e-02 7.60451555e-01 9.03085619e-02 4.31019306e-01 -1.41133821e+00 -4.28771496e-01 5.23599327e-01 4.91109900e-02 1.66900888e-01 5.63550368e-02 4.51745450e-01 -1.13540292e+00 8.24530959e-01 -3.13677639e-01 -5.04785240e-01 -7.48968422e-01 6.34961665e-01 3.34291577e-01 -7.04641402e-01 -6.99442804e-01 5.17110527e-01 1.28347695e-01 -5.34351349e-01 -7.25499243e-02 -6.91975653e-01 -5.65545037e-02 -4.25446242e-01 7.53483847e-02 5.03469646e-01 5.96679568e-01 -3.15202236e-01 -7.78381675e-02 4.55485374e-01 -4.09157127e-01 5.95104575e-01 1.65628338e+00 3.83012474e-01 -6.15477920e-01 2.42035970e-01 9.86217856e-01 -3.36135298e-01 -7.61974990e-01 -1.36365905e-01 -7.90634304e-02 4.77150589e-01 -2.89176852e-01 -1.63577214e-01 -1.07907593e+00 5.84098577e-01 1.31890267e-01 6.46144748e-01 6.56774223e-01 1.39558539e-02 7.37889290e-01 1.13951361e+00 2.58964866e-01 -9.89371538e-01 1.79089069e-01 9.56858754e-01 8.35640192e-01 -7.57029951e-01 4.24215943e-01 -6.31178260e-01 -1.12062082e-01 1.38825965e+00 4.80384350e-01 -3.04619402e-01 5.62340379e-01 1.44329235e-01 -7.11627603e-01 -8.23500335e-01 -6.37524664e-01 -4.14370261e-02 1.97881803e-01 6.46358728e-01 4.45700794e-01 1.06542557e-01 -2.69209713e-01 1.61028057e-01 -2.51800507e-01 -3.35190415e-01 7.17055082e-01 8.95675182e-01 -4.21554506e-01 -1.35212898e+00 1.20479371e-02 8.25099230e-01 -1.50988609e-01 -4.72983122e-01 -5.66213191e-01 8.93854678e-01 -1.87347934e-01 5.64850211e-01 -1.36432081e-01 -3.39177847e-01 1.08443029e-01 -1.28065109e-01 8.40228558e-01 -6.95152223e-01 -4.59827840e-01 -2.67117113e-01 3.49504828e-01 -5.23381889e-01 -5.59982061e-01 -1.39002800e-01 -1.22559798e+00 -6.63160384e-01 -2.12838501e-01 -1.04387991e-01 4.14164811e-01 8.33567977e-01 6.11232400e-01 8.68843019e-01 1.68692172e-01 -1.10018444e+00 1.47365302e-01 -8.93994987e-01 -7.05258191e-01 2.69424856e-01 5.26302382e-02 -5.32292366e-01 -5.16901612e-02 -4.17980254e-01]	[6.447460651397705, 5.976089000701904]
abc57a6e-91c0-4602-b768-c367e3a00a1e	an-fpga-based-on-device-reinforcement	2005.04646	null	https://arxiv.org/abs/2005.04646v4	https://arxiv.org/pdf/2005.04646v4.pdf	An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning	DQN (Deep Q-Network) is a method to perform Q-learning for reinforcement learning using deep neural networks. DQNs require a large buffer and batch processing for an experience replay and rely on a backpropagation based iterative optimization, making them difficult to be implemented on resource-limited edge devices. In this paper, we propose a lightweight on-device reinforcement learning approach for low-cost FPGA devices. It exploits a recently proposed neural-network based on-device learning approach that does not rely on the backpropagation method but uses OS-ELM (Online Sequential Extreme Learning Machine) based training algorithm. In addition, we propose a combination of L2 regularization and spectral normalization for the on-device reinforcement learning so that output values of the neural network can be fit into a certain range and the reinforcement learning becomes stable. The proposed reinforcement learning approach is designed for PYNQ-Z1 board as a low-cost FPGA platform. The evaluation results using OpenAI Gym demonstrate that the proposed algorithm and its FPGA implementation complete a CartPole-v0 task 29.77x and 89.40x faster than a conventional DQN-based approach when the number of hidden-layer nodes is 64.	['Mineto Tsukada', 'Hiroki Matsutani', 'Hirohisa Watanabe']	2020-05-10	null	null	null	null	['l2-regularization']	['methodology']	[-3.79574895e-01 -1.93553850e-01 -1.21430464e-01 -2.58552909e-01 1.46250561e-01 2.88743735e-03 -3.20634395e-02 7.43149519e-02 -8.69112849e-01 6.88449740e-01 -8.08610618e-01 -5.17666280e-01 -1.18972778e-01 -8.88305366e-01 -7.83342659e-01 -5.23130953e-01 2.63050832e-02 1.66663826e-01 2.62205482e-01 -5.56216896e-01 3.02670568e-01 5.54752588e-01 -1.42241728e+00 -4.47384194e-02 6.85846806e-01 1.35329485e+00 1.92649618e-01 8.18173468e-01 -6.39107004e-02 1.07944155e+00 -6.40820205e-01 5.73597848e-02 5.16107261e-01 -2.65278727e-01 4.33537699e-02 -5.10916054e-01 9.32181850e-02 -4.09630567e-01 -1.04346551e-01 9.64366674e-01 9.42995071e-01 8.70159343e-02 4.28600103e-01 -1.29353011e+00 -2.53015533e-02 4.52194214e-01 -6.12578332e-01 3.97998393e-01 -1.75557867e-01 3.51895064e-01 3.14413995e-01 -6.67315185e-01 2.59445399e-01 8.30278695e-01 9.63010073e-01 4.59292382e-01 -8.63659322e-01 -1.05630875e+00 -2.96367735e-01 2.23538220e-01 -1.19620049e+00 -1.46987094e-02 8.47389519e-01 4.58393432e-02 1.56134689e+00 -2.06854001e-01 1.09224498e+00 5.27500749e-01 7.81541884e-01 5.11182785e-01 1.02375782e+00 -5.50800741e-01 1.00953531e+00 1.11346982e-01 -9.91254747e-02 7.84878790e-01 2.44433686e-01 3.78136009e-01 -5.90585351e-01 5.91959320e-02 9.98736084e-01 6.01455644e-02 3.41490269e-01 -8.90970901e-02 -5.90654731e-01 8.74104798e-01 6.86222553e-01 2.48885736e-01 -5.32069385e-01 6.21646166e-01 8.47286582e-01 6.27407253e-01 1.93368584e-01 3.83902401e-01 -6.38754129e-01 -2.93088555e-01 -1.11980796e+00 2.57753462e-01 7.36875057e-01 7.63557613e-01 7.09666073e-01 9.70822334e-01 3.50584894e-01 6.00409389e-01 3.64093155e-01 5.03931403e-01 9.62152302e-01 -5.60163975e-01 2.47424945e-01 7.00975478e-01 -1.12666391e-01 -7.17466772e-01 -8.82714570e-01 -6.97341919e-01 -9.27167594e-01 1.25114536e+00 1.74701437e-01 -8.36338997e-01 -7.26065159e-01 1.20426381e+00 4.73759681e-01 2.82087654e-01 3.70964170e-01 9.25685048e-01 5.94513178e-01 8.87778759e-01 6.88381121e-02 -1.58806637e-01 9.09031630e-01 -9.97407496e-01 -6.44726455e-01 -5.96337952e-02 7.00216591e-01 -7.09229052e-01 9.48116958e-01 8.22319746e-01 -9.91793811e-01 -9.71370816e-01 -1.90422201e+00 3.13552976e-01 -2.87193149e-01 3.40308994e-01 8.41109693e-01 9.18590128e-01 -1.02189505e+00 1.16121900e+00 -9.08150971e-01 5.90442643e-02 2.03585714e-01 8.71971250e-01 3.66317123e-01 5.19782960e-01 -9.99610186e-01 5.66420197e-01 9.38486099e-01 2.03464404e-01 -5.08477867e-01 -6.71854198e-01 -3.17445993e-01 1.87162057e-01 7.94258565e-02 -4.96277869e-01 1.12017655e+00 -1.68195796e+00 -2.43877387e+00 2.66368717e-01 8.42330635e-01 -9.71190631e-01 2.49782130e-01 -1.88683435e-01 -6.97655261e-01 1.21604592e-01 -6.41657591e-01 6.31836295e-01 1.30428112e+00 -2.36394987e-01 -5.62465250e-01 -2.48731717e-01 -3.24306220e-01 1.89011633e-01 -4.85565871e-01 -3.29071492e-01 3.66669774e-01 -6.51806593e-01 -4.82116938e-02 -9.09099936e-01 -3.31019282e-01 1.14023440e-01 1.89932138e-01 -1.31154984e-01 8.78991425e-01 -2.33421460e-01 9.50507402e-01 -2.11941457e+00 -4.81189251e-01 4.22064602e-01 -7.86174089e-02 6.99705005e-01 3.94707710e-01 8.40333104e-02 -8.11133683e-02 -5.81725836e-01 2.05834478e-01 1.48545727e-01 -1.40065104e-01 -1.66896600e-02 -1.12974800e-01 4.46437031e-01 7.45206103e-02 5.33524096e-01 -6.18835270e-01 -3.39941084e-01 4.46538985e-01 3.60162824e-01 -7.27475226e-01 1.83446944e-01 -2.87757099e-01 7.22378939e-02 -2.32116476e-01 5.45464993e-01 8.08040023e-01 2.01669365e-01 1.90117151e-01 -2.35276863e-01 -3.80872428e-01 -3.77644718e-01 -1.45385039e+00 1.88009429e+00 -7.83944726e-01 5.62328815e-01 -1.44860670e-01 -1.01250792e+00 1.52784884e+00 1.32022321e-01 4.24420953e-01 -9.63213742e-01 6.37978375e-01 7.04587579e-01 8.50859284e-02 -2.25136518e-01 4.11263347e-01 -2.86450237e-01 8.50726590e-02 3.31261843e-01 5.52327216e-01 -3.42099443e-02 -7.73980692e-02 -3.29681456e-01 9.02202666e-01 5.15468597e-01 1.65017083e-01 -5.58465123e-01 4.78934139e-01 5.52145466e-02 7.62350082e-01 5.41412115e-01 -1.20579734e-01 -1.23208389e-01 2.00062975e-01 -7.62588799e-01 -1.26581156e+00 -8.27486038e-01 -9.28240493e-02 8.28565538e-01 -1.31878868e-01 -1.73608541e-01 -7.92604208e-01 -3.40392530e-01 2.02751867e-02 6.61547244e-01 2.12345049e-02 -3.99146259e-01 -4.80449885e-01 -8.02784741e-01 5.34572244e-01 5.16391039e-01 8.32593858e-01 -1.22336113e+00 -1.43079913e+00 5.98254323e-01 1.02666104e+00 -5.35948873e-01 2.48478115e-01 6.50283754e-01 -1.50542641e+00 -4.95333761e-01 -6.21303618e-01 -9.88320112e-01 4.38776404e-01 -6.95117474e-01 9.65405762e-01 6.96535632e-02 -4.34707731e-01 7.37370625e-02 -3.07568461e-01 -5.53344846e-01 -4.90141436e-02 1.04673803e-01 4.71199095e-01 -1.36639580e-01 4.07315373e-01 -8.63055944e-01 -7.41714537e-01 -1.45450518e-01 -5.03356636e-01 -2.70098969e-02 7.16896951e-01 9.87848520e-01 5.57677984e-01 1.69096828e-01 1.01586378e+00 -6.98233187e-01 5.31121790e-01 -3.07823926e-01 -1.19307280e+00 -1.73959937e-02 -8.94917250e-01 3.35188895e-01 1.26153481e+00 -7.63881624e-01 -1.05965745e+00 2.62351245e-01 -4.89078969e-01 -5.54912090e-01 4.12000269e-01 1.19264126e-01 3.59243631e-01 -5.66025078e-01 7.80306101e-01 -1.04792029e-01 1.18280733e-02 -1.69621810e-01 -8.54174048e-03 6.49074495e-01 3.08396518e-01 -1.86131895e-01 2.13339686e-01 8.24894290e-03 2.74525702e-01 -8.48613203e-01 -2.84959413e-02 1.37399107e-01 -6.96656406e-02 -5.53464472e-01 6.09507859e-01 -1.00443077e+00 -1.45406342e+00 7.24702835e-01 -6.50518179e-01 -6.47022843e-01 -4.40893114e-01 9.53270257e-01 -7.34685957e-01 -2.53800064e-01 -7.84303784e-01 -9.31110620e-01 -9.72540259e-01 -7.85482287e-01 1.63576216e-01 9.03385997e-01 4.22818139e-02 -8.76013994e-01 3.63926589e-02 -4.92859513e-01 6.01017475e-01 1.49946898e-01 5.68990409e-01 -3.42697829e-01 -2.73764729e-01 2.98299914e-04 1.91861361e-01 5.24074972e-01 -5.12006938e-01 4.97602783e-02 -6.74369752e-01 -5.56344032e-01 5.66911101e-01 -7.21430480e-01 5.29672146e-01 5.55771172e-01 8.42106581e-01 1.16695240e-01 9.68048275e-02 8.97874534e-01 2.18292212e+00 3.36197942e-01 5.95625758e-01 4.21119928e-01 4.35376883e-01 -2.51400501e-01 7.47770071e-01 8.01023185e-01 -2.99622953e-01 2.91073233e-01 3.88448954e-01 -2.68607110e-01 2.24694267e-01 -1.06599435e-01 4.37817544e-01 1.08573830e+00 1.53941408e-01 2.15236917e-01 -7.25795150e-01 3.78151648e-02 -1.81129658e+00 -6.15933657e-01 -3.04638594e-02 2.22545528e+00 6.35715842e-01 7.40484774e-01 8.05923566e-02 4.31376338e-01 4.47600186e-01 -3.89261872e-01 -9.73153174e-01 -1.28219259e+00 3.32822837e-02 8.43824089e-01 9.36669946e-01 2.64932692e-01 -6.01275802e-01 7.89767683e-01 4.96143484e+00 1.03873730e+00 -1.64581311e+00 1.09679392e-02 5.34270942e-01 -5.42088270e-01 3.79209727e-01 -1.53590605e-01 -9.66031075e-01 5.63127816e-01 1.37662256e+00 1.49686739e-01 3.15287262e-01 1.32621121e+00 -7.85034522e-02 -4.64091212e-01 -7.60847449e-01 1.42142916e+00 -1.97605059e-01 -1.17713559e+00 -4.47883248e-01 -4.32119012e-01 7.83328474e-01 2.05618702e-02 2.11231932e-01 7.35556901e-01 -1.44239604e-01 -5.57540834e-01 6.73272967e-01 5.50171912e-01 6.86881840e-01 -1.45395887e+00 8.03734899e-01 3.01877439e-01 -8.75123799e-01 -5.05816936e-01 -7.60907888e-01 -5.14603198e-01 -9.23565030e-02 6.91805720e-01 -7.78810740e-01 5.21889441e-02 8.17235410e-01 3.60801727e-01 -3.17151725e-01 9.06190872e-01 -2.92115752e-03 7.34614491e-01 -6.34278119e-01 -7.46469140e-01 4.39670712e-01 -2.60840654e-01 1.98842391e-01 8.18428338e-01 5.65068960e-01 -3.23394202e-02 1.40363956e-02 5.77507079e-01 1.31250208e-03 4.63326424e-01 -3.20629597e-01 1.59685016e-01 1.29575223e-01 1.42027318e+00 -1.10272539e+00 -3.40559125e-01 -2.77201593e-01 9.57173288e-01 2.79109657e-01 -5.15498891e-02 -9.69133317e-01 -9.50054348e-01 2.67951369e-01 -1.15226600e-02 5.26083112e-01 -2.40993381e-01 -3.56062651e-01 -6.67938232e-01 -1.58936173e-01 -6.67894542e-01 -7.15050381e-03 -7.06298590e-01 -7.46173501e-01 6.01495683e-01 -6.40669823e-01 -1.44365883e+00 -6.67549610e-01 -8.82898808e-01 -5.40164411e-01 6.67907536e-01 -1.34948826e+00 -5.55974483e-01 -7.38836825e-02 7.33371019e-01 3.22288662e-01 -7.15600014e-01 8.83795977e-01 2.96629846e-01 -4.56766337e-01 7.16162503e-01 5.85483491e-01 -2.15084106e-01 4.04944032e-01 -1.04723370e+00 1.54713526e-01 4.45213288e-01 -1.34236902e-01 1.42121583e-01 6.50331616e-01 -7.86923885e-01 -1.64516580e+00 -8.08923364e-01 1.36022031e-01 7.00040638e-01 3.63385171e-01 -3.85877520e-01 -6.63837373e-01 2.33052090e-01 4.43928868e-01 2.66698003e-01 6.20521605e-01 -1.73813865e-01 3.45492274e-01 -7.66185522e-01 -1.47679210e+00 4.85965043e-01 3.94393861e-01 -9.28371623e-02 -1.68475047e-01 1.17219396e-01 3.38561833e-01 -5.32564700e-01 -7.99051464e-01 8.96627605e-02 5.56263447e-01 -1.19270909e+00 5.61660945e-01 -1.82224840e-01 2.21693590e-01 -2.97692895e-01 7.32230768e-02 -1.22979915e+00 -4.49621351e-03 -7.46979117e-01 -2.96531737e-01 7.87438035e-01 1.88289642e-01 -6.03738666e-01 1.28735256e+00 1.01764083e-01 7.51988171e-03 -1.12107432e+00 -9.43169475e-01 -8.00472200e-01 -1.10518262e-01 -2.90218294e-01 2.85021693e-01 5.22147298e-01 1.51515350e-01 3.91055882e-01 -2.20440656e-01 -1.57033727e-01 5.33077538e-01 -1.74317226e-01 4.42349851e-01 -9.39783275e-01 -7.80114830e-01 -4.72934768e-02 -7.67581701e-01 -5.51175594e-01 -1.11450195e-01 -7.50312984e-01 -3.20118189e-01 -7.35984564e-01 -6.57529473e-01 -8.15688908e-01 -5.15685976e-01 2.05197245e-01 4.28096592e-01 2.60854840e-01 7.02046305e-02 -1.77294299e-01 -4.47885096e-01 6.04755819e-01 7.40162432e-01 1.04554541e-01 -6.20200753e-01 1.09758981e-01 1.16544336e-01 8.02392006e-01 1.27353466e+00 -6.56971097e-01 -7.26058662e-01 -1.84942812e-01 6.54225051e-01 3.56198967e-01 8.22572932e-02 -1.98564410e+00 5.18763542e-01 3.09862167e-01 1.04678833e+00 -5.91667295e-01 2.42540255e-01 -1.09571874e+00 2.99919732e-02 1.12313354e+00 2.11919248e-01 4.77946103e-01 6.31614089e-01 2.39840582e-01 1.10274674e-02 -6.27153099e-01 8.08491588e-01 2.18467750e-02 -8.19955170e-01 -7.48226866e-02 -5.86737573e-01 -2.40651965e-01 1.26583266e+00 -2.99732745e-01 1.93895206e-01 -4.59411321e-03 -5.56450367e-01 7.60108791e-03 1.54621586e-01 -8.25373363e-03 8.38155210e-01 -1.48602927e+00 -3.26734602e-01 6.14547789e-01 -5.01066446e-01 -3.40686589e-01 5.15029669e-01 4.49506372e-01 -1.13882864e+00 5.49375825e-02 -1.14274466e+00 -6.00490212e-01 -9.31908369e-01 5.80676198e-01 5.78603983e-01 -2.52294153e-01 -6.28203332e-01 7.38654733e-01 -8.92778814e-01 -3.70685399e-01 1.50826722e-01 -3.50082070e-01 -1.16648652e-01 -2.64709860e-01 4.33812886e-01 6.44696534e-01 3.74320656e-01 2.76030630e-01 -2.83544153e-01 4.15292859e-01 -6.47453591e-02 -2.46239424e-01 1.45322812e+00 4.31751013e-01 1.58220425e-01 6.36764348e-01 1.15334189e+00 -3.57223421e-01 -1.45467758e+00 6.60195276e-02 -1.46450371e-01 1.26591101e-01 4.97923046e-01 -7.04302430e-01 -1.24672329e+00 8.45016301e-01 1.54188013e+00 -3.03696752e-01 1.47479820e+00 -1.01701093e+00 8.74007225e-01 7.89856434e-01 4.47696626e-01 -1.92413163e+00 1.71954468e-01 5.31540096e-01 4.79357541e-01 -8.93816590e-01 2.88423449e-01 2.83637792e-01 -3.39063346e-01 1.58877110e+00 8.81262600e-01 -9.04344678e-01 9.41260338e-01 8.07237446e-01 5.81948645e-02 1.17837630e-01 -6.87856495e-01 4.30499405e-01 -5.22984624e-01 4.00711447e-01 1.00501686e-01 7.68306032e-02 -4.08001125e-01 5.31733513e-01 -2.52278447e-01 5.63827038e-01 4.55983043e-01 1.21572280e+00 -5.66916645e-01 -8.37868452e-01 -2.63586968e-01 5.46116948e-01 -4.81559515e-01 -3.76558565e-02 5.81724942e-01 6.26668751e-01 3.85328114e-01 4.78478760e-01 4.31175351e-01 -6.26684368e-01 1.55059814e-01 -1.18224509e-01 7.57720947e-01 -9.84667838e-02 -1.18583262e+00 -1.85930043e-01 -4.61234778e-01 -4.95092511e-01 6.73312098e-02 -2.39190787e-01 -1.71748996e+00 -5.25721073e-01 -2.92098999e-01 -2.90669296e-02 1.30886149e+00 5.89082420e-01 2.47444615e-01 8.24862480e-01 7.03246713e-01 -7.91844547e-01 -8.12587917e-01 -7.76047289e-01 -9.34623063e-01 -2.85664737e-01 2.37317607e-02 -6.28815770e-01 -8.12545884e-03 -4.91111279e-01]	[8.23653793334961, 2.6699788570404053]
dad4a5c1-db89-4f2f-9cac-8d5408fa04d9	invariant-teacher-and-equivariant-student-for	2012.09398	null	https://arxiv.org/abs/2012.09398v1	https://arxiv.org/pdf/2012.09398v1.pdf	Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation	We propose a novel method based on teacher-student learning framework for 3D human pose estimation without any 3D annotation or side information. To solve this unsupervised-learning problem, the teacher network adopts pose-dictionary-based modeling for regularization to estimate a physically plausible 3D pose. To handle the decomposition ambiguity in the teacher network, we propose a cycle-consistent architecture promoting a 3D rotation-invariant property to train the teacher network. To further improve the estimation accuracy, the student network adopts a novel graph convolution network for flexibility to directly estimate the 3D coordinates. Another cycle-consistent architecture promoting 3D rotation-equivariant property is adopted to exploit geometry consistency, together with knowledge distillation from the teacher network to improve the pose estimation performance. We conduct extensive experiments on Human3.6M and MPI-INF-3DHP. Our method reduces the 3D joint prediction error by 11.4% compared to state-of-the-art unsupervised methods and also outperforms many weakly-supervised methods that use side information on Human3.6M. Code will be available at https://github.com/sjtuxcx/ITES.	['Ya zhang', 'Maosen Li', 'Siheng Chen', 'Chenxin Xu']	2020-12-17	null	null	null	null	['unsupervised-3d-human-pose-estimation']	['computer-vision']	[-5.37591994e-01 3.92268419e-01 -1.70972437e-01 -4.88151938e-01 -5.88487625e-01 -2.10332885e-01 2.25427717e-01 -3.46573800e-01 -3.84836525e-01 4.44961846e-01 2.14111850e-01 -1.22120120e-01 -3.86982858e-02 -4.96647924e-01 -9.11905468e-01 -5.18626213e-01 4.38507879e-03 8.58958423e-01 1.91160753e-01 -2.45297194e-01 -7.03034475e-02 4.56137866e-01 -9.96786177e-01 -3.88644040e-01 1.03415167e+00 7.35137045e-01 2.17238516e-01 3.45861882e-01 2.65242904e-01 4.00985658e-01 -2.97363222e-01 1.81966387e-02 4.29375499e-01 -1.24066338e-01 -7.77427971e-01 3.05014998e-01 6.57090664e-01 -5.27005732e-01 -5.84811985e-01 9.13432479e-01 7.54289269e-01 4.72687662e-01 7.15720236e-01 -9.95184302e-01 -4.23199445e-01 1.13703981e-01 -6.73634648e-01 -2.01167196e-01 3.88030976e-01 1.39398620e-01 6.13670528e-01 -1.06009185e+00 5.74265420e-01 1.40037060e+00 7.31210768e-01 4.96752828e-01 -1.04500520e+00 -6.85623646e-01 2.09861621e-01 2.44398549e-01 -1.63286066e+00 -1.24252960e-01 1.15357006e+00 -3.84957135e-01 8.51906300e-01 -4.78239777e-03 8.38257492e-01 1.08866334e+00 1.14139296e-01 7.03801155e-01 8.21030021e-01 -3.72848064e-01 -1.59522459e-01 -1.58101887e-01 -1.32233456e-01 1.28215837e+00 6.31706938e-02 4.12836038e-02 -5.58908403e-01 1.59694925e-02 1.30474627e+00 -6.64974144e-03 -1.30680054e-01 -9.53613520e-01 -1.17999375e+00 6.78693712e-01 7.76787579e-01 -2.51993984e-01 -7.22490698e-02 3.15479219e-01 1.25363097e-01 -6.12054244e-02 6.38529658e-01 1.81459352e-01 -7.28456497e-01 -2.68557128e-02 -5.69853306e-01 3.39470923e-01 5.66644728e-01 1.23570323e+00 7.47357428e-01 1.28268003e-01 1.54657543e-01 7.66539991e-01 8.64799440e-01 5.90772629e-01 1.90515921e-01 -1.16903102e+00 4.67592865e-01 6.72616780e-01 -8.06827769e-02 -1.08925605e+00 -7.53458619e-01 -7.26816356e-01 -9.35962200e-01 2.24256754e-01 3.59676242e-01 -7.16377497e-02 -9.67271209e-01 1.57879007e+00 1.01903212e+00 2.42928132e-01 -3.61709416e-01 1.46299791e+00 1.05659342e+00 3.27421308e-01 -3.62248421e-01 1.87705576e-01 1.24324584e+00 -1.32169926e+00 -2.34221727e-01 -7.21021369e-02 7.78561234e-01 -7.11131752e-01 9.01079714e-01 3.03297162e-01 -9.11006689e-01 -8.66553426e-01 -9.25520182e-01 -3.51484746e-01 1.10847622e-01 3.21877182e-01 5.89809000e-01 2.11371034e-01 -7.38908648e-01 5.84956229e-01 -1.16582453e+00 -3.49950671e-01 2.33928666e-01 4.70072120e-01 -4.77663279e-01 1.78955212e-01 -1.07974827e+00 8.50557148e-01 3.37340891e-01 2.29740366e-01 -8.68931890e-01 -6.15357876e-01 -1.00156653e+00 -3.73790592e-01 6.73775434e-01 -9.98953819e-01 1.12987816e+00 -3.83593321e-01 -1.76534235e+00 8.22805703e-01 1.08546250e-01 -1.67989030e-01 7.40737200e-01 -6.24636233e-01 1.27957836e-01 2.80332267e-01 1.11401871e-01 8.59736204e-01 7.61134684e-01 -1.15417576e+00 3.40737738e-02 -4.69936520e-01 8.65332410e-02 6.78141773e-01 -4.45147082e-02 -4.95534688e-01 -9.51317132e-01 -7.60995448e-01 6.55474305e-01 -1.37358057e+00 -4.94069844e-01 1.19505025e-01 -6.88733935e-01 -3.06525379e-01 5.94738960e-01 -6.41615748e-01 8.00351143e-01 -1.75583327e+00 4.48228985e-01 3.90866846e-01 5.06593287e-01 7.75563717e-02 -5.69815934e-02 1.18116952e-01 2.03041453e-02 -2.53349483e-01 -1.26681492e-01 -6.88353717e-01 3.61758992e-02 2.18277067e-01 1.74498022e-01 8.90989542e-01 1.08250275e-01 8.37141395e-01 -7.42682338e-01 -7.19258606e-01 4.25223649e-01 8.25912237e-01 -8.31988037e-01 3.62568498e-01 -2.47354493e-01 1.07975829e+00 -7.32984781e-01 4.47547346e-01 7.25095093e-01 -4.54857528e-01 1.54627815e-01 -4.04675364e-01 6.66614324e-02 4.33256119e-01 -1.27754509e+00 2.42350888e+00 -2.79343754e-01 6.42492920e-02 -5.90768345e-02 -1.02885985e+00 9.54495788e-01 3.09912473e-01 5.08902073e-01 -3.00182432e-01 3.16563427e-01 -3.37758921e-02 -9.81187597e-02 -3.61568958e-01 1.24221399e-01 3.01994711e-01 6.09312952e-03 2.48053938e-01 2.46336967e-01 -1.61400259e-01 -3.22957814e-01 2.02412292e-01 6.66974604e-01 8.65810096e-01 8.34682658e-02 -4.71050233e-01 5.38618147e-01 -1.45469010e-01 7.99652100e-01 3.87664855e-01 -1.56457111e-01 7.06851065e-01 1.29588693e-01 -6.60611987e-01 -7.99262881e-01 -1.08986163e+00 -8.26939940e-02 8.53132606e-01 2.82207191e-01 -6.46267295e-01 -7.14700282e-01 -8.41371715e-01 1.13137357e-01 1.99813157e-01 -5.13651311e-01 -1.00539185e-01 -6.68805420e-01 -4.37479407e-01 3.54848981e-01 6.81571245e-01 7.09018469e-01 -5.23164690e-01 -3.66109282e-01 -1.25912488e-01 -2.68645853e-01 -9.40899312e-01 -7.43471861e-01 1.05657063e-01 -1.03077912e+00 -1.13624573e+00 -7.15392888e-01 -7.79380083e-01 1.06626618e+00 4.12633792e-02 8.80392432e-01 1.79535031e-01 -1.81472018e-01 4.63544756e-01 -1.71323210e-01 -6.10707104e-02 1.00099184e-01 2.65738159e-01 6.48680449e-01 -4.33664858e-01 2.72739589e-01 -8.48300993e-01 -7.26435244e-01 5.39837420e-01 -2.49781057e-01 3.50604534e-01 4.89993453e-01 7.29010344e-01 9.33045983e-01 -1.62406445e-01 1.75638705e-01 -7.13678718e-01 1.24471623e-03 -8.37662145e-02 -6.05340481e-01 -1.40362307e-01 -4.25902605e-01 3.05046469e-01 4.00724679e-01 -6.33111894e-01 -1.08001506e+00 5.44807494e-01 -2.39222899e-01 -6.84996605e-01 -3.77941221e-01 3.10013145e-01 -3.06418359e-01 -3.34835291e-01 6.94673538e-01 5.93909658e-02 7.39731491e-02 -8.33315372e-01 3.45961124e-01 2.06442282e-01 5.32644272e-01 -8.93572390e-01 1.19990420e+00 3.27750266e-01 2.59330302e-01 -7.29783118e-01 -1.03317595e+00 -3.77805322e-01 -1.08861411e+00 -2.03722045e-01 1.03157866e+00 -1.34266639e+00 -8.58636320e-01 5.45980275e-01 -1.23257709e+00 -5.62157691e-01 9.68705863e-02 8.39064896e-01 -6.76192641e-01 5.74695349e-01 -6.88645005e-01 -4.72301841e-01 -3.03950965e-01 -1.26698279e+00 1.09569228e+00 3.58100794e-02 -2.36823484e-01 -1.01224041e+00 3.59086916e-02 6.33317173e-01 -2.17106286e-02 2.85964221e-01 3.99953216e-01 -4.62910116e-01 -5.38175821e-01 7.16070309e-02 -5.39557487e-02 1.43529832e-01 -6.19803146e-02 -3.75367731e-01 -5.60154080e-01 -4.13152456e-01 -1.28377108e-02 -4.36570227e-01 7.23745525e-01 3.63766253e-01 1.27051556e+00 -1.62327021e-01 -2.47696385e-01 9.23883915e-01 8.08187664e-01 -4.53473955e-01 3.04673523e-01 2.20051453e-01 1.43342698e+00 5.76552033e-01 6.37824059e-01 4.27021921e-01 8.66127551e-01 8.31121862e-01 4.30653542e-01 -1.13526016e-01 -1.31476283e-01 -5.55882573e-01 1.99365765e-01 1.35109496e+00 -4.09996927e-01 3.00819367e-01 -1.00643969e+00 4.10658307e-02 -1.89469898e+00 -3.29212427e-01 -1.57843322e-01 1.98086345e+00 8.35357726e-01 2.73712248e-01 2.13499352e-01 -2.29589313e-01 5.13315380e-01 1.55020833e-01 -6.21097326e-01 2.34410420e-01 4.72158968e-01 -4.92755249e-02 3.85938764e-01 7.25607216e-01 -1.15765560e+00 1.08841920e+00 5.05010605e+00 8.48534346e-01 -9.09905434e-01 8.06874037e-02 3.36320698e-01 -7.42995888e-02 -4.96033728e-02 9.49320421e-02 -9.40371931e-01 1.67122409e-01 3.63311440e-01 4.66206104e-01 2.29237527e-01 1.00313175e+00 4.26759362e-01 3.19980569e-02 -1.00837874e+00 1.14153695e+00 1.01378441e-01 -9.87532139e-01 -8.86440277e-02 1.16895467e-01 6.59366429e-01 8.08641911e-02 -1.15598910e-01 1.92801461e-01 9.09038335e-02 -9.18699443e-01 6.53326452e-01 7.07204819e-01 7.91629672e-01 -8.79712999e-01 4.40466672e-01 6.35633469e-01 -1.44155264e+00 5.83107948e-01 -4.68847513e-01 -2.54556865e-01 5.01546636e-02 6.41014218e-01 -6.85908198e-01 6.35074794e-01 9.06154692e-01 9.12548602e-01 -6.47621632e-01 6.73710823e-01 -6.24540031e-01 3.84370297e-01 -5.15367627e-01 2.05591887e-01 2.28790529e-02 -3.94523382e-01 7.61012256e-01 8.41764450e-01 -2.41492270e-03 2.09744588e-01 7.59093702e-01 7.84923136e-01 -8.22818205e-02 -5.31074107e-02 -3.65667313e-01 3.96892786e-01 4.03690308e-01 1.34764934e+00 -6.30962968e-01 -2.04974070e-01 -8.67646635e-02 1.13914120e+00 4.92054373e-01 2.81686544e-01 -9.03864682e-01 -2.94238567e-01 3.85954201e-01 1.98205456e-01 2.22825542e-01 -7.64895439e-01 8.05345774e-02 -1.33932722e+00 2.08464876e-01 -7.58730054e-01 1.46778584e-01 -7.67297268e-01 -1.16296613e+00 3.87033671e-01 3.29580247e-01 -1.29762304e+00 -2.02431202e-01 -5.85236669e-01 -5.34318626e-01 6.62684441e-01 -1.04469264e+00 -1.30858088e+00 -3.69500399e-01 5.42591870e-01 2.28862599e-01 -1.07999831e-01 6.82937622e-01 1.61232695e-01 -5.44035196e-01 6.02250695e-01 -2.82710165e-01 3.75985146e-01 9.31326210e-01 -1.40458822e+00 5.43777525e-01 4.34270918e-01 1.79930165e-01 8.29514384e-01 5.03466964e-01 -8.34787011e-01 -1.63815928e+00 -1.11653531e+00 5.79131901e-01 -6.83795810e-01 3.22315961e-01 -5.16240180e-01 -8.01844120e-01 7.77136922e-01 -1.81800291e-01 1.91246808e-01 4.74899352e-01 3.61300856e-01 -5.04209816e-01 -2.91752666e-02 -9.78418231e-01 5.92515528e-01 1.43282199e+00 -4.03527588e-01 -6.75947785e-01 5.13376534e-01 9.72678423e-01 -1.06505537e+00 -1.06685984e+00 4.72103298e-01 5.51155031e-01 -6.24205410e-01 1.08094001e+00 -3.60196710e-01 1.68053478e-01 -5.69003999e-01 4.06023487e-02 -1.22637355e+00 -3.08451355e-01 -6.53057277e-01 -5.19986331e-01 7.21761644e-01 8.79815891e-02 -5.03930092e-01 1.17564607e+00 2.85528153e-01 -2.19677106e-01 -1.09081078e+00 -8.74058425e-01 -8.80934298e-01 1.59081057e-01 -4.34699893e-01 3.49405080e-01 8.30642819e-01 -2.24682331e-01 5.69252968e-01 -6.03831828e-01 4.21927929e-01 9.81161714e-01 2.56024376e-02 1.24569917e+00 -1.09885335e+00 -5.78827798e-01 1.11722294e-02 -5.03773928e-01 -1.77846277e+00 2.74956942e-01 -9.61524487e-01 2.06522662e-02 -1.32515192e+00 4.91596907e-02 -2.57101208e-01 7.05543905e-02 5.65350056e-01 4.03794721e-02 2.78439671e-01 1.28583359e-02 1.44080222e-01 -9.51591790e-01 8.78027678e-01 1.61417913e+00 1.84028029e-01 -3.24366480e-01 -1.05131745e-01 -3.08229774e-01 1.12042284e+00 9.01860833e-01 -4.45864826e-01 -4.70007330e-01 -5.47485232e-01 4.47577052e-02 -1.62643604e-02 7.05725908e-01 -1.09602618e+00 2.92650789e-01 -1.33009970e-01 8.25675368e-01 -1.05447602e+00 4.42564458e-01 -6.92648947e-01 1.57269575e-02 5.36560237e-01 -1.20916516e-01 -1.14498124e-01 8.68135039e-03 5.87629199e-01 2.54263967e-01 9.90988314e-02 5.85677981e-01 -2.00832427e-01 -5.03019691e-01 7.32037067e-01 -6.73196614e-02 1.88947722e-01 5.76802373e-01 9.14650857e-02 1.81330621e-01 -4.72122312e-01 -8.91305864e-01 5.17260969e-01 5.15759468e-01 2.44218111e-01 7.34400928e-01 -1.63759327e+00 -5.14812708e-01 1.67514756e-01 1.01434991e-01 8.33803594e-01 3.20203215e-01 9.80207503e-01 -7.52994418e-01 1.89633265e-01 -5.75708412e-02 -9.32000220e-01 -1.05203271e+00 2.08509728e-01 4.47992980e-01 -1.28169432e-01 -7.91528642e-01 8.89971316e-01 1.39867842e-01 -1.16663063e+00 3.97172451e-01 -2.45226800e-01 1.87954649e-01 -5.24584115e-01 8.24338794e-02 4.50503826e-01 -1.22483127e-01 -8.11999798e-01 -5.26674151e-01 8.16477776e-01 -7.93042481e-02 1.31050363e-01 1.31407154e+00 -1.33702010e-01 6.43294379e-02 2.66313165e-01 1.28258502e+00 4.56605069e-02 -1.57473946e+00 -3.69218647e-01 -3.46411228e-01 -2.85658032e-01 -2.99445242e-02 -4.81077999e-01 -1.14341640e+00 8.04192364e-01 5.07097304e-01 -6.10393405e-01 7.28822172e-01 7.14296103e-02 7.71000504e-01 8.22947145e-01 4.34497684e-01 -1.15474284e+00 3.96105677e-01 7.90678322e-01 1.04385602e+00 -1.47195137e+00 3.95925313e-01 -6.46352828e-01 -3.36333007e-01 1.13792455e+00 1.18604076e+00 -5.29713571e-01 8.53077531e-01 -2.28307962e-01 1.62607715e-01 -2.75195777e-01 -3.02228659e-01 -2.27273572e-02 9.50426877e-01 6.03549778e-01 5.81952214e-01 7.59377610e-03 -1.03472404e-01 5.64541578e-01 -3.51117820e-01 -4.31920141e-01 3.23995482e-03 7.40415871e-01 -3.56929630e-01 -1.15797782e+00 -4.04137671e-01 1.53387770e-01 -3.85286734e-02 8.83293897e-02 -2.42294312e-01 8.55058253e-01 1.94527939e-01 5.30453205e-01 -1.43954083e-01 -6.15631759e-01 2.49908507e-01 -7.97423944e-02 8.20667505e-01 -7.64574885e-01 -2.18158662e-01 4.36074704e-01 1.45775769e-02 -7.99814999e-01 -4.99307275e-01 -3.24471802e-01 -1.62210310e+00 -3.16409826e-01 -3.88996214e-01 1.15794122e-01 4.00563717e-01 1.04010582e+00 4.59589511e-01 4.71836239e-01 3.25346231e-01 -1.27224672e+00 -5.70745528e-01 -9.81253564e-01 -4.17557359e-01 2.89870799e-01 1.12310007e-01 -1.12361443e+00 -2.27386504e-01 -1.23225786e-01]	[7.003758430480957, -0.9443991184234619]
e506ff1f-a7c4-4b92-940b-a6fe264d65ee	combining-manual-and-automatic-prosodic	null	null	https://aclanthology.org/L16-1613	https://aclanthology.org/L16-1613.pdf	Combining Manual and Automatic Prosodic Annotation for Expressive Speech Synthesis	Text-to-speech has long been centered on the production of an intelligible message of good quality. More recently, interest has shifted to the generation of more natural and expressive speech. A major issue of existing approaches is that they usually rely on a manual annotation in expressive styles, which tends to be rather subjective. A typical related issue is that the annotation is strongly influenced ― and possibly biased ― by the semantic content of the text (e.g. a shot or a fault may incite the annotator to tag that sequence as expressing a high degree of excitation, independently of its acoustic realization). This paper investigates the assumption that human annotation of basketball commentaries in excitation levels can be automatically improved on the basis of acoustic features. It presents two techniques for label correction exploiting a Gaussian mixture and a proportional-odds logistic regression. The automatically re-annotated corpus is then used to train HMM-based expressive speech synthesizers, the performance of which is assessed through subjective evaluations. The results indicate that the automatic correction of the annotation with Gaussian mixture helps to synthesize more contrasted excitation levels, while preserving naturalness.	['Thomas Fran{\\c{c}}ois', 'rine', 'S Brognaux', 'Marco Saerens']	2016-05-01	combining-manual-and-automatic-prosodic-1	https://aclanthology.org/L16-1613	https://aclanthology.org/L16-1613.pdf	lrec-2016-5	['expressive-speech-synthesis']	['speech']	[ 4.83440101e-01 4.90496933e-01 6.26024231e-02 -5.97001910e-01 -9.92006481e-01 -5.18334270e-01 4.85755771e-01 2.21459553e-01 -2.97017485e-01 7.25014389e-01 5.58137596e-01 -8.55578557e-02 1.41478226e-01 -4.09152567e-01 -3.13335419e-01 -7.97644079e-01 5.82070708e-01 5.55455267e-01 2.34878272e-01 -2.65177876e-01 2.58133382e-01 2.33355924e-01 -1.63579023e+00 3.23125303e-01 5.70282102e-01 6.20892227e-01 4.71254289e-01 8.73273253e-01 -3.32787275e-01 9.24377561e-01 -1.07503593e+00 -5.49121261e-01 -2.28409186e-01 -6.68950438e-01 -9.07629073e-01 4.53197271e-01 -2.25579977e-01 8.57351422e-02 2.73707718e-01 1.21675277e+00 5.02009928e-01 2.62152731e-01 6.86439931e-01 -8.37670147e-01 -1.77965388e-01 1.04551589e+00 8.20676461e-02 -1.45696467e-02 4.37436372e-01 -1.33251503e-01 8.85516226e-01 -6.27191901e-01 6.38047218e-01 1.16614616e+00 4.40896511e-01 5.68249166e-01 -1.38958561e+00 -4.56704587e-01 -1.29726186e-01 -1.25205860e-01 -1.37073314e+00 -7.69635856e-01 9.04380798e-01 -6.48653030e-01 8.20072174e-01 6.10169291e-01 4.46944565e-01 1.26233208e+00 -2.00648919e-01 3.36300522e-01 1.09894216e+00 -8.75835538e-01 3.21300477e-01 7.88237453e-01 -2.02643424e-01 3.40780467e-01 -4.09304917e-01 1.58195030e-02 -5.09861112e-01 3.22590694e-02 1.56684846e-01 -7.19870687e-01 -2.19165444e-01 5.62322624e-02 -1.05355167e+00 7.86484659e-01 -2.88350135e-01 9.40049589e-01 -4.16143805e-01 -1.29645243e-01 7.01623499e-01 6.32823855e-02 6.59160018e-01 5.95556796e-01 -1.09530844e-01 -6.24052584e-01 -1.22889519e+00 1.99655056e-01 8.69064271e-01 6.79120362e-01 3.97559494e-01 3.25446337e-01 -2.16760468e-02 1.20804954e+00 4.72427040e-01 3.74350131e-01 6.37802243e-01 -9.79319274e-01 1.54432738e-02 2.97378510e-01 1.59465477e-01 -8.40979159e-01 -2.79216558e-01 -3.96483660e-01 -5.12683332e-01 2.18376890e-01 3.86470377e-01 -1.75503686e-01 -4.97489393e-01 1.74898612e+00 1.24416970e-01 -4.18714583e-01 1.60425857e-01 7.16845810e-01 4.19578224e-01 9.59071994e-01 1.73505098e-01 -5.32113492e-01 1.18901074e+00 -8.80656123e-01 -1.26601446e+00 -5.70695177e-02 7.05763519e-01 -1.19495201e+00 1.20720351e+00 5.74434578e-01 -1.01839054e+00 -7.01927185e-01 -1.00073051e+00 1.41582385e-01 -1.01880632e-01 3.27181071e-01 -9.42082033e-02 9.48687255e-01 -8.03333580e-01 5.43641388e-01 -4.78603184e-01 -2.80705005e-01 -2.78654784e-01 2.10327312e-01 -1.08886972e-01 4.69141752e-01 -1.28095210e+00 1.08299935e+00 5.76304734e-01 -2.02363938e-01 -4.63538706e-01 -2.77143121e-01 -7.26923108e-01 -1.13198841e-02 2.50749201e-01 -8.59050080e-02 1.61155438e+00 -1.44292676e+00 -1.93549407e+00 8.53246689e-01 -8.70427713e-02 -4.08309191e-01 6.46175683e-01 6.96281623e-03 -7.46789098e-01 7.00729489e-02 1.33500591e-01 4.95090544e-01 8.78774524e-01 -1.37925696e+00 -8.56243551e-01 -8.36563110e-02 -3.81779045e-01 1.71279892e-01 -2.38301113e-01 4.13730294e-01 -1.24910578e-01 -8.97988439e-01 -1.18622057e-01 -9.64779675e-01 -5.86398318e-02 -5.73575139e-01 -4.98335689e-01 -3.91873837e-01 6.33565485e-01 -8.18055451e-01 1.57987785e+00 -2.20981550e+00 7.25364238e-02 2.57832378e-01 -1.98346063e-01 2.92883337e-01 3.83738667e-01 4.44531918e-01 -1.99286491e-01 1.36712089e-01 -3.12117189e-01 -4.78572160e-01 2.16922805e-01 2.83750564e-01 -3.39185417e-01 2.75140733e-01 -1.99693609e-02 2.75414735e-01 -9.49457347e-01 -6.84009075e-01 3.50867122e-01 5.44468105e-01 -4.00823116e-01 4.63164717e-01 -1.11720972e-01 6.95736825e-01 -1.78358227e-01 9.48615521e-02 8.15645903e-02 2.77058035e-01 2.15350389e-01 -2.22276449e-01 -4.65437889e-01 6.00736618e-01 -1.14901733e+00 1.57805347e+00 -4.15189892e-01 6.94309354e-01 -2.51536667e-02 -1.01645410e+00 1.22840440e+00 9.03419077e-01 3.77789289e-01 -2.02461973e-01 3.16763788e-01 4.43513364e-01 1.02413885e-01 -7.04120696e-01 7.79930115e-01 -5.09074330e-01 -1.58558637e-01 3.11473101e-01 1.06034771e-01 -5.63966036e-01 1.05482295e-01 -1.24872603e-01 6.23525202e-01 1.81824416e-01 3.84442121e-01 -2.90552288e-01 6.08169019e-01 -7.56634846e-02 4.13846225e-01 4.99374956e-01 -1.17321029e-01 4.61725712e-01 4.09128606e-01 1.09390192e-01 -1.34056258e+00 -7.23944247e-01 -1.72723159e-01 1.26739502e+00 -3.81892949e-01 -3.75948817e-01 -1.25744569e+00 -4.11761552e-01 -7.58748055e-01 1.39384425e+00 -3.06047231e-01 -2.11241856e-01 -5.02137542e-01 -4.04385418e-01 7.13904798e-01 2.15654582e-01 -3.58851887e-02 -1.22339809e+00 -4.89123344e-01 6.31681025e-01 -5.99375069e-01 -1.05972576e+00 -2.93905407e-01 3.70595783e-01 -4.57220972e-01 -4.14562762e-01 -6.22169971e-01 -6.78922594e-01 4.23319191e-01 -3.85818213e-01 7.45709002e-01 -1.75603226e-01 2.42894039e-01 6.44835681e-02 -7.80340075e-01 -5.09727061e-01 -1.51675534e+00 1.18983090e-01 1.46223739e-01 1.54083014e-01 3.15176040e-01 -3.57264519e-01 8.12894478e-02 3.13511521e-01 -9.30352867e-01 1.55793235e-01 3.82031709e-01 6.70452774e-01 2.94442236e-01 1.15626439e-01 7.15436637e-01 -9.50555384e-01 8.05415928e-01 -1.39243200e-01 -1.50155097e-01 -3.47989015e-02 -5.62892258e-01 9.95958894e-02 5.68686366e-01 -4.69671398e-01 -1.33541679e+00 1.71804711e-01 -8.44016492e-01 -1.47535037e-02 -6.09829307e-01 3.01438272e-01 -4.08389568e-01 2.29286894e-01 8.59803796e-01 1.48901597e-01 -1.37038991e-01 -3.74359876e-01 2.83708841e-01 1.18235016e+00 7.46492326e-01 -5.15059769e-01 6.29025817e-01 -7.30829407e-03 -4.89693701e-01 -1.14603150e+00 -7.39627242e-01 -4.88965780e-01 -6.91055179e-01 -7.22294390e-01 1.03861964e+00 -4.88771647e-01 -1.61410332e-01 3.01881790e-01 -1.19504106e+00 -2.94274181e-01 -5.04781604e-01 7.29735970e-01 -7.84744263e-01 4.97742325e-01 -4.60782528e-01 -1.10344613e+00 -2.59392820e-02 -1.35592079e+00 9.16617692e-01 -5.46082966e-02 -9.17543352e-01 -8.24122608e-01 1.13345616e-01 6.53946042e-01 1.29246816e-01 -5.96198440e-03 9.62184787e-01 -9.94969487e-01 2.17600986e-01 -4.08419758e-01 3.42476338e-01 7.97130048e-01 1.81053281e-01 1.93612769e-01 -1.35233283e+00 2.23407343e-01 3.08533460e-01 -2.45541543e-01 1.38902977e-01 2.15839148e-01 8.70292187e-01 -4.58161563e-01 6.92871138e-02 -7.86028951e-02 8.78397465e-01 4.26700383e-01 5.83711267e-01 1.02295987e-01 3.46094698e-01 1.01859283e+00 6.85350001e-01 4.69246447e-01 -3.77100334e-02 9.52219963e-01 7.34585449e-02 -2.08282471e-03 -3.15230116e-02 -2.92241782e-01 3.58986109e-01 1.30644858e+00 -1.49367228e-01 -4.56784338e-01 -7.27183282e-01 5.55748224e-01 -1.56430542e+00 -9.79604423e-01 -2.16186658e-01 2.01318860e+00 1.04099917e+00 2.74949789e-01 2.42511913e-01 7.32113779e-01 1.01773059e+00 3.63709331e-02 2.45489478e-01 -8.41273129e-01 -1.01103924e-01 -1.09310441e-01 1.84258670e-01 7.81452358e-01 -8.72513592e-01 8.20694625e-01 5.84959173e+00 1.13435757e+00 -9.90171969e-01 1.58803254e-01 4.99201477e-01 2.01129064e-01 -3.41132164e-01 -2.00715467e-01 -5.84476769e-01 6.97752476e-01 1.28399384e+00 -1.34455115e-01 1.98965922e-01 7.45475888e-01 6.79118276e-01 -2.29152754e-01 -8.53051066e-01 6.76092744e-01 2.77250350e-01 -9.06825542e-01 -4.35634591e-02 -4.77567650e-02 5.56827307e-01 -5.26908934e-01 -7.85361156e-02 2.38798901e-01 1.40169382e-01 -8.51321220e-01 1.27172971e+00 5.33187032e-01 6.73637390e-01 -8.60866547e-01 8.26348007e-01 5.74104667e-01 -7.20969975e-01 2.16770902e-01 -1.19071223e-01 8.31835642e-02 5.24573803e-01 3.45504731e-01 -1.21932328e+00 2.21421346e-01 4.61687773e-01 -7.64224380e-02 -1.07446924e-01 6.77815497e-01 -3.81772786e-01 9.94619370e-01 -1.85298845e-01 -2.97066271e-01 2.42877558e-01 -1.07440963e-01 9.38841820e-01 1.65223312e+00 4.25944567e-01 1.24410996e-02 1.71182543e-01 8.14031065e-01 3.34603041e-01 5.67744374e-01 -5.18690705e-01 -1.87437698e-01 3.70992929e-01 1.14623225e+00 -7.81346500e-01 -4.36680943e-01 -2.47409120e-01 9.16318357e-01 -4.55625057e-02 5.13749495e-02 -8.25654447e-01 -1.98577970e-01 1.53809279e-01 2.70912737e-01 1.11896135e-01 9.41496044e-02 -2.75289774e-01 -5.48045516e-01 -2.10070059e-01 -9.93005395e-01 -1.46509007e-01 -8.89059007e-01 -8.55281055e-01 1.01262093e+00 -7.02421442e-02 -1.03642714e+00 -5.86594701e-01 -2.21199244e-01 -2.61760384e-01 8.40389073e-01 -9.06650960e-01 -8.51511836e-01 1.33505538e-02 9.72253606e-02 8.74618411e-01 -2.07433477e-01 1.04714501e+00 4.61960316e-01 -2.41861448e-01 3.99516314e-01 -1.34570271e-01 7.04576299e-02 7.91212380e-01 -1.31246400e+00 -1.64922267e-01 9.22298551e-01 2.74907172e-01 1.33410856e-01 1.47423267e+00 -5.11292994e-01 -3.53587866e-01 -9.74013269e-01 1.52054846e+00 -2.52553940e-01 7.92626262e-01 -2.61488110e-01 -1.05022776e+00 3.05077851e-01 1.97675303e-01 -6.36756361e-01 8.83639932e-01 -1.87187150e-01 1.37039393e-01 6.96285218e-02 -1.00532043e+00 5.02043068e-01 4.47612703e-01 -7.18588829e-01 -8.80229890e-01 2.83694178e-01 6.59465373e-01 -1.71649173e-01 -8.08899820e-01 1.82260886e-01 2.00040668e-01 -9.56414878e-01 4.22971249e-01 -3.41659337e-01 1.99934885e-01 -3.04271162e-01 -2.08496019e-01 -1.45844293e+00 -1.81884065e-01 -7.03457713e-01 4.26159203e-01 1.60831320e+00 5.68618596e-01 -4.94859554e-02 4.14101928e-01 4.77454990e-01 -4.20575410e-01 -1.47497073e-01 -8.84172738e-01 -6.30596161e-01 -3.23502094e-01 -8.66539836e-01 3.27047378e-01 8.37571621e-01 3.51636946e-01 5.70958555e-01 -6.44281924e-01 1.82829890e-02 1.65193692e-01 -3.59013617e-01 6.27376199e-01 -1.25227726e+00 -2.41663903e-01 -4.92149144e-01 -3.67029011e-01 -6.85229361e-01 3.12954336e-01 -7.11221099e-01 7.53616989e-01 -9.89287496e-01 -3.06767613e-01 -2.15906963e-01 1.29322380e-01 1.42861694e-01 -3.21510434e-03 2.44125515e-01 8.03271160e-02 5.55419736e-02 -3.22262079e-01 4.87922370e-01 8.80314171e-01 1.05247714e-01 -3.36459637e-01 4.16802615e-01 -2.80000836e-01 9.96299386e-01 8.77360344e-01 -6.61226153e-01 -2.76278436e-01 1.40612885e-01 2.50604540e-01 1.19921990e-01 1.04766421e-01 -1.10400271e+00 9.85457748e-02 5.23413755e-02 -1.62344903e-01 -2.88358986e-01 4.06576395e-01 -8.84405434e-01 4.88433570e-01 2.50420779e-01 -7.74404824e-01 -1.46710128e-01 -7.21808299e-02 3.68798107e-01 -4.61906970e-01 -8.76487374e-01 1.06050885e+00 -1.93160810e-02 -4.96975154e-01 -3.89380306e-01 -1.02738857e+00 -1.48111030e-01 8.38677108e-01 -3.40924472e-01 2.90267318e-01 -5.37199318e-01 -9.10607994e-01 -5.51845193e-01 2.74417847e-01 3.91551167e-01 2.09814295e-01 -1.07058072e+00 -7.68197477e-01 -3.56110521e-02 2.44462505e-01 -3.63191634e-01 1.40280887e-01 7.89006114e-01 -4.36378479e-01 3.69879514e-01 1.04811266e-01 -4.38603669e-01 -1.50796318e+00 4.32016462e-01 2.54991978e-01 -1.32796243e-01 -4.85359102e-01 7.14119315e-01 -7.49287084e-02 -2.11085185e-01 4.09823000e-01 -2.75360972e-01 -4.67524856e-01 2.25048527e-01 3.69332105e-01 4.25390512e-01 1.65460601e-01 -1.15285039e+00 5.23701198e-02 2.34120525e-02 3.10392886e-01 -6.27210259e-01 1.06397855e+00 -3.73145759e-01 8.31479356e-02 9.40739274e-01 8.82197976e-01 4.33495671e-01 -1.06426120e+00 -4.24023382e-02 1.78430632e-01 -2.67062604e-01 7.58417174e-02 -7.79036701e-01 -4.40919459e-01 7.52442420e-01 3.62116903e-01 5.40115237e-01 9.16510940e-01 -2.23976793e-03 5.29367805e-01 2.03534141e-01 7.35057443e-02 -1.67220747e+00 -1.15771510e-01 4.07084316e-01 9.22326207e-01 -8.65959167e-01 -5.00744641e-01 -4.80361849e-01 -9.44478154e-01 1.17134559e+00 1.86512500e-01 2.65299737e-01 4.16357458e-01 4.66083467e-01 3.87234688e-01 3.84262726e-02 -3.45845163e-01 -6.00420125e-02 3.25810909e-01 6.52914047e-01 6.30662560e-01 2.33439252e-01 -5.42395115e-01 6.52978003e-01 -6.61209524e-01 -2.11624905e-01 5.39964795e-01 4.45928633e-01 -8.06404114e-01 -1.18618417e+00 -5.33438802e-01 8.20359588e-02 -7.51643658e-01 3.76242660e-02 -4.40549433e-01 3.99440020e-01 4.31241721e-01 1.34052360e+00 -9.24396366e-02 -3.12784135e-01 2.66496092e-01 5.46170890e-01 9.67153683e-02 -7.31672287e-01 -7.48798668e-01 6.69162214e-01 5.09564102e-01 -1.07786067e-01 -7.13965416e-01 -7.41685450e-01 -1.18526840e+00 6.96124956e-02 -5.01722276e-01 7.40181923e-01 8.85089815e-01 1.15001404e+00 -3.92782182e-01 7.28239477e-01 6.01564288e-01 -6.21250272e-01 -5.27891695e-01 -1.26826370e+00 -7.45496452e-01 4.76152331e-01 2.53059738e-03 -3.74659866e-01 -4.93993193e-01 5.10095537e-01]	[14.679389953613281, 6.573779582977295]
196b1176-bc74-4501-a321-56462cc72f3e	a-multimodal-transformer-fusing-clinical	2208.10240	null	https://arxiv.org/abs/2208.10240v2	https://arxiv.org/pdf/2208.10240v2.pdf	A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Prediction	Deep-learning-based clinical decision support using structured electronic health records (EHR) has been an active research area for predicting risks of mortality and diseases. Meanwhile, large amounts of narrative clinical notes provide complementary information, but are often not integrated into predictive models. In this paper, we provide a novel multimodal transformer to fuse clinical notes and structured EHR data for better prediction of in-hospital mortality. To improve interpretability, we propose an integrated gradients (IG) method to select important words in clinical notes and discover the critical structured EHR features with Shapley values. These important words and clinical features are visualized to assist with interpretation of the prediction outcomes. We also investigate the significance of domain adaptive pretraining and task adaptive fine-tuning on the Clinical BERT, which is used to learn the representations of clinical notes. Experiments demonstrated that our model outperforms other methods (AUCPR: 0.538, AUCROC: 0.877, F1:0.490).	['Chao Chen', 'Fusheng Wang', 'Kayley Abell-Hart', 'Songzhu Zheng', 'Rachel Wong', 'Xinyu Dong', 'Weimin Lyu']	2022-08-09	null	null	null	null	['mortality-prediction']	['medical']	[-2.28298046e-02 8.97701979e-02 -3.06599468e-01 -5.81747115e-01 -9.94803488e-01 -3.81739467e-01 -1.48452455e-02 8.24036717e-01 -2.61816710e-01 8.07927549e-01 1.08549237e+00 -3.48626196e-01 -5.88173985e-01 -5.49252808e-01 -9.83020067e-02 -6.02190256e-01 -4.39365417e-01 5.28949380e-01 -5.42308927e-01 1.65890619e-01 1.49373035e-03 1.99449047e-01 -8.34263563e-01 8.95880997e-01 1.06301761e+00 9.90906060e-01 -8.81173909e-02 5.08460402e-01 -3.64267756e-03 1.11014700e+00 -4.71155554e-01 -4.73126918e-01 -2.20565960e-01 -6.02961302e-01 -5.91348886e-01 -2.54740387e-01 -2.24012136e-01 -3.66567522e-01 -2.80252010e-01 7.16541290e-01 9.40921247e-01 -1.40361547e-01 8.75967324e-01 -7.11124420e-01 -8.44815791e-01 7.56451488e-01 -3.76798958e-01 2.57000506e-01 1.53929651e-01 1.12712942e-01 1.10593796e+00 -9.00547266e-01 6.06820107e-01 9.28164303e-01 9.74496067e-01 4.95772064e-01 -8.56972814e-01 -6.06512785e-01 4.67561558e-03 2.43873760e-01 -1.21244144e+00 -1.86896697e-01 5.37825525e-01 -6.60360456e-01 7.86569595e-01 2.64184535e-01 8.25029254e-01 1.03513825e+00 5.63695848e-01 5.90239406e-01 6.10811412e-01 -3.33097167e-02 7.36272521e-03 5.72870113e-02 3.55164438e-01 9.56180334e-01 5.03954351e-01 2.50713006e-02 -3.73809397e-01 -6.70301259e-01 6.05507076e-01 7.95392573e-01 -3.32702607e-01 2.45217934e-01 -1.36283302e+00 9.46704209e-01 6.83481991e-01 1.46959797e-01 -6.80557787e-01 -1.74173445e-01 6.38979733e-01 2.22603425e-01 4.88329113e-01 4.85716283e-01 -6.45588517e-01 4.60789688e-02 -6.36314571e-01 2.03434452e-02 6.19916379e-01 5.17136455e-01 8.34983438e-02 -1.84222132e-01 -6.56414509e-01 7.75941849e-01 2.90469915e-01 4.36528146e-01 6.71967208e-01 -5.97215295e-01 5.88162839e-01 1.05418277e+00 -4.16630805e-02 -9.05853271e-01 -8.95839691e-01 -6.75985277e-01 -1.32039607e+00 -7.22267270e-01 -3.19919698e-02 -5.73677778e-01 -6.72904849e-01 1.26633990e+00 1.90750081e-02 7.46086687e-02 4.48411047e-01 8.02660644e-01 1.30182946e+00 5.60491025e-01 6.68089271e-01 -3.20923746e-01 1.65820265e+00 -5.60576677e-01 -1.01534891e+00 1.30758613e-01 1.15723515e+00 -3.17686319e-01 9.95081723e-01 2.11493865e-01 -7.89241195e-01 2.10317150e-02 -6.53834522e-01 -7.57141486e-02 -8.27381015e-02 5.38247466e-01 3.74652505e-01 6.03563376e-02 -7.00802147e-01 5.41335642e-01 -7.77180076e-01 -1.11899078e-01 9.45241511e-01 2.59651840e-01 -2.86905587e-01 -2.60678846e-02 -1.26654851e+00 6.79250062e-01 2.60645300e-01 2.93734334e-02 -6.29626453e-01 -9.02356088e-01 -7.32809365e-01 3.59952539e-01 6.53869435e-02 -1.04485214e+00 9.90795255e-01 -5.14964402e-01 -8.30878019e-01 8.88206124e-01 -3.40879522e-02 -3.60151231e-01 2.92160332e-01 -4.77988780e-01 -3.61226559e-01 3.54322553e-01 -4.16424274e-02 4.24594969e-01 1.58332631e-01 -8.48009706e-01 -5.37124574e-01 -7.66994298e-01 -5.19281924e-01 1.92984238e-01 -7.37250149e-01 -7.06541613e-02 7.32004419e-02 -8.15373361e-01 -2.67743528e-01 -5.38675725e-01 -6.23977125e-01 -1.53279841e-01 -4.31338906e-01 -3.34564716e-01 1.98359773e-01 -1.20412362e+00 1.69431889e+00 -2.21897483e+00 -9.31017101e-02 4.03892957e-02 7.62838662e-01 1.16673261e-01 1.00510232e-01 3.94404024e-01 6.74009919e-02 2.93776184e-01 -3.28321636e-01 -7.08220229e-02 -4.21281248e-01 -1.22451093e-02 -1.65303424e-01 2.25371987e-01 4.22323465e-01 1.39559329e+00 -9.17153060e-01 -7.62489378e-01 -1.02117218e-01 7.79252589e-01 -6.49944305e-01 4.73138809e-01 9.55083594e-02 5.41473567e-01 -7.12121964e-01 5.85683048e-01 1.82271346e-01 -9.71637428e-01 4.02403533e-01 -1.00700341e-01 2.99518138e-01 3.44640613e-01 -4.28192973e-01 1.36025012e+00 -1.93726718e-01 1.69819057e-01 -3.94259334e-01 -8.64445686e-01 9.62949634e-01 6.34506166e-01 8.21224988e-01 -4.42626983e-01 1.67692021e-01 -4.52744588e-03 -1.18326902e-01 -9.13803041e-01 -2.16136321e-01 -3.81088018e-01 -9.16085541e-02 1.82410389e-01 -2.21534416e-01 5.45064509e-01 -4.20648545e-01 7.18804896e-02 1.21156430e+00 -4.09471691e-01 8.51763308e-01 -1.18819155e-01 3.04310948e-01 1.80078402e-01 8.01450372e-01 4.40721601e-01 -1.02894537e-01 6.33360684e-01 5.96541882e-01 -8.77095222e-01 -5.37093043e-01 -8.45695794e-01 -3.34793478e-01 7.48405576e-01 -1.56242028e-01 -5.15772641e-01 -2.73983270e-01 -8.24795902e-01 7.43299397e-03 5.69892287e-01 -7.60722339e-01 -4.71263170e-01 -3.01189572e-01 -1.13557947e+00 5.72597623e-01 9.97914493e-01 2.00105131e-01 -1.24006009e+00 -8.73346090e-01 3.53398293e-01 -2.88450360e-01 -7.62419164e-01 -4.82167721e-01 3.29375565e-01 -1.30359054e+00 -1.21125567e+00 -8.42756629e-01 -7.98018932e-01 5.74965239e-01 -2.15418145e-01 1.17125118e+00 1.57762483e-01 -4.58216727e-01 1.12759441e-01 -4.19027269e-01 -4.02469814e-01 -1.62038565e-01 5.62163219e-02 -2.74393052e-01 -7.46164545e-02 6.13758802e-01 -2.25660235e-01 -1.03217947e+00 -1.82030618e-01 -8.43747914e-01 1.06728420e-01 7.48563468e-01 1.10189486e+00 6.68273151e-01 -5.45263648e-01 9.55118179e-01 -1.17229557e+00 9.87925828e-01 -8.99209499e-01 -5.56822568e-02 2.50687361e-01 -9.16860044e-01 5.11021353e-02 7.23967254e-01 -1.78263441e-01 -8.50469947e-01 5.86617403e-02 -1.44272670e-01 -2.27890402e-01 -1.60226390e-01 1.05436051e+00 5.07400222e-02 6.45534754e-01 5.46399295e-01 8.00575390e-02 -2.77744770e-01 -6.92245424e-01 -3.39241847e-02 8.17910075e-01 8.89690667e-02 -3.71792391e-02 -4.22686934e-02 1.27618387e-01 -6.99776709e-02 -3.66825759e-01 -1.18362868e+00 -5.56123018e-01 -4.77370590e-01 2.59997517e-01 1.15985489e+00 -1.16051280e+00 -7.59732366e-01 -1.48636162e-01 -1.07872069e+00 -9.05063450e-02 -2.97788173e-01 6.88761532e-01 -1.60858959e-01 1.64869338e-01 -8.34835708e-01 -5.31585217e-01 -9.10777032e-01 -8.09956372e-01 1.10823131e+00 1.56911120e-01 -5.48009455e-01 -1.23471260e+00 2.89063454e-01 2.40896210e-01 1.79447040e-01 3.18018585e-01 1.38441241e+00 -1.17566919e+00 9.76888984e-02 -2.63291925e-01 -4.57415760e-01 -6.38100132e-03 3.17390770e-01 -3.32859486e-01 -6.95703149e-01 -8.89316648e-02 -1.73951328e-01 -3.40661198e-01 1.07388556e+00 7.29847610e-01 1.49487388e+00 -7.50946701e-01 -5.01151085e-01 9.10397708e-01 1.26962769e+00 5.40159643e-01 4.18334544e-01 1.03977613e-01 7.82400906e-01 5.67727327e-01 3.15419227e-01 9.26222801e-01 7.37738192e-01 9.94720086e-02 1.72260150e-01 -3.01266551e-01 3.74813765e-01 -1.76354006e-01 1.97111234e-01 8.20270479e-01 -1.39425725e-01 -9.54521671e-02 -1.36177957e+00 4.97433692e-01 -1.89522147e+00 -7.04129994e-01 -6.73891380e-02 1.81457579e+00 9.55478787e-01 -2.60481119e-01 -1.02112377e-02 -2.42533326e-01 5.00317752e-01 -1.76052824e-01 -6.57290161e-01 -3.47167291e-02 -1.18672788e-01 4.96974401e-02 1.78754836e-01 1.36480302e-01 -1.16477597e+00 4.95262742e-01 6.24500465e+00 2.79262811e-01 -9.75334585e-01 8.59234557e-02 1.20604706e+00 -1.51186123e-01 -3.49410981e-01 -5.75274825e-01 -6.18124127e-01 5.20208955e-01 9.52571630e-01 -2.59154558e-01 -2.14014769e-01 7.43449807e-01 4.29173708e-01 5.07246971e-01 -1.09278309e+00 1.12786603e+00 -1.50886551e-01 -1.62675118e+00 2.80971438e-01 1.80074796e-01 7.45688081e-01 -8.01320896e-02 8.30360055e-02 9.93729606e-02 4.32638556e-01 -1.31610143e+00 -1.01092823e-01 8.27657402e-01 1.04835451e+00 -6.34907722e-01 1.28149116e+00 2.87979376e-02 -1.02477419e+00 -3.54932666e-01 -2.70277262e-01 2.05313534e-01 -1.25813574e-01 6.58086896e-01 -1.03282177e+00 4.47120786e-01 7.24768400e-01 1.21103847e+00 -5.22598803e-01 1.08384502e+00 1.26771266e-02 9.12181854e-01 3.50388706e-01 -1.44535542e-01 1.07371211e-01 5.27384132e-02 6.23618886e-02 1.47580194e+00 5.15923977e-01 7.03045964e-01 3.73246640e-01 6.78938150e-01 -3.08888704e-01 6.53940380e-01 -6.76152408e-01 -3.55965257e-01 2.23395124e-01 1.08919573e+00 -4.07675177e-01 -4.72131491e-01 -3.40210587e-01 6.15001798e-01 1.75453857e-01 3.01554084e-01 -5.54251254e-01 -2.77322471e-01 4.05322999e-01 2.54637331e-01 3.90176587e-02 3.13305855e-01 -7.70954311e-01 -1.39341009e+00 -3.76394093e-01 -7.79115677e-01 1.09360993e+00 -5.09578407e-01 -1.58394802e+00 7.51617730e-01 -3.68322283e-01 -1.40812612e+00 -2.16120631e-01 -3.53799194e-01 -5.25824964e-01 7.33603776e-01 -1.44821000e+00 -8.91020179e-01 -3.74992251e-01 6.23087585e-01 3.24990958e-01 -5.15851617e-01 1.11352253e+00 1.88262358e-01 -5.54507732e-01 6.52500033e-01 3.27133656e-01 5.37905514e-01 7.62571931e-01 -1.08674586e+00 -9.81701463e-02 7.41416812e-02 -3.68813276e-01 7.02912807e-01 9.89472345e-02 -8.49380791e-01 -1.04352152e+00 -1.48925865e+00 1.13850117e+00 -3.19674522e-01 3.56544018e-01 3.08147788e-01 -1.14505434e+00 6.61112249e-01 -3.92359830e-02 -1.13078989e-01 1.53037417e+00 1.62531108e-01 -1.83082953e-01 -1.23854116e-01 -1.08144855e+00 4.40364063e-01 7.51396358e-01 -2.95609474e-01 -6.66316032e-01 3.16572815e-01 8.43059838e-01 1.71428785e-01 -1.23248672e+00 6.60862565e-01 5.23892045e-01 -4.92644936e-01 1.01590526e+00 -1.31762314e+00 9.92095768e-01 2.29632095e-01 -3.17666121e-02 -1.27287698e+00 -5.98371327e-01 -2.06895217e-01 -3.07433188e-01 6.26716733e-01 5.47903836e-01 -5.22188008e-01 5.49862385e-01 2.85452753e-01 -4.01618630e-02 -1.30537331e+00 -6.59019828e-01 1.86020657e-02 5.69435358e-02 2.72683357e-03 5.46459854e-01 1.20118678e+00 3.21789771e-01 5.73411226e-01 -3.17798555e-01 7.38457590e-02 3.62905890e-01 2.24350989e-01 -5.27683692e-03 -1.70071971e+00 1.74567252e-02 -4.87782001e-01 -1.70599997e-01 -5.14832735e-01 -1.68993771e-01 -1.15081215e+00 -2.88276970e-01 -1.96793604e+00 7.23116815e-01 -2.55375206e-01 -1.07831645e+00 7.02861607e-01 -6.82951212e-01 -1.36617795e-01 -2.53798276e-01 4.25946206e-01 -7.47429609e-01 6.16190434e-01 1.18082309e+00 -1.80882826e-01 -4.43599999e-01 -4.05563675e-02 -1.07835996e+00 5.77388287e-01 9.27321374e-01 -6.09927356e-01 -2.58494049e-01 -3.04802924e-01 3.03005934e-01 6.99826300e-01 3.32956642e-01 -5.98837256e-01 -6.78435415e-02 -1.93798855e-01 8.04357588e-01 -5.37557423e-01 -1.55553162e-01 -6.53821290e-01 -1.11592218e-01 7.97423065e-01 -9.67319846e-01 3.45348805e-01 9.27083716e-02 6.51128769e-01 -3.66652966e-01 1.86619982e-01 4.42414969e-01 -1.83159500e-01 -2.62454212e-01 4.51637298e-01 -4.20543820e-01 2.73200125e-01 8.12458992e-01 1.71195313e-01 -9.82579961e-02 -3.58022869e-01 -1.04939258e+00 4.83526886e-01 -1.49552956e-01 2.24136472e-01 1.10764241e+00 -1.33393216e+00 -1.08563697e+00 4.81585376e-02 2.85655767e-01 -5.74693345e-02 4.16969717e-01 1.01716638e+00 -6.70056641e-01 5.43837428e-01 -2.34692153e-02 -4.78703022e-01 -1.44545710e+00 4.85834450e-01 2.75156111e-01 -8.02467227e-01 -9.69135702e-01 7.28271306e-01 4.87548113e-01 -2.24308819e-01 4.11626577e-01 -4.44611460e-01 -7.06464231e-01 3.79407138e-01 7.57114589e-01 1.44603655e-01 5.46784997e-02 -1.57289445e-01 -5.89270413e-01 3.86992663e-01 -6.23550303e-02 2.23162219e-01 1.92241335e+00 9.69447121e-02 -5.97765930e-02 4.45274889e-01 1.14424741e+00 -2.19646767e-01 -9.06864762e-01 -3.02642733e-01 2.62802273e-01 -8.79235659e-03 -2.34143138e-02 -1.08400285e+00 -1.04896760e+00 1.21327627e+00 7.42777765e-01 -1.76470816e-01 1.24359941e+00 6.56346455e-02 8.24659824e-01 5.97300828e-01 -2.76499897e-01 -5.70229173e-01 9.32454243e-02 4.01623487e-01 8.51547241e-01 -1.40023220e+00 -1.29978001e-01 -1.08576298e-01 -1.23772180e+00 1.30202484e+00 3.72612238e-01 1.10918127e-01 8.83074641e-01 2.46614754e-01 3.73795658e-01 -5.24125636e-01 -1.14755738e+00 1.82965472e-01 5.62705278e-01 3.50551933e-01 8.43222618e-01 2.98304051e-01 -3.77949864e-01 1.45661688e+00 1.49607807e-01 2.97153443e-01 8.00434723e-02 7.91319072e-01 -4.34339434e-01 -5.52758634e-01 -2.15133533e-01 9.46282089e-01 -8.17814291e-01 -5.89253664e-01 -4.87213910e-01 2.52323359e-01 -5.40427379e-02 7.21985340e-01 -1.01517655e-01 -5.78814924e-01 3.12661082e-01 4.57280815e-01 -1.20645061e-01 -6.84410751e-01 -9.30356562e-01 2.19528705e-01 -1.26284778e-01 -2.67126322e-01 -8.10937211e-02 -4.33217198e-01 -1.49890769e+00 1.24450192e-01 7.38938665e-03 3.10632467e-01 6.86490014e-02 7.29901373e-01 8.80350113e-01 9.12927091e-01 4.70371723e-01 -3.20189446e-02 -5.52120566e-01 -8.58372211e-01 -3.90669018e-01 5.00975132e-01 5.48346639e-01 -3.28648269e-01 -3.92078981e-02 3.30720842e-01]	[7.933475017547607, 6.462647438049316]
94fdef1e-8576-4332-ab95-88bb22f78a6b	socratic-pretraining-question-driven	2212.10449	null	https://arxiv.org/abs/2212.10449v3	https://arxiv.org/pdf/2212.10449v3.pdf	Socratic Pretraining: Question-Driven Pretraining for Controllable Summarization	In long document controllable summarization, where labeled data is scarce, pretrained models struggle to adapt to the task and effectively respond to user queries. In this paper, we introduce Socratic pretraining, a question-driven, unsupervised pretraining objective specifically designed to improve controllability in summarization tasks. By training a model to generate and answer relevant questions in a given context, Socratic pretraining enables the model to more effectively adhere to user-provided queries and identify relevant content to be summarized. We demonstrate the effectiveness of this approach through extensive experimentation on two summarization domains, short stories and dialogue, and multiple control strategies: keywords, questions, and factoid QA pairs. Our pretraining method relies only on unlabeled documents and a question generation system and outperforms pre-finetuning approaches that use additional supervised data. Furthermore, our results show that Socratic pretraining cuts task-specific labeled data requirements in half, is more faithful to user-provided queries, and achieves state-of-the-art performance on QMSum and SQuALITY.	['Chien-Sheng Wu', 'Wojciech Kryściński', 'Alexander R. Fabbri', 'Artidoro Pagnoni']	2022-12-20	null	null	null	null	['question-generation']	['natural-language-processing']	[ 6.02984369e-01 5.81994414e-01 -3.25224310e-01 -3.58045965e-01 -1.53714824e+00 -8.79614830e-01 7.10124314e-01 3.82645011e-01 -4.29401904e-01 9.23223019e-01 7.84049392e-01 -1.23679280e-01 -6.73760325e-02 -4.98724014e-01 -5.81664979e-01 1.73151344e-01 4.33527023e-01 1.09326720e+00 2.16664955e-01 -6.55218720e-01 4.33646500e-01 -2.36932114e-02 -1.12703657e+00 8.18762600e-01 1.46281433e+00 5.56055307e-01 2.67766625e-01 1.09706092e+00 -1.06322154e-01 1.13053131e+00 -9.79312539e-01 -3.43147963e-01 -1.38500810e-01 -8.43517661e-01 -1.34479511e+00 2.80100375e-01 7.96615720e-01 -4.76263940e-01 -1.67713746e-01 6.13720894e-01 5.65761983e-01 3.27470601e-01 8.45057487e-01 -6.61280811e-01 -8.13400686e-01 9.08051372e-01 -3.03220768e-02 2.69849330e-01 7.34367251e-01 1.09088480e-01 1.34615803e+00 -6.71143711e-01 8.41575861e-01 1.23769999e+00 4.21043217e-01 7.87408173e-01 -1.39447904e+00 3.55197750e-02 7.44543150e-02 3.42423171e-02 -7.96391666e-01 -7.19038606e-01 4.88708854e-01 -1.03918202e-01 1.23203635e+00 5.75161695e-01 2.25954741e-01 1.00759840e+00 1.21909417e-01 1.13106406e+00 5.27527630e-01 -5.88634789e-01 2.19757915e-01 1.99795231e-01 3.02992970e-01 3.48266721e-01 5.28957844e-02 -5.05901873e-01 -4.97338206e-01 -1.93978056e-01 3.07044655e-01 -5.55431962e-01 -4.82331991e-01 -1.62543535e-01 -1.17404389e+00 9.50755119e-01 -3.47270556e-02 2.68328756e-01 -3.49479616e-01 -1.45246223e-01 4.55422670e-01 5.07410824e-01 4.86307889e-01 1.50186753e+00 -7.59022117e-01 -3.73356909e-01 -1.13285470e+00 5.70205748e-01 1.39458513e+00 1.27534890e+00 5.32762706e-01 8.49197507e-02 -9.02701914e-01 1.09026730e+00 -3.51181746e-01 6.33953154e-01 7.17343986e-01 -1.36047006e+00 8.40747356e-01 7.09296107e-01 2.56840080e-01 -5.80244362e-01 -2.40421534e-01 -5.87360978e-01 -5.69141448e-01 -7.12080181e-01 1.25676900e-01 -4.78263527e-01 -8.25082481e-01 1.67704916e+00 -1.55021995e-01 -4.92543489e-01 5.27510226e-01 5.49630165e-01 9.77742612e-01 9.03678894e-01 -2.29084849e-01 -5.57291508e-01 1.23185730e+00 -1.30678725e+00 -8.44458044e-01 -5.70626795e-01 6.10833228e-01 -6.80376709e-01 1.52219057e+00 2.55949318e-01 -1.49452806e+00 -4.28084075e-01 -8.54839325e-01 -4.22718555e-01 9.76549089e-02 2.18890101e-01 1.74751878e-01 2.65010417e-01 -1.01131999e+00 3.96706343e-01 -5.70824146e-01 -6.10045373e-01 1.12735100e-01 2.01773524e-01 5.60322218e-02 -1.60583436e-01 -1.17715669e+00 1.01326740e+00 4.46570992e-01 -4.46166337e-01 -8.97329509e-01 -6.07185245e-01 -8.43904734e-01 5.11410594e-01 7.72177041e-01 -1.12424421e+00 2.11178637e+00 -7.22247005e-01 -1.71591461e+00 4.63418990e-01 -2.01029360e-01 -6.42124772e-01 2.74123520e-01 -5.63566148e-01 -3.28512490e-02 5.79250455e-01 2.43235484e-01 7.95696914e-01 6.38313711e-01 -1.13238180e+00 -4.61702526e-01 -2.18826346e-02 3.83747786e-01 5.39062262e-01 -5.15125751e-01 -1.53831586e-01 -4.46262926e-01 -5.05367041e-01 -3.02733958e-01 -6.28848374e-01 -3.38589787e-01 -8.23059201e-01 -6.93584502e-01 -4.21253502e-01 4.75480556e-01 -5.96283197e-01 1.33497524e+00 -1.52210450e+00 2.83491075e-01 -2.15349481e-01 -7.65342712e-02 3.41294855e-01 -5.51440120e-01 8.91705692e-01 3.53687406e-01 1.65642977e-01 -4.21130717e-01 -3.31546247e-01 1.10034212e-01 2.38365859e-01 -5.32573104e-01 -3.38649362e-01 4.22255427e-01 1.01769471e+00 -1.08971214e+00 -7.12285161e-01 -2.41617382e-01 -2.69352108e-01 -9.51054573e-01 6.43042564e-01 -1.00262153e+00 2.56276965e-01 -6.13259852e-01 2.77512252e-01 -1.58488620e-02 -3.01982731e-01 5.42804338e-02 -2.73183342e-02 2.35947773e-01 5.51102102e-01 -6.50070310e-01 1.91000414e+00 -6.98661685e-01 5.42727411e-01 -1.37956604e-01 -8.70577455e-01 7.15539873e-01 3.83177131e-01 1.41104057e-01 -7.27068543e-01 4.32784855e-02 1.12467520e-02 -2.28110522e-01 -8.55962813e-01 1.05560803e+00 2.22319975e-01 -3.76859337e-01 6.15185022e-01 4.17121083e-01 -9.02184367e-01 8.60143244e-01 6.88876867e-01 1.12955856e+00 -1.64524913e-01 3.76507372e-01 -1.32417127e-01 6.00154340e-01 3.88514906e-01 2.34728292e-01 1.24426591e+00 3.21097255e-01 7.60233462e-01 7.13964641e-01 1.62530258e-01 -8.42235804e-01 -7.50306189e-01 2.67954350e-01 1.49995136e+00 -2.58316398e-01 -7.82309473e-01 -1.07681823e+00 -7.84818351e-01 -1.72567651e-01 1.49465930e+00 -4.31488186e-01 -2.33627483e-01 -7.08456218e-01 -2.52434373e-01 4.96533066e-01 3.81317884e-01 3.80756944e-01 -1.13815916e+00 -6.21734023e-01 4.02175844e-01 -6.40189528e-01 -1.11559927e+00 -9.17593300e-01 -1.34904264e-02 -9.50471699e-01 -1.03565228e+00 -5.95177889e-01 -6.87904596e-01 5.92202663e-01 9.96676013e-02 1.54008603e+00 -1.90445647e-01 1.73275679e-01 8.12396646e-01 -4.40994203e-01 -4.00799960e-01 -8.46522331e-01 7.54186928e-01 -3.67375284e-01 -3.86826932e-01 -7.96432048e-02 -4.24287379e-01 -3.93789083e-01 1.53713286e-01 -1.15564573e+00 7.27895126e-02 7.38015532e-01 1.04214513e+00 3.30936402e-01 -5.12353420e-01 1.03961599e+00 -1.31049502e+00 1.43851340e+00 -2.85328448e-01 -1.95902556e-01 7.42413640e-01 -6.41816616e-01 4.17387903e-01 7.86922097e-01 -4.11026806e-01 -1.26249290e+00 -1.70946240e-01 -3.63278687e-02 1.20711904e-02 -3.85216773e-02 8.97402346e-01 -9.57250893e-02 4.98000175e-01 1.22159803e+00 2.44465336e-01 -9.34867933e-02 -2.64966547e-01 8.72228920e-01 7.26525426e-01 7.64227688e-01 -8.30684006e-01 4.38211322e-01 -1.31521046e-01 -6.37374997e-01 -8.42258811e-01 -1.35795963e+00 -5.32366991e-01 -3.94340515e-01 -2.70073954e-02 6.88595295e-01 -6.55170083e-01 -2.51094788e-01 -1.30811527e-01 -1.32906425e+00 -4.94574577e-01 -7.34594941e-01 1.12812176e-01 -9.10805225e-01 3.60797554e-01 -6.25311196e-01 -6.48230851e-01 -8.84595037e-01 -7.92251170e-01 1.06750619e+00 3.31189126e-01 -6.43793643e-01 -9.43125427e-01 3.18740726e-01 7.25744307e-01 5.41600704e-01 -4.13784124e-02 1.03511238e+00 -1.31322193e+00 -3.06210756e-01 -3.56158555e-01 4.35463153e-02 5.01940429e-01 2.37960443e-01 -2.44694605e-01 -5.70139110e-01 -1.89805999e-01 1.77907333e-01 -1.03582561e+00 8.65059674e-01 1.08564503e-01 9.72122312e-01 -9.79047358e-01 8.71007666e-02 -6.25648582e-03 8.67588401e-01 -1.75233230e-01 3.80103707e-01 9.49307904e-02 3.80788684e-01 7.70049572e-01 6.55806839e-01 3.65702003e-01 5.75284064e-01 4.25869048e-01 5.32445833e-02 2.31596753e-01 3.08531914e-02 -4.66168076e-01 2.37280637e-01 1.01986480e+00 2.89251417e-01 -7.21729577e-01 -7.13903010e-01 7.54184008e-01 -2.01618195e+00 -9.63353038e-01 9.34362113e-02 1.75998616e+00 1.50250268e+00 1.85475901e-01 -3.62949781e-02 -3.81728053e-01 3.44907433e-01 1.56542107e-01 -6.94305658e-01 -4.87042099e-01 -1.28055178e-02 2.94196427e-01 1.05666198e-01 5.62834859e-01 -7.98550248e-01 1.12652433e+00 6.61318779e+00 7.27919221e-01 -7.73055017e-01 2.28255596e-02 4.66769755e-01 -1.76447123e-01 -6.20934308e-01 -5.92141971e-02 -5.14175475e-01 3.67183052e-02 1.22123003e+00 -6.11033916e-01 2.85458952e-01 8.14553976e-01 3.55383098e-01 -1.74691513e-01 -1.49300945e+00 3.86240691e-01 4.76911575e-01 -1.43894613e+00 5.21342278e-01 -4.28909063e-01 9.82084334e-01 -2.15040579e-01 -1.35582730e-01 7.54075229e-01 5.94032705e-01 -9.10916865e-01 4.52484548e-01 4.97461557e-01 5.52394390e-01 -6.35705888e-01 7.93013752e-01 8.85416269e-01 -4.11177546e-01 -2.00743414e-02 -3.20508778e-01 6.62904754e-02 3.05317223e-01 7.64076486e-02 -1.28244483e+00 6.93684101e-01 5.05595021e-02 4.49824572e-01 -7.69630373e-01 7.30734944e-01 -4.73276019e-01 8.65567923e-01 -5.85305765e-02 -2.73673236e-01 2.97551304e-01 1.26155451e-01 5.70582390e-01 1.45050693e+00 -7.26356879e-02 3.76502693e-01 3.92176300e-01 6.84052467e-01 -3.02983761e-01 2.86776274e-01 -3.76122028e-01 -3.09756666e-01 3.54507625e-01 1.07522511e+00 -1.17085241e-01 -6.42559290e-01 1.78496167e-02 8.95057738e-01 4.19817805e-01 5.01808584e-01 -3.18305254e-01 -4.64577526e-01 -1.25556186e-01 -3.27959210e-02 2.62468815e-01 -3.20608914e-02 -2.37076700e-01 -1.38043845e+00 -1.64423138e-01 -1.48843288e+00 5.75451732e-01 -8.76080811e-01 -1.06199455e+00 7.41034329e-01 2.50262022e-01 -9.14432883e-01 -9.36108291e-01 -3.32947150e-02 -7.59764612e-01 5.66111147e-01 -1.31775534e+00 -9.38311875e-01 -1.34146005e-01 4.03444052e-01 1.14803088e+00 -1.34643480e-01 9.30519700e-01 -1.77055359e-01 -4.69098687e-01 5.68006277e-01 9.92305428e-02 -1.16943561e-01 1.03319561e+00 -1.59004140e+00 3.36017966e-01 7.54681468e-01 1.64007545e-01 7.84713745e-01 1.06788576e+00 -5.47761679e-01 -1.29359210e+00 -1.11313009e+00 1.07013130e+00 -5.77314436e-01 5.48325419e-01 -1.67016611e-01 -9.83085752e-01 6.57655120e-01 8.71659160e-01 -7.11234629e-01 7.50509739e-01 1.01714261e-01 -1.12966627e-01 -8.74038339e-02 -9.73573089e-01 5.34275353e-01 7.69500792e-01 -4.67775494e-01 -1.31977224e+00 8.46398652e-01 1.05275559e+00 -7.43773818e-01 -6.45883977e-01 3.01180065e-01 1.20683327e-01 -5.96154690e-01 5.79456031e-01 -1.12479722e+00 7.96495140e-01 1.87504873e-01 5.45388162e-02 -1.55138958e+00 -9.41705555e-02 -8.91188920e-01 -3.09664607e-01 1.24448991e+00 8.20211887e-01 -2.21131504e-01 6.28023922e-01 6.49700820e-01 -6.03710711e-01 -7.43512630e-01 -5.29551148e-01 -5.59834540e-01 1.72098830e-01 2.63830405e-02 3.21593434e-01 5.83190560e-01 3.00786406e-01 1.06572258e+00 -2.37750322e-01 -1.72195643e-01 1.73105136e-01 2.46530995e-01 1.00152636e+00 -8.83654237e-01 -3.50273371e-01 -3.49066794e-01 4.36075151e-01 -1.51074409e+00 2.06910506e-01 -7.40970254e-01 3.63507390e-01 -2.10640478e+00 1.08912975e-01 1.88963801e-01 2.22890779e-01 4.38980579e-01 -4.72567230e-01 -2.40653560e-01 2.33612925e-01 2.08172426e-01 -1.15656590e+00 8.03385317e-01 1.36219764e+00 -3.83975565e-01 -4.72699016e-01 1.92787707e-01 -1.10107684e+00 4.43664670e-01 7.33217180e-01 -2.55995601e-01 -8.49628389e-01 -6.63750529e-01 7.08261505e-02 5.41568458e-01 -1.97242334e-01 -8.13490510e-01 4.99399006e-01 -2.58938402e-01 -2.06573959e-02 -7.19076931e-01 2.06966937e-01 -1.85238317e-01 -5.64357519e-01 1.61600828e-01 -1.14796841e+00 1.48021683e-01 2.79893309e-01 4.84475702e-01 -3.40616703e-01 -6.12735689e-01 4.26622272e-01 -2.99372286e-01 -9.32417065e-02 -7.60064572e-02 -5.66815913e-01 9.68262792e-01 4.57032859e-01 8.45268518e-02 -5.01934707e-01 -1.00391471e+00 -4.99690861e-01 9.29238379e-01 2.14829609e-01 2.79322833e-01 5.63079834e-01 -8.21092844e-01 -1.15968120e+00 -3.38557482e-01 2.54993349e-01 2.62588382e-01 1.51914954e-01 3.13332826e-01 -3.33435059e-01 8.46426308e-01 1.76578552e-01 -5.28635800e-01 -9.93716061e-01 3.13034534e-01 1.55931473e-01 -7.84760654e-01 -1.76542968e-01 7.24028111e-01 2.16258410e-02 -6.30341172e-01 3.29417527e-01 -5.91824651e-01 -5.29860139e-01 1.84891358e-01 4.99040216e-01 1.52981415e-01 2.16630399e-01 -2.08258945e-02 1.48089945e-01 8.87834430e-02 -5.43136477e-01 -4.05027241e-01 1.11955297e+00 -5.09722754e-02 3.31680253e-02 2.98464805e-01 8.20193410e-01 1.67963192e-01 -1.09677553e+00 -3.76205444e-01 2.57195950e-01 4.26291600e-02 -3.14413399e-01 -1.18129659e+00 -4.52809960e-01 5.85777402e-01 -3.21412653e-01 4.61893380e-01 1.00411475e+00 9.05306116e-02 8.73326182e-01 1.15244353e+00 -1.17877267e-01 -1.16511667e+00 7.10107267e-01 9.11089540e-01 1.39966369e+00 -8.44914615e-01 3.79480310e-02 -2.41762698e-01 -9.96245325e-01 1.06969893e+00 9.66947496e-01 1.32534534e-01 -2.25513220e-01 -2.66591132e-01 1.35944011e-02 -3.03760115e-02 -1.26015282e+00 -4.49304134e-02 4.43796843e-01 4.57309574e-01 3.66461217e-01 -3.01805347e-01 -2.77323306e-01 5.94317913e-01 -6.69773042e-01 -9.68863294e-02 8.55912626e-01 1.01118481e+00 -6.67853177e-01 -1.07201171e+00 -8.12933072e-02 7.27903306e-01 -2.64767796e-01 -2.58676052e-01 -8.47990930e-01 6.33934438e-01 -5.26045442e-01 1.36287248e+00 -9.28201303e-02 6.48770556e-02 8.56308103e-01 1.52675018e-01 4.63703454e-01 -1.33062446e+00 -8.82177949e-01 -1.07342519e-01 6.75480366e-01 -1.42788053e-01 -1.93209156e-01 -5.76663852e-01 -9.95593667e-01 1.24335721e-01 -5.26460648e-01 7.92863965e-01 2.12102175e-01 1.07256866e+00 6.76933587e-01 6.49262071e-01 6.47929490e-01 -4.01839465e-01 -1.33928490e+00 -1.41417992e+00 1.03983626e-01 3.91412258e-01 3.11813772e-01 -5.47136255e-02 -1.72543526e-01 2.56574512e-01]	[12.214491844177246, 9.063788414001465]
43098628-f6e6-49ad-8dc7-275f21a406f3	analysis-of-task-transferability-in-large-pre	2307.00823	null	https://arxiv.org/abs/2307.00823v1	https://arxiv.org/pdf/2307.00823v1.pdf	Analysis of Task Transferability in Large Pre-trained Classifiers	Transfer learning transfers the knowledge acquired by a model from a source task to multiple downstream target tasks with minimal fine-tuning. The success of transfer learning at improving performance, especially with the use of large pre-trained models has made transfer learning an essential tool in the machine learning toolbox. However, the conditions under which the performance is transferable to downstream tasks are not understood very well. In this work, we analyze the transfer of performance for classification tasks, when only the last linear layer of the source model is fine-tuned on the target task. We propose a novel Task Transfer Analysis approach that transforms the source distribution (and classifier) by changing the class prior distribution, label, and feature spaces to produce a new source distribution (and classifier) and allows us to relate the loss of the downstream task (i.e., transferability) to that of the source task. Concretely, our bound explains transferability in terms of the Wasserstein distance between the transformed source and downstream task's distribution, conditional entropy between the label distributions of the two tasks, and weighted loss of the source classifier on the source task. Moreover, we propose an optimization problem for learning the transforms of the source task to minimize the upper bound on transferability. We perform a large-scale empirical study by using state-of-the-art pre-trained models and demonstrate the effectiveness of our bound and optimization at predicting transferability. The results of our experiments demonstrate how factors such as task relatedness, pretraining method, and model architecture affect transferability.	['Jihun Hamm', 'Yunbei Zhang', 'Akshay Mehra']	2023-07-03	null	null	null	null	['transfer-learning']	['miscellaneous']	[ 4.96040821e-01 7.84044564e-02 3.25930342e-02 -4.72415954e-01 -7.72929788e-01 -6.91953659e-01 6.17266119e-01 1.59243017e-01 -5.90636432e-01 6.12728179e-01 -2.96897255e-03 -1.72998384e-01 -3.22173834e-01 -6.03181481e-01 -9.53637600e-01 -8.16488504e-01 4.40087616e-02 3.39855611e-01 2.63870656e-01 -1.30727232e-01 6.58575669e-02 2.33198598e-01 -1.14873719e+00 3.90066832e-01 1.11673725e+00 1.03364909e+00 4.74956185e-01 4.40589577e-01 3.35278153e-01 4.19625580e-01 -4.93076324e-01 -4.51170206e-01 2.98552483e-01 -7.18410730e-01 -9.42584097e-01 -2.42814094e-01 3.33071738e-01 -9.40470845e-02 7.09389523e-02 8.93304646e-01 3.29366356e-01 2.47762248e-01 1.34675872e+00 -1.38657880e+00 -8.97791803e-01 3.51616383e-01 -3.37487668e-01 1.86613783e-01 -2.75851011e-01 -9.93102696e-03 8.78055513e-01 -8.72311294e-01 4.26104337e-01 1.02646315e+00 8.03889513e-01 4.49852496e-01 -1.36870706e+00 -8.04046810e-01 7.00221732e-02 1.23586908e-01 -1.17140162e+00 -4.29354370e-01 3.46037149e-01 -8.77630115e-01 7.29791820e-01 -2.77482569e-01 3.15707654e-01 1.10547006e+00 5.72843671e-01 4.59393352e-01 1.22235477e+00 -5.99630415e-01 1.75815493e-01 7.29656696e-01 1.46648929e-01 5.04217267e-01 1.20910980e-01 2.46158779e-01 -5.14754832e-01 9.71712619e-02 5.52595437e-01 -2.37985998e-01 -3.85410160e-01 -7.99307168e-01 -1.05716288e+00 8.39774013e-01 6.19692087e-01 4.35551822e-01 -1.88619673e-01 4.43890132e-02 3.22070509e-01 6.13593757e-01 8.58514369e-01 5.03764331e-01 -7.50171185e-01 9.56062526e-02 -5.16000330e-01 -1.88536480e-01 6.42081738e-01 9.16814804e-01 8.53956878e-01 -3.62446129e-01 -5.50615549e-01 8.16488147e-01 1.09273508e-01 4.46242541e-01 6.53045774e-01 -6.96605265e-01 7.10014045e-01 4.51448023e-01 -6.98557124e-02 -5.53504646e-01 -2.27277294e-01 -7.88826585e-01 -3.73657674e-01 1.22504301e-01 7.93722928e-01 -3.57205898e-01 -5.17273843e-01 2.15015268e+00 1.69958115e-01 -6.99900687e-02 8.93911868e-02 6.06161296e-01 7.72885680e-02 5.21431804e-01 2.74129331e-01 -1.50141791e-01 9.19633567e-01 -8.84603560e-01 -3.27446014e-01 -4.10715550e-01 1.10785019e+00 -6.47098601e-01 1.43685734e+00 3.23066674e-02 -8.60294104e-01 -7.62379825e-01 -9.96053040e-01 1.63726937e-02 -2.49497652e-01 7.72895515e-02 1.37062877e-01 5.02906740e-01 -8.84616673e-01 8.49080622e-01 -6.58190668e-01 -4.17886287e-01 4.93773758e-01 4.25330937e-01 -3.27868253e-01 -6.55205101e-02 -1.18927133e+00 1.39377463e+00 4.60154355e-01 -4.37015772e-01 -1.09490120e+00 -1.10451746e+00 -5.57096601e-01 5.07831097e-01 6.98556751e-02 -8.01796973e-01 1.27292991e+00 -1.23281872e+00 -1.42164695e+00 8.08769941e-01 1.39868498e-01 -1.66295066e-01 5.65427303e-01 -1.35661498e-01 9.70500484e-02 -2.80691832e-01 9.45108384e-02 6.62393212e-01 1.10710382e+00 -9.91618454e-01 -8.85915637e-01 -4.70039159e-01 -2.44597480e-01 3.63837838e-01 -8.68948221e-01 -3.44178468e-01 -3.59345786e-02 -3.80807370e-01 -4.53831255e-01 -1.01494789e+00 3.31707239e-01 -5.74467480e-02 1.36883587e-01 -4.35896039e-01 4.45558220e-01 -6.17439091e-01 7.44332314e-01 -2.56276083e+00 3.47668886e-01 6.85880780e-02 -2.14293925e-03 1.41973451e-01 -5.13947248e-01 1.99675083e-01 -1.94850236e-01 1.49246622e-02 -2.05532476e-01 -2.33993560e-01 2.19362285e-02 -2.72972673e-01 -2.28342816e-01 5.13358235e-01 1.13475293e-01 7.99106240e-01 -9.27947700e-01 -1.78016439e-01 -8.13894495e-02 4.46852207e-01 -5.70239305e-01 4.87446219e-01 1.43824697e-01 6.23517752e-01 -2.79596120e-01 -2.71138370e-01 2.60732383e-01 -1.58122763e-01 -4.41759117e-02 -1.37346923e-01 2.86880493e-01 1.98243842e-01 -5.32521367e-01 1.51804030e+00 -8.97853196e-01 6.05545700e-01 -8.65640566e-02 -1.10664630e+00 9.93198216e-01 1.59938067e-01 1.63722217e-01 -6.33325100e-01 9.11338404e-02 2.63204992e-01 4.30829883e-01 -3.24580669e-01 -1.06502943e-01 -6.10926330e-01 4.58588488e-02 5.29146850e-01 4.50380504e-01 -3.94615568e-02 -8.36885422e-02 -2.57423580e-01 8.65220964e-01 2.64755905e-01 1.73342258e-01 -4.92838234e-01 2.03053102e-01 -8.40186477e-02 2.34281376e-01 6.21074259e-01 -3.98227274e-01 2.62189507e-01 6.02411568e-01 1.03065938e-01 -8.83738816e-01 -1.12779522e+00 -1.13871701e-01 1.75845206e+00 -1.62516683e-01 1.60425827e-01 -9.36708987e-01 -9.29218054e-01 1.73425838e-01 1.00265861e+00 -9.26578045e-01 -1.03421426e+00 -3.73558879e-01 -5.41662753e-01 3.92265052e-01 6.18091643e-01 3.95853370e-01 -8.74916375e-01 -3.60817164e-01 -1.00402214e-01 -1.91739634e-01 -9.32489812e-01 -6.69800162e-01 3.81592989e-01 -1.11102080e+00 -9.72247481e-01 -7.92903543e-01 -9.08133328e-01 6.92624986e-01 5.53867742e-02 8.38252485e-01 -3.82348537e-01 1.47484541e-01 3.02404314e-01 -1.30602270e-01 -3.99051845e-01 -4.82923776e-01 5.06563425e-01 -5.07414117e-02 2.04306811e-01 2.12549150e-01 -3.71507406e-01 -3.48930687e-01 5.30942976e-01 -6.96205795e-01 -8.60062614e-02 7.08976269e-01 7.43629813e-01 2.53242880e-01 -2.36403737e-02 9.02073562e-01 -8.71075392e-01 8.74103427e-01 -5.52964568e-01 -4.11097944e-01 5.99300563e-01 -8.35215330e-01 3.33388746e-01 5.27101040e-01 -6.35145664e-01 -1.35911787e+00 -2.53503211e-02 4.85310823e-01 -3.92854840e-01 7.37426803e-02 5.29774666e-01 -1.72423467e-01 1.12917840e-01 1.00912392e+00 -8.38540047e-02 2.19464079e-01 -3.88331056e-01 4.35155243e-01 6.73191547e-01 2.33570993e-01 -6.46066606e-01 8.77117872e-01 1.62597179e-01 -1.02261223e-01 -4.13488328e-01 -1.23505723e+00 -2.11843103e-01 -9.67812717e-01 -4.56555653e-03 9.56268430e-01 -7.47837722e-01 -4.57891375e-01 4.67537433e-01 -9.63935554e-01 -9.54798639e-01 -3.95216852e-01 6.04466021e-01 -7.18206286e-01 -2.41831213e-01 -2.25204647e-01 -4.16496217e-01 2.90690176e-02 -1.08974004e+00 8.51205945e-01 -1.29477680e-01 -3.47697765e-01 -1.55057073e+00 8.82223696e-02 1.84394717e-01 5.61069727e-01 -1.11887552e-01 1.39632618e+00 -9.62118208e-01 -1.03540301e-01 8.41384381e-02 -2.74066806e-01 7.67794609e-01 3.46257329e-01 -5.36699355e-01 -1.01156783e+00 -4.79138017e-01 3.98248523e-01 -4.75190103e-01 9.99729097e-01 5.29191136e-01 8.97710323e-01 -6.28360808e-02 -4.27883506e-01 6.09648287e-01 1.17862630e+00 3.62660587e-02 3.44094932e-01 3.67723942e-01 5.15257299e-01 1.04290473e+00 6.93735182e-01 -1.19485974e-01 8.33246037e-02 6.61607385e-01 -5.03473058e-02 2.12040573e-01 -2.97219127e-01 -3.31760705e-01 6.76938355e-01 5.95865071e-01 1.31078005e-01 -1.70448292e-02 -1.01303816e+00 5.06091952e-01 -1.69856727e+00 -5.29517233e-01 1.96648180e-01 2.50631857e+00 1.01231670e+00 7.63028264e-02 -4.45934236e-02 -1.31430537e-01 8.15599501e-01 -3.99104208e-01 -5.60823202e-01 -2.21453935e-01 4.23253387e-01 8.47435594e-02 3.63246351e-01 7.21265674e-01 -9.94875133e-01 8.02993774e-01 6.18281317e+00 8.15119565e-01 -1.01936328e+00 3.87422234e-01 6.01043582e-01 -4.07442600e-02 -5.23060039e-02 -1.58260316e-01 -7.99107850e-01 2.85142720e-01 1.16397166e+00 -4.67517287e-01 4.16226596e-01 7.97367215e-01 -7.52617419e-02 1.10039942e-01 -1.92351091e+00 5.29767156e-01 7.76190087e-02 -6.57337070e-01 -6.39432520e-02 1.46707162e-01 7.59757042e-01 -8.21565390e-02 4.98266131e-01 8.29121113e-01 7.39169717e-02 -9.96628344e-01 6.32363200e-01 2.38529190e-01 8.94093513e-01 -6.77761614e-01 7.25257158e-01 5.82145691e-01 -7.54954278e-01 -2.22827256e-01 -3.58569831e-01 -1.24278463e-01 -3.26533198e-01 4.14612710e-01 -1.10169005e+00 6.38291687e-02 5.36168337e-01 5.27901530e-01 -6.71160877e-01 6.64831877e-01 -3.04681629e-01 5.51528990e-01 1.04084976e-01 1.36168614e-01 -1.19625822e-01 -1.87349319e-01 2.35824436e-01 1.13926220e+00 4.00403529e-01 -2.95703024e-01 1.73259284e-02 9.44577992e-01 -2.70387530e-01 1.09260932e-01 -7.62822509e-01 4.39505540e-02 4.55314577e-01 1.03104854e+00 -3.94405067e-01 -1.06079400e-01 -2.26657555e-01 8.98557603e-01 7.65381038e-01 5.67898571e-01 -7.79143393e-01 -4.44326460e-01 5.67426205e-01 2.08972096e-01 3.23217064e-01 5.53057231e-02 -5.57023227e-01 -8.66681039e-01 3.24635729e-02 -6.12561882e-01 2.67256349e-01 -5.98301589e-01 -1.55776143e+00 4.27597344e-01 2.61222631e-01 -1.01129603e+00 -2.74651676e-01 -6.07204676e-01 -5.55986941e-01 1.24441278e+00 -1.52258813e+00 -1.01691890e+00 -2.29792714e-01 6.39773250e-01 3.47945094e-01 -3.92567664e-01 7.19478548e-01 2.05787614e-01 -3.24056447e-01 9.29669201e-01 2.88903087e-01 6.04926869e-02 1.16331363e+00 -1.05323923e+00 1.43194534e-02 3.76674086e-01 -2.81189054e-01 4.42243367e-01 4.84736174e-01 -5.01688421e-01 -8.12311947e-01 -1.28277886e+00 8.40344071e-01 -7.32906878e-01 7.42824733e-01 -4.48748648e-01 -8.77130985e-01 9.47387218e-01 -4.76929545e-02 -1.88871607e-01 7.60360003e-01 4.70639437e-01 -5.36274552e-01 -3.38319749e-01 -9.95002806e-01 3.52958620e-01 9.55456793e-01 -6.07895672e-01 -7.54500985e-01 3.14426124e-01 7.10501790e-01 -7.45813549e-02 -8.98743749e-01 2.79246747e-01 4.95154023e-01 -7.79887617e-01 7.34266281e-01 -7.20594704e-01 6.07704878e-01 2.76501298e-01 -8.36143941e-02 -1.97381175e+00 -5.18456638e-01 2.51926184e-02 1.90519363e-01 1.26401317e+00 6.76159382e-01 -7.30414748e-01 3.41299623e-01 5.16213298e-01 -1.51724786e-01 -5.81642747e-01 -8.06195557e-01 -1.10935092e+00 6.92731917e-01 -6.58362582e-02 1.02249637e-01 8.97443771e-01 -9.16543826e-02 8.51428747e-01 8.83727074e-02 -1.75356999e-01 5.22507071e-01 -6.12258650e-02 4.75286096e-01 -1.42264020e+00 -3.50719273e-01 -4.54210013e-01 -3.73302214e-02 -6.96034133e-01 5.60501218e-01 -1.34924161e+00 2.39673719e-01 -1.15531051e+00 4.29124296e-01 -6.32560909e-01 -5.09476364e-01 6.35455072e-01 -3.46132755e-01 -1.16152622e-01 3.91161144e-01 4.47036803e-01 -2.12726980e-01 6.36005580e-01 1.36843860e+00 -4.18300293e-02 -3.81346136e-01 1.47689492e-01 -7.41983712e-01 6.52970970e-01 8.13787401e-01 -8.68951619e-01 -7.29177654e-01 -6.90044045e-01 6.68187588e-02 -2.33074099e-01 2.14372456e-01 -8.36559117e-01 -3.66152599e-02 -4.49358560e-02 4.89933163e-01 4.13105547e-01 2.94468015e-01 -8.72349203e-01 -3.21782142e-01 6.15432620e-01 -8.28887045e-01 -3.08881998e-01 1.88304618e-01 6.33760989e-01 -2.54555643e-02 -4.81408566e-01 1.06243479e+00 3.49612504e-01 -2.27095276e-01 1.18923429e-02 -1.11150436e-01 3.27966303e-01 1.19375408e+00 -3.10299974e-02 -3.96938473e-01 -3.09921890e-01 -8.75387549e-01 4.29926477e-02 3.32417399e-01 5.29086113e-01 1.90168738e-01 -1.28087842e+00 -9.41510558e-01 2.33189166e-01 1.36800110e-01 -3.84205192e-01 -7.89203346e-02 9.45697069e-01 1.08543620e-01 4.13680106e-01 -6.17906392e-01 -6.13295674e-01 -9.47466791e-01 4.76286948e-01 4.18914795e-01 -5.07103801e-01 -5.31675331e-02 8.41230571e-01 9.03430045e-01 -5.98494351e-01 2.58955300e-01 -2.82865435e-01 -5.45366667e-02 3.11533272e-01 1.86814621e-01 4.78309900e-01 2.62926966e-01 -2.20401257e-01 -2.30995938e-01 5.52806675e-01 -1.40579179e-01 -1.99126229e-01 1.32104731e+00 -5.92549443e-02 4.66698483e-02 6.94855154e-01 1.61584198e+00 -4.93934214e-01 -1.54893553e+00 -3.23166966e-01 2.68498454e-02 -2.11927295e-01 2.28704400e-02 -8.35978210e-01 -8.25130105e-01 1.16751146e+00 7.03697920e-01 -6.74985126e-02 1.03279126e+00 1.34588569e-01 4.08455461e-01 4.13244933e-01 1.84594736e-01 -1.06906676e+00 4.23462987e-01 7.84274817e-01 9.96017575e-01 -1.19647026e+00 -3.55823457e-01 -3.89182121e-01 -7.56088138e-01 7.40332425e-01 7.44621933e-01 -1.06201023e-01 7.24628448e-01 -4.50211205e-02 -1.12687007e-01 5.66314906e-02 -7.36673176e-01 1.13047749e-01 5.36775410e-01 8.14193606e-01 4.39210057e-01 -3.12327035e-02 5.01463376e-02 6.30608737e-01 -1.46222860e-01 6.84269071e-02 1.44176453e-01 7.15826690e-01 -5.24010539e-01 -9.18336451e-01 -1.95270002e-01 4.12270755e-01 -1.30127177e-01 -1.48216829e-01 -4.72332150e-01 7.69498885e-01 8.26535374e-02 7.41997898e-01 1.31649673e-01 -3.22275579e-01 3.71134549e-01 5.47971249e-01 6.94963396e-01 -1.02267540e+00 -6.10576332e-01 -2.91712433e-01 -2.02425972e-01 -2.36484095e-01 -1.18037544e-01 -3.90898436e-01 -8.51635098e-01 -3.36689427e-02 -3.72267723e-01 2.35517040e-01 6.30760133e-01 1.17385375e+00 3.56083006e-01 6.24181032e-01 5.73395729e-01 -6.94341063e-01 -1.17454123e+00 -1.29360831e+00 -5.00110209e-01 5.50785124e-01 2.51445472e-01 -8.28992307e-01 -4.99708652e-01 3.09665561e-01]	[9.774170875549316, 3.240222930908203]
94c4c9f6-e77a-449e-beb1-08bb065dde1e	effect-of-personalized-calibration-on-gaze	2109.12801	null	https://arxiv.org/abs/2109.12801v1	https://arxiv.org/pdf/2109.12801v1.pdf	Effect Of Personalized Calibration On Gaze Estimation Using Deep-Learning	With the increase in computation power and the development of new state-of-the-art deep learning algorithms, appearance-based gaze estimation is becoming more and more popular. It is believed to work well with curated laboratory data sets, however it faces several challenges when deployed in real world scenario. One such challenge is to estimate the gaze of a person about which the Deep Learning model trained for gaze estimation has no knowledge about. To analyse the performance in such scenarios we have tried to simulate a calibration mechanism. In this work we use the MPIIGaze data set. We trained a multi modal convolutional neural network and analysed its performance with and without calibration and this evaluation provides clear insights on how calibration improved the performance of the Deep Learning model in estimating gaze in the wild.	['Didier Schwab', 'Sébastien Riou', 'Nairit Bandyopadhyay']	2021-09-27	null	null	null	null	['gaze-estimation']	['computer-vision']	[-9.25377533e-02 9.78191644e-02 4.46707457e-01 -5.40917277e-01 6.04073480e-02 -3.37212145e-01 3.27143371e-01 -1.83882162e-01 -7.63279974e-01 6.48883522e-01 -2.05607340e-01 5.04235663e-02 -2.53714994e-02 -2.50710666e-01 -8.16630781e-01 -5.95842600e-01 9.75652039e-02 3.33124429e-01 1.04702435e-01 -1.13745928e-01 2.79729635e-01 2.12831318e-01 -2.00792742e+00 -7.83339739e-02 5.26714265e-01 8.63354504e-01 1.33907702e-03 8.43448937e-01 2.97619373e-01 6.43116534e-01 -7.68159747e-01 -4.94628400e-01 2.31153429e-01 -1.40359312e-01 -7.92587042e-01 -1.75998271e-01 1.14998996e+00 -4.29761738e-01 6.62160143e-02 9.45813775e-01 7.23878622e-01 -1.83425963e-01 5.10040581e-01 -1.67258847e+00 -1.76630482e-01 2.11546887e-02 -9.04949665e-01 4.71654892e-01 3.56161952e-01 2.24074930e-01 4.50474977e-01 -3.21661502e-01 6.07101262e-01 9.42543268e-01 7.57469118e-01 6.09776974e-01 -1.03399408e+00 -8.41918051e-01 -4.39892747e-02 3.61493915e-01 -1.30065441e+00 -6.16244733e-01 5.35337567e-01 -4.22619730e-01 7.81543195e-01 -1.50144547e-01 5.34751236e-01 1.23714077e+00 -2.32519880e-02 5.29464126e-01 1.71973801e+00 -5.90152264e-01 -3.59782577e-02 4.88993973e-01 1.64729208e-01 7.35166490e-01 2.76879132e-01 2.59910468e-02 -7.08462894e-01 2.27762803e-01 5.41092992e-01 -2.67049462e-01 -3.84321243e-01 -3.51277202e-01 -7.40267932e-01 6.10643148e-01 7.37146080e-01 2.83979058e-01 -3.92399579e-01 2.51144350e-01 2.21657678e-01 1.94325924e-01 5.58900893e-01 3.10834855e-01 -5.27512550e-01 -4.39229071e-01 -1.07914257e+00 2.75618941e-01 7.02742517e-01 5.60811996e-01 6.95341289e-01 -2.60328233e-01 1.67770088e-01 6.55551791e-01 5.09189487e-01 5.67458868e-01 2.93705374e-01 -8.22738171e-01 1.33624971e-01 7.69247055e-01 1.83984742e-01 -8.81823123e-01 -7.25292563e-01 -2.74456739e-01 -3.97180349e-01 9.40056205e-01 1.03522265e+00 -4.49326932e-01 -9.45900023e-01 1.87530828e+00 3.15583497e-01 2.19434917e-01 -2.84475327e-01 1.05647111e+00 7.35459507e-01 1.35911480e-01 1.66278526e-01 4.87352759e-02 1.34297395e+00 -6.08596206e-01 -5.97898781e-01 -3.15656364e-01 4.34589893e-01 -8.00917029e-01 9.45644438e-01 5.97549736e-01 -8.25492144e-01 -6.56679928e-01 -1.03791976e+00 -3.11540887e-02 -5.43021202e-01 2.03714058e-01 7.57182837e-01 1.05556488e+00 -1.42803776e+00 3.63970250e-01 -6.88856542e-01 -8.65291953e-01 6.15630686e-01 7.69325078e-01 -6.34504080e-01 1.12682737e-01 -7.57015526e-01 1.13157678e+00 6.95962235e-02 2.97769547e-01 -7.34337270e-01 -5.09896159e-01 -6.13790035e-01 -5.58188297e-02 1.14048593e-01 -6.01391375e-01 1.21170163e+00 -1.70710218e+00 -1.44913328e+00 1.39404094e+00 -3.23695898e-01 -3.85132343e-01 6.81944668e-01 -3.51531148e-01 -2.75435507e-01 -1.24063700e-01 -3.50187361e-01 9.75957274e-01 9.98793304e-01 -1.26284027e+00 -6.16225302e-01 -7.85897851e-01 3.00843269e-01 3.67386900e-02 -9.90263373e-03 1.65448412e-01 -2.47786909e-01 1.91444084e-01 -2.59287298e-01 -1.25736105e+00 5.22344530e-01 2.23936960e-01 -1.33702308e-01 -3.58913243e-01 1.03591156e+00 -5.90553641e-01 9.17025685e-01 -1.76920223e+00 3.33201177e-02 5.75187393e-02 5.93154669e-01 6.02224588e-01 1.55265048e-01 1.91137284e-01 -2.76530445e-01 -1.91172734e-01 1.79043859e-01 -7.53240943e-01 -2.11223379e-01 -3.62506136e-02 1.25307530e-01 6.94276094e-01 6.91955686e-02 6.97119474e-01 -5.92153370e-01 -4.23185915e-01 2.50017434e-01 8.40805173e-01 -2.85122275e-01 4.73509908e-01 4.55865972e-02 5.77756703e-01 5.30989990e-02 4.69096124e-01 8.03457141e-01 -2.63196230e-01 -1.29067197e-01 -2.20899969e-01 -7.58029968e-02 -3.52187276e-01 -8.85399401e-01 1.57929683e+00 -4.67564642e-01 1.43343318e+00 -9.04723927e-02 -4.57559407e-01 5.38634896e-01 1.36413187e-01 5.44483848e-02 -8.62750649e-01 6.95988834e-01 -1.32639229e-01 4.25175816e-01 -8.58663857e-01 3.76101255e-01 6.05286621e-02 5.46438515e-01 4.62269545e-01 3.38220030e-01 4.71914679e-01 -1.47986844e-01 2.87873168e-02 8.58230293e-01 3.90040278e-01 -2.42744368e-02 -2.49057889e-01 5.11070251e-01 -3.09509963e-01 -5.49167618e-02 2.00347409e-01 -6.24635279e-01 5.70295691e-01 4.79625076e-01 -5.56164265e-01 -9.82888222e-01 -6.14923537e-01 -6.56679943e-02 1.24832153e+00 4.23331559e-03 -1.68144822e-01 -1.26281714e+00 -6.44814253e-01 -2.10362911e-01 4.53398973e-01 -1.11347461e+00 9.25548822e-02 -2.58732915e-01 -6.29896939e-01 4.24030870e-01 1.90713525e-01 6.46179259e-01 -1.06961000e+00 -1.17415190e+00 -4.35573369e-01 1.93099409e-01 -9.53320920e-01 1.55075595e-01 -1.29933015e-01 -4.62354004e-01 -1.53819251e+00 -9.08734918e-01 -4.23007160e-01 6.89771414e-01 1.91820785e-02 1.39704466e+00 2.98605114e-01 -2.67852008e-01 4.48661447e-01 -1.75463349e-01 -1.13470435e+00 2.21202821e-02 2.80063152e-01 -4.58823144e-02 1.27098203e-01 1.02560568e+00 -3.45498413e-01 -8.45459998e-01 2.49042973e-01 -5.70374966e-01 -8.91202614e-02 4.41457987e-01 3.65548998e-01 -6.83479458e-02 -3.07428271e-01 7.94362873e-02 -9.68621016e-01 7.26080358e-01 -3.00915271e-01 -8.63902032e-01 1.67540625e-01 -6.03760779e-01 2.82437682e-01 -1.01004757e-01 -3.39102507e-01 -9.09939349e-01 -1.35175337e-03 -1.03404455e-01 -4.16595310e-01 -5.81710696e-01 1.26835063e-01 1.69001102e-01 -4.51850981e-01 8.80122840e-01 -3.80130112e-01 3.33349444e-02 -3.31499875e-01 -9.75628272e-02 9.73823190e-01 1.63287029e-01 -1.65058509e-01 5.49552977e-01 3.77312243e-01 2.57597983e-01 -8.94961059e-01 -8.65979970e-01 -3.10432732e-01 -8.00339937e-01 -7.68028677e-01 1.04366088e+00 -7.61140406e-01 -1.42575884e+00 1.10492790e+00 -1.10532403e+00 -5.52385867e-01 5.37932813e-01 2.18647689e-01 -3.02638799e-01 -9.77269337e-02 2.26138398e-01 -1.14128244e+00 -3.47653896e-01 -1.16416335e+00 1.04382598e+00 8.02283287e-01 -2.46110946e-01 -1.02193463e+00 3.95221084e-01 3.54319751e-01 7.07408965e-01 4.35005724e-01 3.16882730e-01 -3.28859955e-01 -3.77841622e-01 -2.40011051e-01 -5.03436267e-01 1.36109069e-01 -2.58453429e-01 2.32321814e-01 -1.80810392e+00 -2.93818474e-01 -3.12226713e-01 -5.61778486e-01 4.73376453e-01 3.68070662e-01 9.87073123e-01 1.82696417e-01 -3.72199625e-01 6.38763011e-01 1.55139136e+00 -3.44153583e-01 7.19519019e-01 4.46877569e-01 6.60126209e-01 8.70776951e-01 3.38266879e-01 1.07761234e-01 4.39699382e-01 7.16439724e-01 7.47808158e-01 -8.65655616e-02 -3.31084314e-03 -7.02774748e-02 -1.03546977e-01 1.66538209e-02 -5.51281273e-01 -4.30159688e-01 -1.14505959e+00 3.53231907e-01 -1.70801234e+00 -7.96861291e-01 -2.10660234e-01 2.26201272e+00 5.56174994e-01 1.57836229e-01 4.22078192e-01 8.95546973e-02 4.06670690e-01 -1.39678344e-01 -5.12495875e-01 -5.20200253e-01 1.36358723e-01 2.42161289e-01 6.12637341e-01 1.64528698e-01 -1.08324611e+00 7.04478681e-01 6.38124704e+00 6.57447577e-02 -1.64807749e+00 1.78474844e-01 7.12101817e-01 -1.27129480e-01 5.98844171e-01 -4.53876227e-01 -8.61615598e-01 5.22184491e-01 1.33042812e+00 2.81697184e-01 4.32356894e-01 8.83912146e-01 3.35617512e-02 -6.96613967e-01 -1.20470405e+00 1.36815023e+00 4.11547601e-01 -8.98562431e-01 -6.80106461e-01 1.36387751e-01 3.97707105e-01 4.72327441e-01 2.89672613e-01 1.89706549e-01 1.13394950e-03 -1.35622025e+00 4.53518540e-01 7.68638968e-01 8.41234446e-01 -5.29850543e-01 1.10493577e+00 2.66590476e-01 -5.48428237e-01 -4.07917798e-02 -1.17446899e-01 -2.23712802e-01 -2.41636217e-01 -1.63256109e-01 -9.76551652e-01 -2.41737410e-01 1.05127621e+00 4.00411397e-01 -1.25776315e+00 1.34681928e+00 -2.73309976e-01 5.83659232e-01 -4.91422802e-01 -6.42855763e-02 8.13914984e-02 -1.79575514e-02 1.11455366e-01 8.72869253e-01 1.09989103e-02 -2.79459894e-01 -6.74415171e-01 7.26887286e-01 -2.14408841e-02 -2.57434517e-01 -4.92562473e-01 2.29295895e-01 9.53107104e-02 1.44894052e+00 -4.16716456e-01 4.03517000e-02 -3.05916339e-01 9.00704563e-01 6.85608327e-01 3.76730680e-01 -8.61600518e-01 -2.15073660e-01 8.80352378e-01 5.49910128e-01 5.07785380e-02 -2.62218993e-02 2.98732631e-02 -9.09297645e-01 -2.18518481e-01 -7.29580402e-01 4.39355671e-02 -1.41818178e+00 -9.18876767e-01 7.50762165e-01 1.89651594e-01 -7.53009021e-01 -3.30663413e-01 -9.91192818e-01 -7.23538697e-01 1.26758635e+00 -1.52775609e+00 -1.43321419e+00 -1.04301822e+00 5.96069872e-01 1.68532833e-01 -2.09142432e-01 8.53209198e-01 1.31354287e-01 -5.92187822e-01 8.05318832e-01 -1.96916819e-01 2.21517995e-01 1.04243755e+00 -1.33936787e+00 -4.87116538e-03 7.65554726e-01 4.76565100e-02 6.61234856e-01 1.05908060e+00 -9.63031203e-02 -1.09192348e+00 -4.67460126e-01 5.63551009e-01 -7.93485403e-01 3.95309031e-01 -5.21595895e-01 -8.36040676e-01 6.78616941e-01 7.71259785e-01 2.12640278e-02 6.14971161e-01 4.05014634e-01 -4.13442314e-01 -3.10928404e-01 -1.26325619e+00 2.83792645e-01 6.27508879e-01 -5.20681500e-01 -3.37041050e-01 5.16751818e-02 1.04525993e-02 -6.38060451e-01 -5.75974286e-01 -1.30932871e-02 8.19939554e-01 -1.54097724e+00 5.89177549e-01 -4.41132218e-01 2.48565570e-01 -1.25842854e-01 4.99842495e-01 -1.24037659e+00 1.68047905e-01 -4.58332092e-01 -7.58026615e-02 1.13995612e+00 2.79478788e-01 -6.29738867e-01 1.00461757e+00 1.03245997e+00 5.24408281e-01 -5.48869550e-01 -6.37741208e-01 -5.62088005e-02 -1.20550252e-01 -9.62054208e-02 3.05726677e-01 6.16493642e-01 -4.03009474e-01 4.84378010e-01 -3.26412171e-01 1.01561837e-01 6.18616164e-01 -3.70528042e-01 1.21815729e+00 -1.59932601e+00 4.81317341e-02 -2.45466813e-01 -8.70469987e-01 -3.75956327e-01 1.66982725e-01 -5.61909610e-03 -2.27738798e-01 -1.13320947e+00 8.29026029e-02 -2.53433198e-01 -2.71716118e-01 3.46348822e-01 -2.40251482e-01 6.40384793e-01 1.42513350e-01 -7.12700635e-02 -6.72738791e-01 -1.40890017e-01 8.30208480e-01 2.44093537e-01 6.06717616e-02 1.91242605e-01 -3.33703279e-01 7.23351181e-01 7.91797221e-01 -4.51015443e-01 -3.52208316e-01 -5.37233531e-01 7.67137527e-01 -6.38811052e-01 4.84002352e-01 -1.37706947e+00 3.58664423e-01 4.57531035e-01 7.53674746e-01 -3.15990239e-01 5.92766881e-01 -1.03800464e+00 2.19757389e-02 1.33304089e-01 -7.85308108e-02 1.58302695e-01 5.41910768e-01 3.72396469e-01 7.37883747e-02 -2.75638908e-01 8.93956423e-01 -3.32473777e-02 -7.94069827e-01 1.94872558e-01 1.31396621e-01 -6.06346242e-02 1.09155405e+00 -4.40046251e-01 -4.09889579e-01 -4.17034656e-01 -6.12719417e-01 1.03254011e-02 9.50527847e-01 5.20623267e-01 1.91660494e-01 -6.28920197e-01 -4.46077198e-01 3.96205127e-01 3.17298919e-01 -1.78748369e-01 2.54408214e-02 9.79575872e-01 -7.79967070e-01 2.92003334e-01 -6.89913452e-01 -8.30308259e-01 -1.88865495e+00 4.36116576e-01 6.95965946e-01 1.83948994e-01 1.00780144e-01 1.07638180e+00 -1.94958970e-02 -6.26455843e-02 3.14601421e-01 -1.59152865e-01 -6.35943532e-01 7.35538602e-02 7.04738021e-01 3.17711085e-01 3.22971493e-02 -1.00665259e+00 -3.00569803e-01 7.52006054e-01 4.96915057e-02 1.02001421e-01 1.47405005e+00 -3.18350315e-01 -1.51585311e-01 5.96356571e-01 1.11333799e+00 -2.51611441e-01 -1.30932248e+00 1.17960736e-01 -1.38429359e-01 -5.94753981e-01 4.59096909e-01 -9.54679728e-01 -1.15095448e+00 1.25489247e+00 1.29290235e+00 2.38597199e-01 1.19070888e+00 -2.86628544e-01 1.26157731e-01 2.13821217e-01 3.22687238e-01 -8.85477543e-01 -1.50714308e-01 2.85854399e-01 5.58391869e-01 -1.93484986e+00 2.09871605e-02 5.78878634e-02 -6.87265873e-01 1.23492539e+00 8.93723011e-01 -2.01745972e-01 7.90790439e-01 3.83907754e-04 4.55860943e-01 -5.37586093e-01 -3.37175429e-01 -3.94894153e-01 4.27148134e-01 9.19401288e-01 6.98723316e-01 -1.78280979e-01 2.19230652e-01 2.64624972e-02 -2.63850689e-01 3.97297680e-01 4.14866984e-01 5.67664802e-01 -1.73202828e-01 -9.25534964e-01 -3.05174589e-01 3.98448527e-01 -6.70305014e-01 1.46765530e-01 -5.17660797e-01 1.04387951e+00 4.59861964e-01 8.91815782e-01 1.96293697e-01 -1.94151238e-01 2.33969331e-01 2.08991468e-01 7.74036050e-01 -4.27040935e-01 -8.34702313e-01 -3.82775635e-01 -4.85472865e-02 -7.47602284e-01 -9.27663982e-01 -6.23931468e-01 -5.85623980e-01 -5.20908356e-01 -4.42698359e-01 -1.84367403e-01 1.20490193e+00 1.03160799e+00 3.45465928e-01 4.61317092e-01 5.07233366e-02 -1.14997029e+00 -2.72447430e-02 -1.31897414e+00 -2.81441033e-01 4.76802021e-01 5.34535289e-01 -9.34994519e-01 -2.48062551e-01 1.29102215e-01]	[14.143427848815918, 0.07841881364583969]
112a90e4-a4ee-4b65-a85a-6efab341e3c8	automated-concatenation-of-embeddings-for-1	2010.05006	null	https://arxiv.org/abs/2010.05006v4	https://arxiv.org/pdf/2010.05006v4.pdf	Automated Concatenation of Embeddings for Structured Prediction	Pretrained contextualized embeddings are powerful word representations for structured prediction tasks. Recent work found that better word representations can be obtained by concatenating different types of embeddings. However, the selection of embeddings to form the best concatenated representation usually varies depending on the task and the collection of candidate embeddings, and the ever-increasing number of embedding types makes it a more difficult problem. In this paper, we propose Automated Concatenation of Embeddings (ACE) to automate the process of finding better concatenations of embeddings for structured prediction tasks, based on a formulation inspired by recent progress on neural architecture search. Specifically, a controller alternately samples a concatenation of embeddings, according to its current belief of the effectiveness of individual embedding types in consideration for a task, and updates the belief based on a reward. We follow strategies in reinforcement learning to optimize the parameters of the controller and compute the reward based on the accuracy of a task model, which is fed with the sampled concatenation as input and trained on a task dataset. Empirical results on 6 tasks and 21 datasets show that our approach outperforms strong baselines and achieves state-of-the-art performance with fine-tuned embeddings in all the evaluations.	['Kewei Tu', 'Fei Huang', 'Zhongqiang Huang', 'Tao Wang', 'Nguyen Bach', 'Yong Jiang', 'Xinyu Wang']	2020-10-10	automated-concatenation-of-embeddings-for	https://aclanthology.org/2021.acl-long.206	https://aclanthology.org/2021.acl-long.206.pdf	acl-2021-5	['aspect-extraction', 'semantic-dependency-parsing']	['natural-language-processing', 'natural-language-processing']	[ 2.28220657e-01 -2.19585910e-01 -4.32683259e-01 -2.35592037e-01 -6.37412071e-01 -2.81903297e-01 5.37208378e-01 3.75881493e-01 -8.42397749e-01 4.45492625e-01 5.92245698e-01 -2.03638926e-01 -1.54253393e-01 -5.33103108e-01 -4.58865434e-01 -6.55508935e-01 9.62222144e-02 6.65198267e-01 2.04761386e-01 3.46160159e-02 5.60645163e-01 1.46633670e-01 -1.46949148e+00 2.26627067e-01 7.89332151e-01 1.07033575e+00 7.05664754e-01 6.47376001e-01 -1.21463068e-01 2.80734271e-01 -3.13480973e-01 -4.02850986e-01 -2.88246963e-02 -2.18182668e-01 -7.55229950e-01 -8.29533115e-02 2.32181307e-02 -3.26160192e-01 2.48255804e-02 7.42434502e-01 5.37413001e-01 4.10452127e-01 8.16206157e-01 -8.43361199e-01 -9.66985822e-01 6.73236370e-01 1.86408404e-02 3.42949480e-01 -1.37825618e-02 9.95715708e-02 1.67436719e+00 -1.04180408e+00 5.20106316e-01 1.07707262e+00 2.75732964e-01 6.74026430e-01 -1.23816991e+00 -3.87616992e-01 5.31611562e-01 2.87619203e-01 -9.51673388e-01 -3.03699076e-01 6.68330014e-01 -3.27928960e-01 1.43256879e+00 -2.66574889e-01 5.93953013e-01 1.26068830e+00 2.22473279e-01 6.72358751e-01 5.29960155e-01 -6.76583111e-01 5.06301105e-01 2.30948150e-01 4.13771808e-01 4.69884813e-01 2.89080679e-01 1.88835174e-01 -5.51587164e-01 -4.59719598e-01 3.71555567e-01 6.16728477e-02 -3.72283272e-02 -4.46599334e-01 -1.07906008e+00 1.14488757e+00 3.22987348e-01 4.69362617e-01 -6.26071215e-01 2.18357459e-01 3.84130806e-01 5.95894232e-02 4.94582921e-01 1.12398469e+00 -7.00618386e-01 -3.77218008e-01 -3.49709690e-01 4.95178998e-01 4.20289904e-01 2.58559883e-01 6.93740904e-01 7.64733255e-02 -3.79831344e-01 1.26964366e+00 3.31085861e-01 -5.12116551e-02 9.42373872e-01 -6.05683804e-01 5.28435230e-01 6.10312223e-01 1.89804733e-01 -6.78462684e-01 -1.52723432e-01 -4.48478341e-01 -2.67663300e-01 -3.98360193e-02 7.59983212e-02 -2.73825914e-01 -7.92689204e-01 1.71041989e+00 1.88304096e-01 2.70630658e-01 1.19132824e-01 9.54624295e-01 2.70304471e-01 8.25009823e-01 3.10425580e-01 7.05062086e-03 1.31218278e+00 -1.11458743e+00 -6.36211455e-01 -7.05268383e-01 8.68073821e-01 -4.94830757e-01 1.06027389e+00 3.04662943e-01 -5.99506795e-01 -7.02425718e-01 -1.13478255e+00 1.16496764e-01 -4.27247316e-01 2.60588288e-01 1.60176158e-01 2.84909576e-01 -7.28352964e-01 8.41390252e-01 -7.29459941e-01 -1.48799166e-01 2.54821807e-01 3.03410441e-01 -7.48156980e-02 -9.27083865e-02 -1.30483341e+00 1.32495821e+00 6.26414955e-01 -8.63525718e-02 -8.34981322e-01 -5.65060079e-01 -6.77101016e-01 2.94303596e-01 1.80269167e-01 -4.78736967e-01 1.08889592e+00 -6.52419508e-01 -1.32085943e+00 3.75723004e-01 -7.96668902e-02 -7.46239960e-01 -1.41885504e-01 -4.10904139e-01 -2.32287258e-01 -1.52670696e-01 -1.34364977e-01 9.20376301e-01 9.60178435e-01 -8.55490685e-01 -6.79541886e-01 -3.15551281e-01 3.81638817e-02 3.47833663e-01 -9.21724260e-01 6.28576949e-02 -1.71564266e-01 -4.85849977e-01 -3.56112510e-01 -9.32909250e-01 -5.46562791e-01 -3.52204926e-02 5.08862436e-02 -8.00060213e-01 5.72385490e-01 -3.92383605e-01 1.66532660e+00 -2.21442556e+00 4.75743085e-01 -1.38614371e-01 -4.17932793e-02 5.93855619e-01 -6.57945454e-01 5.73820889e-01 6.82081282e-02 1.08369708e-01 5.68069890e-03 -6.87570393e-01 1.41002834e-01 3.89536083e-01 -5.22015929e-01 -1.13646574e-01 5.37083268e-01 6.49990916e-01 -9.39377844e-01 -2.88139641e-01 1.80209987e-02 4.97703820e-01 -7.85393894e-01 6.96638107e-01 -4.53528047e-01 -1.22646905e-01 -7.00365663e-01 2.19230518e-01 8.49935189e-02 -1.11203671e-01 3.13687265e-01 -9.08373296e-02 -3.08058225e-02 6.45800233e-01 -1.07612360e+00 1.45372021e+00 -6.99131608e-01 3.03786188e-01 -5.95944941e-01 -1.10044932e+00 1.31439221e+00 1.84333801e-01 3.98581102e-02 -4.45647806e-01 4.95820120e-02 1.85129359e-01 1.58945158e-01 -4.58289981e-01 6.81314111e-01 8.75583738e-02 3.66985574e-02 7.88750827e-01 3.17708641e-01 6.32161498e-02 9.35290232e-02 -1.07032105e-01 1.16151750e+00 2.06001744e-01 3.05004746e-01 4.90594134e-02 2.31214359e-01 -2.08949089e-01 3.77259523e-01 5.10930061e-01 -2.60722131e-01 4.79703516e-01 5.78388989e-01 -7.15577304e-01 -1.05266559e+00 -6.87492549e-01 -7.83028360e-03 1.46276736e+00 -1.85232997e-01 -5.97224176e-01 -4.06195253e-01 -7.52919555e-01 -4.82945107e-02 1.09846044e+00 -8.97118807e-01 -5.41948617e-01 -6.04434252e-01 -6.26617432e-01 1.54771535e-02 6.41624212e-01 -1.93745971e-01 -1.47176194e+00 -8.57163787e-01 4.94479567e-01 1.68942615e-01 -1.08537221e+00 -4.84629720e-01 6.39478087e-01 -1.00978887e+00 -7.22934067e-01 -4.38223273e-01 -9.99486685e-01 6.13691866e-01 1.87839195e-01 8.85764897e-01 1.75907183e-02 -1.36423051e-01 1.21769011e-02 -6.09291375e-01 -2.10653275e-01 -2.57811368e-01 2.74079204e-01 -5.96871786e-03 9.20588076e-02 3.81649524e-01 -3.24122220e-01 -4.98352379e-01 -2.56466717e-02 -8.21933329e-01 -2.36461997e-01 6.38425767e-01 1.12230039e+00 5.96104920e-01 -1.54210448e-01 5.60133517e-01 -6.56581521e-01 1.23118460e+00 -5.92761636e-01 -3.88779134e-01 3.31724852e-01 -8.91216457e-01 6.77060843e-01 8.09573352e-01 -7.52822399e-01 -6.66120172e-01 1.28678419e-02 2.66234744e-02 -6.38492823e-01 5.47322929e-02 5.80146968e-01 2.14225292e-01 5.97666919e-01 6.03711188e-01 2.63181716e-01 1.33883068e-02 -5.14425159e-01 5.53390920e-01 6.91953063e-01 -1.83150128e-01 -6.73911035e-01 3.48550349e-01 -3.75055701e-01 -7.19610751e-01 -4.90006983e-01 -7.56807566e-01 -2.74516463e-01 -4.42987740e-01 9.11398381e-02 9.58155036e-01 -6.19263887e-01 -1.09815106e-01 -9.56673473e-02 -1.27113950e+00 -2.46921510e-01 -1.10803150e-01 6.44566834e-01 -2.79832363e-01 -1.22113489e-01 -9.12537351e-02 -7.44916618e-01 -4.26939875e-01 -1.59865332e+00 8.66400480e-01 1.45908386e-01 -5.41432500e-01 -9.00071502e-01 4.80481148e-01 4.36042696e-02 6.56134665e-01 -2.82066673e-01 1.36369514e+00 -1.11588740e+00 -2.55899966e-01 -4.28343534e-01 2.68056970e-02 5.27951360e-01 3.51147391e-02 -2.06713695e-02 -7.91102648e-01 -4.47120294e-02 -2.70160168e-01 -5.44052422e-01 8.15684974e-01 2.30931252e-01 1.34259939e+00 -3.01045686e-01 -4.41089720e-01 1.43873334e-01 1.31070244e+00 3.01183373e-01 3.98745656e-01 5.11828661e-01 3.35369170e-01 4.60261673e-01 5.76120436e-01 5.26874542e-01 2.26653203e-01 7.96326697e-01 6.23721063e-01 6.41285598e-01 4.52163219e-02 -3.52655202e-01 4.73754585e-01 6.66929960e-01 1.42891452e-01 -1.07461028e-01 -6.51619375e-01 8.08612645e-01 -1.80831599e+00 -7.63396502e-01 6.16730630e-01 2.02835321e+00 9.32307601e-01 3.11358392e-01 1.26564547e-01 -1.33837610e-01 5.03666520e-01 4.67463762e-01 -5.75502455e-01 -9.57436264e-01 5.00014305e-01 5.23046076e-01 1.48621602e-02 4.48488712e-01 -8.43971908e-01 9.81541693e-01 5.86401463e+00 6.85343742e-01 -9.40085709e-01 6.27656356e-02 5.45477509e-01 -5.60507141e-02 -4.31108624e-01 -8.64340812e-02 -1.08216476e+00 5.45496404e-01 1.11794162e+00 -2.54284024e-01 4.57612514e-01 9.39852715e-01 -8.50529149e-02 1.16436474e-01 -1.23309147e+00 4.64571327e-01 2.16901861e-02 -1.31317198e+00 2.63680011e-01 -1.58435553e-02 6.93380475e-01 1.19441651e-01 2.16906637e-01 5.82085133e-01 2.99067646e-01 -8.06845784e-01 4.07377064e-01 2.57306695e-01 1.19714715e-01 -7.35882938e-01 7.58379340e-01 4.00908768e-01 -9.22262192e-01 -4.40480918e-01 -6.35044575e-01 -8.67718309e-02 -2.43283492e-02 2.75252789e-01 -1.05235898e+00 -2.84341397e-03 2.61497259e-01 5.91183007e-01 -4.04876411e-01 8.40402544e-01 -3.67733598e-01 5.84765613e-01 3.87619175e-02 -7.57227302e-01 4.90115494e-01 -6.77390620e-02 1.88523144e-01 1.08993590e+00 2.69855082e-01 -1.77240804e-01 1.83499053e-01 7.62957096e-01 -1.61709890e-01 1.83096990e-01 -5.23073196e-01 -3.56963784e-01 8.15516829e-01 1.14287078e+00 -2.13761896e-01 -1.87424988e-01 -2.81803995e-01 6.37539148e-01 1.07504451e+00 1.36662841e-01 -7.20216513e-01 -1.41505167e-01 1.02652359e+00 -8.62755179e-02 8.07607949e-01 -2.69703865e-01 -1.39487386e-01 -7.94128239e-01 -9.27633047e-02 -7.50432432e-01 3.45000297e-01 -5.70953548e-01 -1.31397343e+00 9.43063378e-01 -1.03516532e-02 -1.18627310e+00 -3.99903327e-01 -6.31606996e-01 -8.28265190e-01 7.13662505e-01 -1.48707592e+00 -5.49645543e-01 2.10395589e-01 -4.00539041e-02 8.93010557e-01 -3.64419103e-01 1.36872184e+00 -2.07822144e-01 -7.59594321e-01 5.40960968e-01 1.52366720e-02 -2.26821974e-02 5.81723928e-01 -9.81427312e-01 4.08767194e-01 6.34966493e-01 4.21332359e-01 4.51809764e-01 5.37469804e-01 -3.67437869e-01 -1.38898695e+00 -1.01341212e+00 1.19234562e+00 -2.23455578e-01 9.70744312e-01 -1.40401185e-01 -9.63402569e-01 5.17815113e-01 3.39536160e-01 9.56093222e-02 7.80948699e-01 2.92327017e-01 -4.82540458e-01 -1.60758838e-01 -7.66797125e-01 5.83966315e-01 8.31666768e-01 -3.97750020e-01 -9.80548501e-01 2.34492034e-01 9.68635499e-01 -7.86406696e-02 -7.40184784e-01 1.61165521e-02 5.13333499e-01 -4.93688434e-01 8.40569019e-01 -9.56550241e-01 7.01116979e-01 4.79585417e-02 -3.42759043e-01 -1.77890992e+00 -5.44603467e-01 -3.68743725e-02 -3.09098870e-01 8.03591311e-01 6.35666370e-01 -6.49821997e-01 4.92155850e-01 5.77597558e-01 -4.55943085e-02 -1.41315377e+00 -8.37867618e-01 -5.08190870e-01 -8.73865187e-02 -2.72932827e-01 4.59052652e-01 5.04741251e-01 5.00071906e-02 5.33257484e-01 -2.61416554e-01 4.86672632e-02 2.48579070e-01 1.57465190e-01 3.93014669e-01 -1.04995012e+00 -3.37149531e-01 -5.31208038e-01 -1.37559369e-01 -1.02057779e+00 4.06620890e-01 -7.81476974e-01 1.62203580e-01 -1.47880018e+00 -4.30239774e-02 -5.75556457e-01 -7.26225436e-01 5.37496686e-01 -5.27939141e-01 -2.22452790e-01 3.65642399e-01 1.65825173e-01 -5.26038289e-01 7.59465516e-01 9.55666125e-01 -1.47702307e-01 -2.28445977e-01 -1.02333553e-01 -7.80426264e-01 3.59743953e-01 8.91221046e-01 -5.94199061e-01 -4.33678240e-01 -8.15065622e-01 8.73526558e-02 -2.05183327e-01 -1.42580733e-01 -8.48948240e-01 9.05594826e-02 -1.46637768e-01 3.10378760e-01 -2.92412251e-01 4.84263301e-01 -7.37466574e-01 -2.94521421e-01 5.53926468e-01 -9.49741900e-01 2.89514422e-01 4.55115363e-02 6.21862948e-01 -1.09636463e-01 -7.66124845e-01 5.06823480e-01 1.07197329e-01 -7.57167041e-01 2.69498289e-01 -2.14564502e-01 -2.23988593e-02 8.85971904e-01 -8.41239393e-02 -4.30593789e-02 1.17014095e-01 -6.68009996e-01 2.25521758e-01 -3.52558866e-02 8.93026948e-01 8.15192759e-01 -1.45913398e+00 -6.29534900e-01 1.82797045e-01 3.32851738e-01 -2.86480963e-01 -2.41769746e-01 2.67920613e-01 1.53204039e-01 3.87780428e-01 -1.77694902e-01 -2.37871096e-01 -9.86828208e-01 4.41368341e-01 2.07269728e-01 -7.79026687e-01 -2.85993159e-01 8.38170826e-01 -1.29502371e-01 -2.42095008e-01 3.89027596e-01 -5.66118479e-01 -5.87156951e-01 3.61866146e-01 6.34786963e-01 1.43362135e-01 1.01747602e-01 -1.61671191e-01 -3.85561228e-01 4.77505684e-01 -4.65175360e-01 7.33334944e-02 1.73680270e+00 2.74446040e-01 3.00400943e-01 3.71991754e-01 1.47441924e+00 -5.79016387e-01 -1.32395005e+00 -4.45212692e-01 -6.23569079e-02 -4.90689665e-01 1.27514794e-01 -6.77539527e-01 -8.39790761e-01 9.44363058e-01 4.45274383e-01 1.56253830e-01 7.48635173e-01 -1.12293534e-01 7.40699410e-01 3.75790238e-01 1.42613709e-01 -1.16794598e+00 6.08031034e-01 5.73635697e-01 9.11220312e-01 -9.85761523e-01 -8.75114799e-02 3.20153534e-01 -9.45120037e-01 1.31310225e+00 9.02407706e-01 -5.31953990e-01 6.79498255e-01 -5.67072369e-02 -2.29546756e-01 7.89886862e-02 -1.41029334e+00 -1.57788023e-01 2.53560454e-01 5.14156103e-01 3.77342939e-01 2.32958123e-01 -4.93773967e-01 6.15447044e-01 7.85321370e-02 -1.48359016e-01 1.34108707e-01 7.31678605e-01 -8.67199659e-01 -1.45366526e+00 -4.31625769e-02 5.74165761e-01 -4.68392782e-02 -1.21098273e-01 -1.51637495e-01 1.97999075e-01 2.80177981e-01 6.14089131e-01 3.06793809e-01 -4.52205867e-01 4.35700268e-01 3.53035659e-01 2.19135076e-01 -7.85987735e-01 -5.93463242e-01 -3.23546499e-01 1.28752738e-01 -3.31572443e-01 -9.88112465e-02 -6.24671459e-01 -1.10477972e+00 3.30760628e-01 -4.71693933e-01 1.74218714e-01 7.80342937e-01 1.06418431e+00 5.83459079e-01 4.74640876e-01 8.40798557e-01 -9.23167467e-01 -1.14610410e+00 -1.11707866e+00 -2.43784729e-02 2.90417492e-01 1.77589178e-01 -9.65767086e-01 -3.33834589e-01 -3.04233313e-01]	[10.582197189331055, 8.602304458618164]
89d53a06-921e-459b-ada9-1964587e25b4	npms-neural-parametric-models-for-3d	2104.00702	null	https://arxiv.org/abs/2104.00702v2	https://arxiv.org/pdf/2104.00702v2.pdf	NPMs: Neural Parametric Models for 3D Deformable Shapes	Parametric 3D models have enabled a wide variety of tasks in computer graphics and vision, such as modeling human bodies, faces, and hands. However, the construction of these parametric models is often tedious, as it requires heavy manual tweaking, and they struggle to represent additional complexity and details such as wrinkles or clothing. To this end, we propose Neural Parametric Models (NPMs), a novel, learned alternative to traditional, parametric 3D models, which does not require hand-crafted, object-specific constraints. In particular, we learn to disentangle 4D dynamics into latent-space representations of shape and pose, leveraging the flexibility of recent developments in learned implicit functions. Crucially, once learned, our neural parametric models of shape and pose enable optimization over the learned spaces to fit to new observations, similar to the fitting of a traditional parametric model, e.g., SMPL. This enables NPMs to achieve a significantly more accurate and detailed representation of observed deformable sequences. We show that NPMs improve notably over both parametric and non-parametric state of the art in reconstruction and tracking of monocular depth sequences of clothed humans and hands. Latent-space interpolation as well as shape/pose transfer experiments further demonstrate the usefulness of NPMs. Code is publicly available at https://pablopalafox.github.io/npms.	['Angela Dai', 'Matthias Nießner', 'Justus Thies', 'Aljaž Božič', 'Pablo Palafox']	2021-04-01	null	http://openaccess.thecvf.com//content/ICCV2021/html/Palafox_NPMs_Neural_Parametric_Models_for_3D_Deformable_Shapes_ICCV_2021_paper.html	http://openaccess.thecvf.com//content/ICCV2021/papers/Palafox_NPMs_Neural_Parametric_Models_for_3D_Deformable_Shapes_ICCV_2021_paper.pdf	iccv-2021-1	['pose-transfer']	['computer-vision']	[ 6.03902191e-02 -1.08468145e-01 -2.92080529e-02 -2.90422767e-01 -4.21251893e-01 -7.99642265e-01 6.49683058e-01 -3.57207179e-01 -9.07364935e-02 5.65137804e-01 1.21643081e-01 -2.44710110e-02 -4.46182955e-03 -3.82432997e-01 -1.03834224e+00 -6.48376405e-01 8.92597884e-02 6.66523933e-01 9.35187414e-02 5.15122600e-02 -2.34404989e-02 8.15178037e-01 -1.36610150e+00 -9.12891924e-02 5.88168323e-01 9.19689536e-01 1.38899714e-01 6.41048729e-01 2.67335117e-01 -2.06434242e-02 -2.19997782e-02 -3.58556539e-01 2.91589320e-01 3.21939513e-02 -3.42132837e-01 3.34795028e-01 7.42109001e-01 -6.59974337e-01 -4.65419501e-01 6.65765047e-01 2.25973696e-01 2.12357685e-01 7.62563169e-01 -1.03566813e+00 -8.45458984e-01 -5.68920821e-02 -6.25665307e-01 -4.31044847e-01 3.29819769e-01 3.04885119e-01 6.89896107e-01 -1.05486834e+00 6.35897756e-01 1.51344550e+00 1.02642977e+00 7.26755857e-01 -1.67779052e+00 -6.41539216e-01 1.86185449e-01 -3.79624218e-01 -1.29276383e+00 -4.53619480e-01 8.51962328e-01 -7.39409685e-01 5.36762655e-01 3.17982763e-01 9.66837347e-01 1.32549059e+00 3.23405862e-02 7.44635165e-01 9.17086422e-01 -2.23973557e-01 -1.59151495e-01 -4.97689843e-02 -1.29245698e-01 9.33243275e-01 2.38521352e-01 3.25801373e-01 -4.66907650e-01 -4.87479717e-01 1.64478695e+00 2.50565320e-01 -2.85534769e-01 -1.06552732e+00 -1.25160933e+00 6.13886654e-01 2.37474009e-01 -2.98303425e-01 -2.93969631e-01 4.90700603e-01 7.15161636e-02 -3.28630239e-01 4.80861992e-01 3.40466470e-01 -6.34357989e-01 -7.89597109e-02 -7.88611352e-01 6.50721669e-01 6.49605870e-01 1.03446436e+00 6.73064411e-01 1.23572610e-01 1.48789734e-01 7.26725340e-01 5.05336463e-01 7.68483579e-01 -5.38427122e-02 -1.37937129e+00 -1.30921435e-02 3.26113850e-01 4.21035081e-01 -9.71176624e-01 -3.28254580e-01 -3.03397238e-01 -8.26852679e-01 4.36111987e-01 5.86534560e-01 5.67178093e-02 -1.11816335e+00 1.72941172e+00 5.65629065e-01 3.28910857e-01 -6.11257970e-01 1.05998659e+00 5.05132198e-01 4.60996717e-01 5.06434531e-04 1.85896546e-01 1.23837733e+00 -8.10519755e-01 -2.79584914e-01 -7.87167028e-02 -5.07228523e-02 -7.19385207e-01 1.14961469e+00 4.14076984e-01 -1.28851724e+00 -4.95534003e-01 -6.53991640e-01 -3.37129295e-01 7.28643984e-02 1.24007404e-01 8.46594155e-01 3.57172757e-01 -8.94273698e-01 7.27579415e-01 -1.23714745e+00 -2.21279874e-01 4.31673497e-01 5.24877012e-01 -4.15601552e-01 7.23562390e-03 -6.88708901e-01 6.55027032e-01 5.96550573e-03 2.60616690e-01 -9.98581827e-01 -1.00697005e+00 -1.05003595e+00 -2.06161499e-01 4.11701709e-01 -1.04567397e+00 1.32409084e+00 -7.24747419e-01 -1.73941004e+00 1.00213218e+00 -2.07059860e-01 -1.53982371e-01 7.24759161e-01 -5.69287539e-01 2.25002274e-01 -1.35363281e-01 -3.96671265e-01 7.51533508e-01 1.19020343e+00 -1.38593853e+00 1.33383676e-01 -3.82593364e-01 8.35046023e-02 6.77695721e-02 -3.53176408e-02 -1.76577762e-01 -6.44367099e-01 -8.69703650e-01 1.71440355e-02 -1.21150041e+00 -2.49467224e-01 9.32143033e-01 -3.78018498e-01 5.99968694e-02 8.67607713e-01 -8.40255737e-01 7.13865578e-01 -2.05557847e+00 6.38521016e-01 2.47280836e-01 3.92894536e-01 2.76466727e-01 -9.97055788e-03 1.15979068e-01 2.09107116e-01 -2.35065166e-03 -2.94440538e-01 -6.43304706e-01 2.91826844e-01 4.73128319e-01 -2.35580042e-01 5.65427005e-01 1.97901294e-01 1.17954278e+00 -8.24777842e-01 -2.14292109e-01 3.16830754e-01 8.99774611e-01 -7.25090981e-01 1.03073895e-01 -5.30287087e-01 8.95120800e-01 -4.76673871e-01 6.86347961e-01 5.65446079e-01 -4.00670141e-01 1.67909727e-01 -3.46763432e-01 -2.33993363e-02 1.02913588e-01 -1.01197708e+00 1.94239283e+00 -3.85378271e-01 3.53508383e-01 3.67576689e-01 -6.59257650e-01 7.87283897e-01 2.49965757e-01 4.74493563e-01 -4.37731296e-02 1.14213064e-01 1.69383511e-01 -3.78668547e-01 -1.56198457e-01 2.82137185e-01 -3.05170119e-01 4.38474268e-02 2.03825936e-01 -5.02325706e-02 -4.95183408e-01 -4.48739558e-01 -1.04781717e-01 5.19103289e-01 9.46733654e-01 1.74037084e-01 -1.35761082e-01 1.47433460e-01 -1.79497868e-01 4.57534850e-01 2.77526319e-01 1.20552547e-01 7.05037415e-01 1.25604004e-01 -6.24249697e-01 -1.48686159e+00 -1.31006312e+00 -1.80193663e-01 9.60207462e-01 -4.07116897e-02 -1.20172545e-01 -5.88705719e-01 -3.78117383e-01 5.79325974e-01 2.79981375e-01 -7.59549797e-01 -6.66917488e-03 -8.18781435e-01 -3.31062436e-01 3.75405163e-01 7.47046351e-01 -7.47678429e-02 -7.71247089e-01 -4.59139109e-01 1.47639200e-01 2.07801551e-01 -1.20593023e+00 -8.95403206e-01 -2.33964726e-01 -1.01996326e+00 -9.49744284e-01 -8.95508051e-01 -5.86687267e-01 8.17677915e-01 4.12392057e-02 1.05001152e+00 4.28549722e-02 -4.48115796e-01 6.33745372e-01 1.05796650e-01 -1.88478917e-01 -2.78507501e-01 -2.34702498e-01 3.39527249e-01 -5.59568480e-02 -2.17844397e-01 -8.97934198e-01 -6.65220380e-01 4.85775590e-01 -6.71491861e-01 2.88994014e-01 3.95290434e-01 8.39146256e-01 8.98091853e-01 -6.38749540e-01 1.84807777e-01 -7.49850810e-01 2.38634616e-01 -1.50517151e-01 -8.13096106e-01 -4.58371360e-03 -1.99408263e-01 8.09613690e-02 4.17535931e-01 -9.25280988e-01 -8.69536161e-01 3.98469925e-01 -3.40916924e-02 -1.05502367e+00 -1.22058719e-01 2.13670403e-01 -6.98694447e-03 -3.43595803e-01 5.24636030e-01 1.33478269e-01 2.86777705e-01 -8.46628726e-01 5.14898360e-01 1.00806832e-01 8.45108449e-01 -1.03812063e+00 1.17277265e+00 6.00886643e-01 2.43033290e-01 -7.66339123e-01 -6.97047830e-01 -1.28196493e-01 -9.50859845e-01 5.26060139e-05 7.55270541e-01 -8.04276109e-01 -8.57808232e-01 4.95100051e-01 -1.16633904e+00 -6.19380474e-01 -2.92891532e-01 3.46522003e-01 -7.82557845e-01 5.14364779e-01 -6.45538390e-01 -8.14442873e-01 -1.93097934e-01 -9.42285597e-01 1.37734878e+00 -2.09336653e-02 -5.38424551e-01 -1.15646076e+00 1.04007851e-02 1.95121869e-01 1.72669575e-01 8.20992887e-01 9.01984394e-01 8.57342780e-02 -6.60372198e-01 -2.14891285e-01 -3.91483456e-02 3.33138496e-01 2.24820003e-01 2.70631164e-01 -7.27138996e-01 -5.07703364e-01 -2.29425609e-01 -3.08258653e-01 5.06982744e-01 4.96927470e-01 1.31691301e+00 -4.84698802e-01 -3.87214303e-01 1.06377280e+00 9.92036521e-01 -1.05934322e-01 2.44303092e-01 -9.89413634e-02 1.07615542e+00 4.86063004e-01 3.24677110e-01 5.22192538e-01 3.92830670e-01 1.03214872e+00 4.44300950e-01 -8.81070718e-02 -1.76849335e-01 -4.94214833e-01 1.30046487e-01 5.97879052e-01 -4.64193344e-01 3.60434711e-01 -8.01822186e-01 2.81135619e-01 -1.70330203e+00 -5.28411925e-01 -1.17393257e-02 2.26545310e+00 9.65968490e-01 -4.31261584e-02 3.48353684e-01 -2.35956833e-01 4.53751951e-01 -4.45652567e-02 -9.79182720e-01 -1.04804644e-02 1.19133249e-01 3.57556969e-01 3.16652834e-01 6.42392635e-01 -1.08119237e+00 8.33361804e-01 5.93683195e+00 4.91478413e-01 -1.09843469e+00 2.65369918e-02 3.19328815e-01 -3.08933854e-01 -4.86984104e-01 -2.02065364e-01 -7.58091211e-01 2.42960557e-01 4.99252915e-01 5.48726283e-02 6.96969867e-01 7.02337444e-01 2.15390846e-01 3.27992380e-01 -1.30127430e+00 1.08272529e+00 -1.11363418e-01 -1.31492257e+00 1.02088846e-01 2.34886199e-01 6.96009398e-01 -2.29774401e-01 3.02989870e-01 8.77589881e-02 2.57822633e-01 -1.08940411e+00 1.01771855e+00 7.47455597e-01 1.06196952e+00 -4.34309095e-01 6.00747904e-03 4.98768479e-01 -1.04438663e+00 2.58716404e-01 -3.16320866e-01 -1.57173304e-03 2.22487390e-01 1.65787727e-01 -5.29405475e-01 1.99624926e-01 4.85433251e-01 6.69416368e-01 -1.40308291e-01 9.45449889e-01 -1.95835158e-01 3.87000501e-01 -5.13853967e-01 3.74565125e-01 4.33829315e-02 -2.28211954e-01 6.75267279e-01 9.77457166e-01 2.53939718e-01 7.77027607e-02 2.86640316e-01 1.16557634e+00 -2.00342909e-02 -2.64577240e-01 -5.02802491e-01 -7.07240999e-02 3.59052330e-01 1.05765224e+00 -2.23545074e-01 -2.80493312e-02 -1.81291729e-01 9.01921451e-01 3.95360589e-01 4.14943755e-01 -9.06518102e-01 2.77784586e-01 8.09762537e-01 5.37088573e-01 3.93996984e-01 -9.68423188e-01 -3.24836552e-01 -1.26174295e+00 9.26047843e-03 -7.32158601e-01 -1.12055272e-01 -7.25290835e-01 -1.33698177e+00 3.14249933e-01 2.01737598e-01 -1.01706839e+00 -2.91797787e-01 -8.46354365e-01 -2.72606462e-01 1.01965022e+00 -1.22778702e+00 -1.56370223e+00 -4.30337250e-01 4.84448791e-01 4.33274925e-01 3.99381459e-01 8.62356544e-01 1.41193345e-01 -1.34930745e-01 6.20707810e-01 -3.97467650e-02 1.86820868e-02 6.54101491e-01 -1.11207879e+00 8.03151131e-01 4.19865668e-01 1.63920477e-01 8.20341110e-01 6.39969647e-01 -6.66183412e-01 -1.79242992e+00 -1.03735328e+00 1.53412059e-01 -8.74973416e-01 5.70081115e-01 -6.50258303e-01 -1.06070793e+00 8.77400875e-01 -4.25518423e-01 2.68004179e-01 5.02040744e-01 9.90085751e-02 -6.36773944e-01 2.38898665e-01 -1.04423523e+00 6.06008768e-01 1.28560936e+00 -5.34722447e-01 -3.70722204e-01 1.93936467e-01 7.71108449e-01 -8.91153753e-01 -9.86928403e-01 3.83320332e-01 1.19465005e+00 -6.10204518e-01 1.49289417e+00 -6.76409960e-01 1.68561056e-01 -2.56055981e-01 -1.64578781e-01 -1.06488705e+00 -4.51217175e-01 -8.56023490e-01 -7.28245020e-01 8.52475107e-01 4.02490906e-02 -5.70623279e-01 9.25377965e-01 8.65932167e-01 -2.22626746e-01 -1.09667289e+00 -8.24172914e-01 -8.38795185e-01 2.09256619e-01 -2.24925578e-01 4.53316897e-01 9.58954811e-01 -5.66032946e-01 -7.48732463e-02 -7.42372334e-01 2.43468970e-01 8.45555544e-01 1.64640129e-01 1.01486409e+00 -1.48101342e+00 -7.69554615e-01 -3.40949357e-01 -1.58733338e-01 -1.45297396e+00 1.98767304e-01 -6.86528027e-01 -2.85389479e-02 -1.24153411e+00 9.87916663e-02 -6.40309453e-01 1.08219206e-01 6.58075988e-01 -2.00962663e-01 5.50255597e-01 3.31525236e-01 3.13790053e-01 -1.80618718e-01 7.18234181e-01 1.70883763e+00 2.11788118e-01 -2.03308910e-01 7.56504089e-02 -3.86496186e-01 9.84248102e-01 6.00613534e-01 -2.00007141e-01 -2.37436935e-01 -6.13352537e-01 6.29021153e-02 1.79333001e-01 9.69928086e-01 -5.41540504e-01 -6.88086823e-02 -3.32359910e-01 6.32545590e-01 -4.35467780e-01 8.33973646e-01 -8.60051632e-01 5.49137235e-01 3.23992431e-01 3.98468003e-02 -8.69537741e-02 4.22494680e-01 6.67536676e-01 2.95492530e-01 2.05371663e-01 7.41411507e-01 -1.75723597e-01 -3.83320272e-01 7.27821410e-01 9.24279094e-02 -1.54449999e-01 7.46164978e-01 -4.34798747e-01 6.58102259e-02 -3.03843260e-01 -1.03735685e+00 6.73887730e-02 9.01861131e-01 4.09320533e-01 6.14581704e-01 -1.33734369e+00 -4.85505015e-01 2.68010437e-01 -1.86311334e-01 4.90148813e-01 2.36886173e-01 9.17872906e-01 -4.51645374e-01 1.81775257e-01 -2.36153752e-01 -7.81242609e-01 -1.23465264e+00 5.38295150e-01 3.64461750e-01 -6.13738075e-02 -8.25965285e-01 8.02130461e-01 5.96304059e-01 -8.03336620e-01 1.40479177e-01 -6.03064358e-01 4.85741287e-01 -4.74079162e-01 6.50751740e-02 3.71043980e-01 -4.59426492e-01 -5.67672968e-01 -2.17163831e-01 1.02193737e+00 1.09800547e-01 1.07608177e-02 1.42790151e+00 4.32376228e-02 2.90271193e-02 4.78820741e-01 9.64809299e-01 8.41010660e-02 -2.08683610e+00 -3.87334794e-01 -3.47107321e-01 -6.13492846e-01 -3.16191673e-01 -6.66496754e-01 -6.68825150e-01 9.58188534e-01 1.48869187e-01 -2.81721652e-01 7.33769238e-01 6.11728206e-02 9.02018249e-01 1.77270025e-01 5.86492538e-01 -3.67907226e-01 1.39849365e-01 4.84312564e-01 1.18478107e+00 -8.26512039e-01 1.06256329e-01 -6.53492272e-01 -3.40089589e-01 1.13494134e+00 3.93147707e-01 -3.58031839e-01 6.17524505e-01 2.91062027e-01 -2.04290941e-01 -4.75703459e-03 -4.91574466e-01 3.65866482e-01 7.66955197e-01 6.72828257e-01 2.52573073e-01 2.16162667e-01 2.61016428e-01 4.97574657e-01 -2.40444839e-01 1.03264473e-01 7.17793480e-02 8.54992032e-01 -1.44769311e-01 -1.15954864e+00 -4.01809394e-01 2.07343131e-01 -1.67968586e-01 7.74174780e-02 -9.16856229e-02 8.43217254e-01 1.82033665e-02 1.15849786e-01 -1.86067820e-02 -2.20412970e-01 4.41260964e-01 2.31882874e-02 9.58639383e-01 -7.39691138e-01 -2.21509367e-01 2.67539054e-01 -1.47054300e-01 -5.80894470e-01 -2.26635769e-01 -8.62816930e-01 -1.05999744e+00 -2.86495179e-01 -7.38236383e-02 -2.45139271e-01 6.48714483e-01 6.85564876e-01 3.72324049e-01 2.00718716e-01 1.05933219e-01 -1.61298633e+00 -8.41507792e-01 -6.67205513e-01 -4.51188356e-01 4.62540358e-01 6.26305103e-01 -1.05718648e+00 1.52561842e-02 2.93851942e-01]	[6.997763156890869, -1.296563982963562]
f93623da-98cb-4c7c-b243-b316ac5bcab5	machine-learning-approaches-to-predict-breast	2206.14972	null	https://arxiv.org/abs/2206.14972v1	https://arxiv.org/pdf/2206.14972v1.pdf	Machine Learning Approaches to Predict Breast Cancer: Bangladesh Perspective	Nowadays, Breast cancer has risen to become one of the most prominent causes of death in recent years. Among all malignancies, this is the most frequent and the major cause of death for women globally. Manually diagnosing this disease requires a good amount of time and expertise. Breast cancer detection is time-consuming, and the spread of the disease can be reduced by developing machine-based breast cancer predictions. In Machine learning, the system can learn from prior instances and find hard-to-detect patterns from noisy or complicated data sets using various statistical, probabilistic, and optimization approaches. This work compares several machine learning algorithm's classification accuracy, precision, sensitivity, and specificity on a newly collected dataset. In this work Decision tree, Random Forest, Logistic Regression, Naive Bayes, and XGBoost, these five machine learning approaches have been implemented to get the best performance on our dataset. This study focuses on finding the best algorithm that can forecast breast cancer with maximum accuracy in terms of its classes. This work evaluated the quality of each algorithm's data classification in terms of efficiency and effectiveness. And also compared with other published work on this domain. After implementing the model, this study achieved the best model accuracy, 94% on Random Forest and XGBoost.	['Md Jihadul Islam', 'Flora Akter', 'Choyon Chandra Bonik', 'Nazmul Islam Khan', 'Arindom Kundu', 'Taminul Islam']	2022-06-30	null	null	null	null	['breast-cancer-detection', 'breast-cancer-detection']	['knowledge-base', 'medical']	[-2.20795963e-02 1.11918807e-01 -7.93948591e-01 -6.10102117e-01 -4.72021669e-01 1.39074057e-01 4.56054449e-01 6.81305707e-01 -3.97178710e-01 1.03351068e+00 -1.44539595e-01 -6.04434431e-01 -5.50590992e-01 -1.07465565e+00 -6.20262511e-02 -7.24954963e-01 1.05414338e-01 9.29858863e-01 1.52374178e-01 6.58866018e-02 3.45774442e-01 7.01107681e-01 -1.49700940e+00 3.81157190e-01 9.48896706e-01 1.07374585e+00 1.54777959e-01 6.25355124e-01 -2.57979810e-01 8.07455659e-01 -3.96329582e-01 -2.55619109e-01 -3.43296051e-01 -3.97832960e-01 -8.04219902e-01 -4.44481552e-01 -4.12671924e-01 7.40041882e-02 3.85829866e-01 4.65797871e-01 4.67864662e-01 -3.98827046e-01 8.13953757e-01 -1.20944893e+00 -1.93067584e-02 4.08487707e-01 -6.19652033e-01 1.50627136e-01 2.87583500e-01 -3.88962299e-01 3.54424626e-01 -3.64796579e-01 5.21608710e-01 1.10215032e+00 8.64475369e-01 6.05027258e-01 -1.12380004e+00 -8.77943277e-01 -3.44961315e-01 5.78911543e-01 -1.12684584e+00 -1.57721803e-01 4.45892334e-01 -3.86032641e-01 7.89082825e-01 6.15004003e-01 9.21113014e-01 6.42912030e-01 6.52954876e-01 6.44283056e-01 1.35755110e+00 -1.00063837e+00 4.50901091e-01 6.37776136e-01 4.47700232e-01 6.24307156e-01 5.61316013e-01 3.17081630e-01 -4.58123326e-01 -5.07318795e-01 -5.33071123e-02 4.43324566e-01 3.51576842e-02 -2.60936824e-04 -6.10005677e-01 8.85343254e-01 2.88877964e-01 5.75845897e-01 -4.32533324e-01 -2.37137064e-01 1.50097162e-01 3.88231725e-02 4.28086758e-01 4.00166601e-01 -7.76654184e-01 -3.15291435e-02 -9.77228403e-01 -5.07727824e-03 9.18238044e-01 4.42430645e-01 3.97318155e-01 -7.18964636e-01 -9.52489674e-02 7.68672287e-01 5.32793581e-01 4.92538840e-01 8.62659156e-01 -3.18457894e-02 -2.45994493e-01 9.15212572e-01 -2.10067257e-03 -1.13250053e+00 -8.21072698e-01 -7.98582911e-01 -1.09601092e+00 -5.62203210e-03 2.56927401e-01 4.27802792e-03 -1.07137799e+00 1.06456840e+00 5.17651200e-01 -7.62148798e-02 6.81622550e-02 4.44049329e-01 8.62702966e-01 6.31461740e-01 4.98964697e-01 -5.73863208e-01 1.32553244e+00 -5.20763874e-01 -7.46512234e-01 -1.03712827e-01 7.61190057e-01 -6.50376916e-01 3.55107605e-01 5.65883994e-01 -3.03007096e-01 -2.24137798e-01 -8.27491522e-01 4.60906535e-01 -4.63958085e-01 2.97538757e-01 1.01934767e+00 1.01987493e+00 -5.87492824e-01 4.40004855e-01 -1.13769376e+00 -7.32289374e-01 4.83030617e-01 2.58071214e-01 -2.74629027e-01 -3.61948133e-01 -8.89915168e-01 1.18043518e+00 4.40980941e-01 -1.31412596e-01 -4.83011335e-01 -4.79875356e-01 -2.03071862e-01 -1.62911192e-01 6.69547170e-02 -5.71967185e-01 9.80878770e-01 -7.51236141e-01 -1.03580999e+00 7.57194638e-01 -5.38573861e-01 -5.28476059e-01 3.10675293e-01 -7.63432160e-02 -5.50462484e-01 -2.65067011e-01 1.13357961e-01 2.92993814e-01 8.41615871e-02 -9.43723619e-01 -1.21091449e+00 -6.33903265e-01 -7.76273251e-01 -2.07304969e-01 -3.02164823e-01 1.48706555e-01 -2.12896056e-02 -1.60989344e-01 4.77505714e-01 -7.98964858e-01 -4.74642366e-01 -3.44078779e-01 -2.47899771e-01 -3.98884654e-01 7.21392035e-01 -7.60074437e-01 1.39089203e+00 -1.79755974e+00 -3.93910468e-01 5.14223635e-01 -2.08167225e-01 7.80979246e-02 7.32114494e-01 3.23129565e-01 1.00670166e-01 3.43637854e-01 1.45553857e-01 3.66053313e-01 -6.61808014e-01 3.64481002e-01 2.20711544e-01 2.68829703e-01 1.15543716e-01 4.37947452e-01 -7.87142634e-01 -7.70967901e-01 1.24399692e-01 4.09512967e-01 -1.50283128e-01 3.92729193e-02 -8.50339010e-02 2.14879781e-01 -5.97890377e-01 9.94737804e-01 4.60166037e-01 -2.87658364e-01 3.96308422e-01 1.15962014e-01 1.46993086e-01 -1.42302796e-01 -9.46788013e-01 8.80483449e-01 -3.11529219e-01 4.63867515e-01 -5.00565112e-01 -1.28821433e+00 1.33023798e+00 3.31019700e-01 6.20987535e-01 -4.37327445e-01 1.11735448e-01 4.26438659e-01 1.17861636e-01 -6.57132804e-01 -1.02831542e-01 -1.15434490e-01 2.36871630e-01 1.48612425e-01 -3.16088021e-01 1.38916507e-01 3.45236100e-02 -1.87599123e-01 1.13458109e+00 -3.40369761e-01 1.05606318e+00 -3.39546949e-01 3.42811048e-01 6.39492571e-01 6.76021516e-01 5.99975944e-01 3.44245099e-02 8.24003965e-02 3.60675246e-01 -8.06061983e-01 -3.99935484e-01 -4.14096236e-01 -5.93457520e-01 8.47549200e-01 -1.37177080e-01 -1.10325977e-01 -3.70111138e-01 -5.78789830e-01 8.94727111e-02 8.68921936e-01 -5.82287610e-01 -1.24954723e-01 -1.43820748e-01 -1.56273127e+00 2.98977733e-01 9.06502753e-02 6.22653961e-01 -8.31864655e-01 -6.98761821e-01 3.89966995e-01 -8.46987516e-02 -2.72591531e-01 6.91783488e-01 6.47827029e-01 -1.26450646e+00 -1.37566972e+00 -3.43448818e-01 -6.42722547e-01 7.01594114e-01 2.28793100e-02 1.07395840e+00 4.47762370e-01 -6.84130728e-01 -3.89754862e-01 -5.93538940e-01 -1.05232430e+00 -4.83415782e-01 2.45037004e-01 -3.65122586e-01 -2.67330259e-01 8.54061067e-01 -6.58338964e-02 -4.07777935e-01 5.64780116e-01 -5.55980742e-01 5.03747612e-02 9.53011274e-01 1.05488312e+00 7.84522712e-01 7.59053111e-01 4.56826717e-01 -1.11318278e+00 3.75366539e-01 -7.96364665e-01 -3.01664144e-01 3.79970759e-01 -1.16796339e+00 -7.86521882e-02 1.35264903e-01 -8.43650028e-02 -9.04588342e-01 3.50894332e-01 -6.99665174e-02 5.47866583e-01 -4.37691182e-01 7.52940297e-01 -3.74182276e-02 1.10032767e-01 1.05521345e+00 -1.74446031e-02 2.00187434e-02 -4.88449216e-01 -3.05340588e-01 1.05128765e+00 -3.27342562e-02 -7.01284334e-02 1.27206013e-01 3.83481860e-01 3.39747965e-01 -6.55250311e-01 -9.20275152e-01 -7.45422602e-01 -5.69781959e-01 -3.33003521e-01 6.60594404e-01 -5.08822620e-01 -4.06268001e-01 5.44739008e-01 -7.83143878e-01 1.15943849e-01 2.92139500e-01 7.33220279e-01 -9.27856658e-03 -3.04497659e-01 -8.75954702e-02 -1.07683265e+00 -4.32758391e-01 -7.23260164e-01 5.54419518e-01 4.74158406e-01 -5.45578122e-01 -9.11197603e-01 1.88525375e-02 3.36458743e-01 5.81441343e-01 4.90872085e-01 1.00892007e+00 -8.06758583e-01 -2.05103550e-02 -6.45344496e-01 -1.37861103e-01 -1.27641439e-01 3.35445166e-01 2.70013005e-01 -7.88211882e-01 -1.07482702e-01 -1.17829099e-01 2.05597989e-02 1.00330138e+00 8.11287105e-01 1.11275542e+00 -3.45735401e-01 -1.37303317e+00 3.65953773e-01 1.53443742e+00 8.05678248e-01 4.58221972e-01 8.10619295e-01 2.72159427e-02 6.56219602e-01 1.07376683e+00 3.24096113e-01 2.07139716e-01 4.19958413e-01 4.66912121e-01 -2.44112894e-01 2.28897735e-01 -1.18756555e-01 -3.33627373e-01 1.44525152e-02 -2.95646966e-01 -9.19603407e-02 -1.48137629e+00 2.64866292e-01 -1.76808357e+00 -9.59842026e-01 -3.17183673e-01 2.06332684e+00 8.21936071e-01 2.10338593e-01 5.77026941e-02 8.53521049e-01 5.68567812e-01 -6.76190197e-01 -1.99379787e-01 -3.72841120e-01 1.87967017e-01 2.19227225e-01 6.68855190e-01 1.55735373e-01 -1.10451376e+00 3.18510145e-01 6.28005505e+00 6.71180665e-01 -1.45639217e+00 -6.27033296e-04 1.37287199e+00 1.75885782e-01 2.20596954e-01 -4.78703715e-02 -1.13768351e+00 6.06198490e-01 1.02964580e+00 1.61851395e-03 -1.83466718e-01 1.17970824e+00 2.47312725e-01 -6.98648751e-01 -9.68677104e-01 6.44326687e-01 -1.06431887e-01 -1.16053832e+00 -4.57701415e-01 7.38814548e-02 5.81733465e-01 -2.85194337e-01 -5.13755381e-01 9.47007090e-02 4.40625638e-01 -1.39077830e+00 1.34644762e-01 8.51098299e-01 4.28385854e-01 -8.08705747e-01 1.42126489e+00 6.84340537e-01 -4.06093210e-01 -2.87609339e-01 -9.44247469e-02 -1.68533593e-01 -2.79313982e-01 1.28004885e+00 -1.41387594e+00 4.05868232e-01 1.15786195e+00 4.00564522e-01 -6.38823926e-01 1.42272401e+00 -4.84130643e-02 9.83038664e-01 -5.55427432e-01 -8.05257499e-01 -2.64183581e-01 4.28397626e-01 -3.89708579e-02 1.12281728e+00 5.59083283e-01 1.86908394e-01 1.99144214e-01 2.59576761e-03 5.74816287e-01 4.61861223e-01 -2.31399506e-01 4.20116603e-01 5.73163807e-01 1.01605487e+00 -1.03569198e+00 -2.41478860e-01 5.04323058e-02 1.85462773e-01 -5.21036498e-02 -2.46108577e-01 -5.50670266e-01 -2.31219575e-01 -8.30260515e-02 4.26542491e-01 -2.86435008e-01 4.28501964e-01 -7.23047674e-01 -3.55623335e-01 -2.98268348e-01 -6.89763725e-01 8.25660944e-01 -3.26498866e-01 -1.01671326e+00 5.30626833e-01 1.19305447e-01 -8.83314252e-01 -3.50918412e-01 -6.32571936e-01 -4.00866985e-01 7.57381260e-01 -1.34123695e+00 -9.37919974e-01 -6.63696527e-01 1.26468644e-01 9.00554210e-02 -3.32895607e-01 1.27179027e+00 9.59681123e-02 -5.34588933e-01 3.77542049e-01 3.09588194e-01 -1.32239804e-01 6.22279286e-01 -1.02051663e+00 -4.32312489e-01 1.88020602e-01 -2.57354558e-01 6.19144402e-02 7.00467110e-01 -7.30545759e-01 -8.78058493e-01 -9.72622693e-01 1.21094787e+00 -2.19829492e-02 2.13421155e-02 2.27304652e-01 -5.84410727e-01 1.47438869e-01 -3.34267586e-01 -1.21702269e-01 1.03862703e+00 4.33912784e-01 2.05809698e-01 -6.70570493e-01 -1.54894435e+00 -5.86568676e-02 2.92373121e-01 3.95989358e-01 -8.34668353e-02 4.97653097e-01 -9.78872627e-02 -1.56523824e-01 -8.18272352e-01 6.46266162e-01 8.70748639e-01 -1.02571380e+00 6.36562884e-01 -5.57393670e-01 5.43272376e-01 -9.56633836e-02 4.66466993e-02 -1.32944477e+00 -4.82302994e-01 7.61659071e-02 1.61753222e-01 1.14604390e+00 8.98808241e-01 -5.77596009e-01 1.14048553e+00 6.13672733e-01 4.46555793e-01 -1.26320302e+00 -8.07887495e-01 -4.57222342e-01 -1.87137082e-01 -2.99293458e-01 6.78421080e-01 9.71550107e-01 -7.49855787e-02 3.33793461e-02 -2.12357655e-01 -1.27789602e-01 4.71072227e-01 8.62113684e-02 7.91089535e-01 -1.60315347e+00 -2.14758277e-01 -2.70392209e-01 -7.94802725e-01 -4.18370701e-02 -4.83734161e-01 -7.18072295e-01 -1.31359547e-01 -1.84883213e+00 5.23764193e-01 -9.57302630e-01 -3.52643996e-01 7.97193170e-01 -3.34063828e-01 -5.19895107e-02 -3.21211100e-01 3.05241644e-01 8.46570730e-03 -3.31778944e-01 9.04472351e-01 -1.64710671e-01 -3.33207339e-01 6.91744745e-01 -7.25917637e-01 7.72740781e-01 1.08429945e+00 -8.96534383e-01 -8.99118260e-02 -1.21615063e-02 1.45247534e-01 2.41131455e-01 3.77327017e-02 -9.46297526e-01 2.89145768e-01 -6.51081145e-01 1.03142893e+00 -7.47581959e-01 6.74330536e-03 -9.83698666e-01 6.78192854e-01 1.15203524e+00 -1.65389076e-01 -4.60731953e-01 9.19070169e-02 4.77338284e-01 -1.73804551e-01 -4.53846872e-01 8.12627196e-01 -4.29939628e-02 -5.28789163e-01 -1.76078901e-01 -3.42804730e-01 -7.09720671e-01 1.57629907e+00 -2.21089527e-01 -1.57537773e-01 -8.56363028e-02 -6.51277423e-01 1.81401566e-01 9.50556993e-02 1.19056255e-01 3.77634317e-01 -1.01108944e+00 -8.31193566e-01 1.16290972e-01 1.36520177e-01 -1.18055888e-01 -9.85750258e-02 8.37440848e-01 -7.81388640e-01 4.90853012e-01 -3.99788648e-01 -6.48289382e-01 -1.84548914e+00 2.56639421e-01 3.03524017e-01 -8.62271726e-01 -8.56052712e-02 8.05832148e-01 -7.68822968e-01 -1.71025351e-01 3.36591572e-01 -9.88496542e-02 -7.00074255e-01 -1.28313825e-02 3.91850501e-01 7.27239370e-01 2.37976715e-01 -1.60366669e-01 -6.23758972e-01 4.05508131e-01 -2.67986804e-01 2.70730346e-01 1.26359069e+00 4.17228550e-01 -3.69448215e-01 1.68959603e-01 7.66456485e-01 -1.96771011e-01 -6.69064000e-02 1.85514316e-01 5.00148475e-01 -5.25479972e-01 3.27592790e-01 -1.39450431e+00 -8.26547027e-01 4.71899480e-01 9.92902815e-01 3.25323611e-01 1.41982329e+00 -5.83281973e-03 2.59960175e-01 4.21809852e-01 3.47394675e-01 -9.51273322e-01 -5.92362285e-01 -1.04326293e-01 5.64895272e-01 -1.69712281e+00 5.68441749e-01 -6.00501537e-01 -2.58961558e-01 1.24853754e+00 3.67067397e-01 1.46111220e-01 1.32796693e+00 2.15762794e-01 9.09009799e-02 -4.55024140e-03 -9.88564372e-01 2.47130588e-01 1.89363450e-01 6.78057134e-01 7.31151164e-01 4.48209316e-01 -8.39549482e-01 7.52986491e-01 -4.25931007e-01 5.10204554e-01 -1.44334838e-01 1.11131728e+00 -8.19256246e-01 -1.20883417e+00 -6.52080119e-01 1.16480291e+00 -8.61951292e-01 2.63600856e-01 -5.34302592e-01 7.90762722e-01 3.45814288e-01 1.19462860e+00 -1.08947568e-01 -2.44626060e-01 9.57830399e-02 2.34069377e-02 3.05292606e-02 -3.58845353e-01 -3.17450851e-01 -3.46821696e-01 2.04883620e-01 -1.57301128e-01 -5.23494065e-01 -6.01829529e-01 -1.17265487e+00 -2.59849489e-01 -6.83754921e-01 4.12027627e-01 1.27253366e+00 7.91082442e-01 1.54865623e-01 3.87017280e-01 6.28035307e-01 -1.78254262e-01 -2.99625129e-01 -1.18324983e+00 -3.07763368e-01 9.23473686e-02 -1.27070710e-01 -6.86103821e-01 -2.08109140e-01 3.11037805e-02]	[8.434679985046387, 4.852565288543701]
c38a5b74-1086-4c0c-bc32-eb04a57eca91	learning-neuro-symbolic-programs-for-language	2211.06652	null	https://arxiv.org/abs/2211.06652v2	https://arxiv.org/pdf/2211.06652v2.pdf	Learning Neuro-symbolic Programs for Language Guided Robot Manipulation	Given a natural language instruction and an input scene, our goal is to train a model to output a manipulation program that can be executed by the robot. Prior approaches for this task possess one of the following limitations: (i) rely on hand-coded symbols for concepts limiting generalization beyond those seen during training [1] (ii) infer action sequences from instructions but require dense sub-goal supervision [2] or (iii) lack semantics required for deeper object-centric reasoning inherent in interpreting complex instructions [3]. In contrast, our approach can handle linguistic as well as perceptual variations, end-to-end trainable and requires no intermediate supervision. The proposed model uses symbolic reasoning constructs that operate on a latent neural object-centric representation, allowing for deeper reasoning over the input scene. Central to our approach is a modular structure consisting of a hierarchical instruction parser and an action simulator to learn disentangled action representations. Our experiments on a simulated environment with a 7-DOF manipulator, consisting of instructions with varying number of steps and scenes with different number of objects, demonstrate that our model is robust to such variations and significantly outperforms baselines, particularly in the generalization settings. The code, dataset and experiment videos are available at https://nsrmp.github.io	['Rohan Paul', 'Parag Singla', 'Rahul Jain', 'Vishwajeet Agrawal', 'Arnav Tuli', 'Vishal Bindal', 'Himanshu Singh', 'Namasivayam Kalithasan']	2022-11-12	null	null	null	null	['robot-manipulation']	['robots']	[ 4.51397270e-01 2.81182855e-01 -2.64215916e-01 -4.22951400e-01 -2.16144994e-01 -6.57595158e-01 6.54059589e-01 3.00909672e-02 -3.53124201e-01 2.90968627e-01 1.12041183e-01 -4.83494610e-01 -5.81768109e-03 -6.72699511e-01 -1.16293132e+00 -4.57076669e-01 -2.36368671e-01 3.62947494e-01 1.53293177e-01 -3.35147351e-01 4.92649794e-01 5.25375247e-01 -1.70701039e+00 3.46991777e-01 9.15938199e-01 6.11269772e-01 7.22263753e-01 8.26841116e-01 1.60450995e-01 1.22022378e+00 -4.24015164e-01 1.92366228e-01 4.21627551e-01 -4.25284207e-01 -9.35691416e-01 1.69694722e-01 4.10444170e-01 -6.81063771e-01 -5.42961240e-01 1.08265352e+00 -3.48375626e-02 4.48510021e-01 7.34799266e-01 -1.30915308e+00 -7.33267844e-01 6.85235977e-01 -5.04771061e-02 -1.75651103e-01 7.11384714e-01 7.22671032e-01 8.30096424e-01 -4.52536494e-01 4.94006217e-01 1.59010005e+00 4.78252070e-04 7.50152409e-01 -1.28339469e+00 -4.41366464e-01 4.48202044e-01 1.14060409e-01 -9.83266413e-01 -1.79763302e-01 5.78318536e-01 -4.14427608e-01 1.29956925e+00 -5.42828925e-02 4.15334553e-01 1.45386755e+00 4.79802579e-01 9.49946105e-01 1.04262769e+00 -3.14374357e-01 3.60177368e-01 -1.89541444e-01 2.89953619e-01 9.90336835e-01 6.60480186e-02 3.46162766e-01 -3.50779891e-01 1.69348076e-01 1.15899241e+00 2.58979023e-01 -1.80459157e-01 -7.72541523e-01 -1.37456882e+00 7.47089326e-01 6.81516647e-01 5.13584726e-02 -4.16885316e-01 3.41698676e-01 4.86701131e-01 5.52863002e-01 -3.29648495e-01 6.75292253e-01 -5.30337632e-01 -1.26867324e-01 -2.37555042e-01 3.73064727e-01 7.72277713e-01 1.48488593e+00 7.28365064e-01 1.33823037e-01 -5.17904349e-02 2.57125258e-01 2.37829521e-01 3.65133554e-01 5.68850219e-01 -1.44877851e+00 7.16898799e-01 7.36745775e-01 5.99686168e-02 -7.12949157e-01 -4.41158473e-01 -1.32476583e-01 -2.52407938e-01 6.79387271e-01 3.11354697e-01 1.43881366e-01 -1.13972449e+00 1.99387395e+00 8.01425353e-02 5.28781582e-03 3.10927391e-01 1.00408697e+00 6.35571182e-01 4.51310843e-01 2.40319431e-01 3.20082396e-01 1.36139798e+00 -1.08977807e+00 -4.81616378e-01 -5.85491359e-01 8.65336478e-01 -2.30230093e-01 1.66714990e+00 4.62346882e-01 -1.14578760e+00 -7.23800540e-01 -1.26593590e+00 -4.67442155e-01 -4.07865137e-01 7.01649040e-02 8.82112503e-01 1.95679352e-01 -9.98470604e-01 5.28822958e-01 -1.25231016e+00 -3.72052222e-01 3.36831480e-01 5.62193513e-01 -4.78017002e-01 -1.86538175e-01 -7.05265343e-01 9.45590079e-01 9.05234218e-01 -1.07181603e-02 -1.48691285e+00 -3.94007534e-01 -1.40666413e+00 1.37715906e-01 6.79006517e-01 -9.43414569e-01 1.56152475e+00 -8.96175683e-01 -1.97726023e+00 6.64006531e-01 2.02394407e-02 -2.32058629e-01 2.05575362e-01 -4.93652225e-01 1.72568917e-01 3.36566389e-01 1.36026859e-01 8.54467392e-01 6.58335984e-01 -1.33086014e+00 -2.30878860e-01 -4.85379487e-01 8.65984142e-01 3.52567434e-01 2.51670450e-01 -2.17046410e-01 -6.47955462e-02 -4.34665680e-01 3.45446140e-01 -1.10902691e+00 -2.30143502e-01 -2.29601517e-01 -2.79366016e-01 -1.58918306e-01 6.81998014e-01 -5.17857969e-01 5.54724753e-01 -2.16111541e+00 7.42164612e-01 -3.61746579e-01 -4.71010916e-02 -1.68372050e-01 -2.45520845e-01 6.39532328e-01 -9.77040678e-02 -1.53271601e-01 -1.74339563e-01 -2.40117759e-01 2.66043901e-01 5.80606163e-01 -5.20804405e-01 3.76357526e-01 3.40230554e-01 9.18700457e-01 -1.17387128e+00 -2.12120473e-01 4.40832943e-01 4.75260429e-02 -9.63150799e-01 5.65606594e-01 -7.64493525e-01 9.02223766e-01 -5.18796146e-01 3.85099351e-01 1.66972876e-01 -1.19557895e-01 1.15054257e-01 7.07973763e-02 3.08197830e-02 6.70071959e-01 -9.92614865e-01 2.40088081e+00 -7.75086343e-01 3.76659274e-01 1.38177395e-01 -9.96787071e-01 6.85848892e-01 2.68764466e-01 -1.64206401e-01 -3.24110657e-01 2.86940575e-01 -2.90377974e-03 3.07461917e-01 -9.68770742e-01 2.96002388e-01 -5.86776882e-02 -3.47568393e-01 3.77028793e-01 3.75665814e-01 -4.98631984e-01 1.40105486e-01 3.40783924e-01 1.17181373e+00 9.06084597e-01 3.92889798e-01 -9.37216505e-02 4.79268730e-01 9.99544337e-02 3.65518659e-01 8.20185900e-01 -8.48484635e-02 1.58919752e-01 5.70103884e-01 -2.50964612e-01 -7.31135428e-01 -1.24713194e+00 1.79106638e-01 1.41683757e+00 2.90902615e-01 -1.59160987e-01 -5.53317666e-01 -5.17714441e-01 -2.71704048e-01 1.29527223e+00 -5.40353656e-01 -3.58764976e-01 -8.17571998e-01 8.66236761e-02 3.93172771e-01 6.78696871e-01 4.99426395e-01 -1.29040873e+00 -1.19945252e+00 -1.09528959e-01 2.15446949e-02 -1.33608651e+00 -1.68405876e-01 3.93197566e-01 -1.24176288e+00 -1.15308750e+00 7.71923140e-02 -9.88932550e-01 1.01965427e+00 1.73573047e-01 1.04917252e+00 -7.99006298e-02 -2.42820308e-01 7.63917267e-01 -3.79350722e-01 -2.53248155e-01 -6.05213583e-01 -2.16683403e-01 -1.16278857e-01 -6.47620022e-01 2.53859550e-01 -7.67136276e-01 -4.08600390e-01 2.01684590e-02 -9.27733421e-01 4.45585698e-01 9.91176069e-01 8.78163278e-01 1.49522200e-01 -1.35195002e-01 2.38906339e-01 -6.53363764e-01 4.92831290e-01 -4.02047485e-01 -5.96621752e-01 -1.20113693e-01 -1.53581142e-01 4.20414269e-01 8.07381511e-01 -4.46547776e-01 -1.17860556e+00 1.49942666e-01 3.33361298e-01 -4.76690978e-01 -8.15274179e-01 3.29709500e-01 -4.00259465e-01 3.32102209e-01 6.76478088e-01 3.24578226e-01 -5.86307459e-02 -2.90496320e-01 5.94967186e-01 3.68046522e-01 7.79776692e-01 -1.23344660e+00 6.32093251e-01 2.65122294e-01 2.54846156e-01 -5.41375756e-01 -6.65764332e-01 -7.79552534e-02 -9.78995204e-01 9.01889205e-02 1.04543126e+00 -9.79040027e-01 -1.16280890e+00 9.22672004e-02 -1.21757257e+00 -7.35458493e-01 -7.16625378e-02 7.58667231e-01 -1.13498771e+00 1.95272371e-01 -9.03496742e-01 -5.37587166e-01 2.01558948e-01 -1.55817032e+00 1.17435408e+00 3.53641994e-02 -3.34635049e-01 -7.30992317e-01 -3.81544560e-01 3.84974748e-01 6.37818361e-03 4.67373937e-01 1.34272230e+00 -5.68049550e-01 -8.53376627e-01 -4.87435460e-02 8.58605951e-02 3.74194562e-01 2.96087831e-01 -3.76898289e-01 -8.40862930e-01 -2.95947760e-01 2.81673253e-01 -8.72461975e-01 4.65007722e-01 4.84242141e-02 1.37015152e+00 -3.82348269e-01 -1.23173378e-01 4.85283881e-01 1.08425105e+00 2.08058223e-01 4.44597811e-01 1.51537463e-01 6.60546303e-01 7.30338931e-01 6.80478632e-01 -2.56618951e-02 3.80895704e-01 5.03922582e-01 7.99242616e-01 5.39018214e-01 -1.57446861e-02 -4.48625147e-01 8.28016996e-01 7.97306478e-01 -6.66526332e-02 1.32903263e-01 -8.26423228e-01 2.25955263e-01 -1.85284901e+00 -8.53282452e-01 7.85756484e-02 2.06594825e+00 7.85394728e-01 1.64340168e-01 -1.44058824e-01 -1.12196349e-01 1.89783081e-01 -4.89185862e-02 -8.56228292e-01 -6.41953826e-01 4.49796647e-01 1.05406277e-01 1.90027505e-01 6.10254228e-01 -8.42113435e-01 1.18655860e+00 5.87714195e+00 5.38835302e-02 -9.52737212e-01 -1.89081490e-01 3.45220836e-03 -9.67424363e-02 1.87833682e-01 9.61768702e-02 -4.67435688e-01 7.82462303e-03 8.69914114e-01 3.80119756e-02 7.07673550e-01 9.75206673e-01 6.93047047e-02 -2.05707744e-01 -1.96742737e+00 6.69146597e-01 8.00990313e-02 -7.82922924e-01 1.71657950e-01 -2.24061355e-01 3.92859221e-01 7.46826530e-02 1.48529723e-01 8.45971704e-01 6.21481776e-01 -1.24218678e+00 7.74708331e-01 8.29944387e-02 3.99513304e-01 -3.42738003e-01 2.63297856e-01 8.49023819e-01 -7.76446760e-01 -3.84823471e-01 -2.19786957e-01 -6.64756656e-01 -1.85210705e-01 -4.09226149e-01 -9.29068506e-01 5.15682280e-01 3.92011493e-01 6.95271313e-01 -3.15905064e-01 3.83632481e-01 -9.41410601e-01 2.75932401e-01 -2.95553003e-02 6.06379919e-02 4.16925400e-01 -2.40231797e-01 4.15514261e-01 9.05399084e-01 4.78340685e-02 3.67754012e-01 5.35443783e-01 1.16658902e+00 9.75022763e-02 -3.23334277e-01 -8.18575680e-01 -1.33542463e-01 2.41098687e-01 6.93969488e-01 -5.39845645e-01 -2.92658597e-01 -6.20559692e-01 1.13519990e+00 4.96267766e-01 6.83676481e-01 -8.18574309e-01 -2.53091544e-01 6.82062924e-01 -3.34398061e-01 3.11954141e-01 -7.65880585e-01 -2.23133907e-01 -1.22905433e+00 1.32041716e-03 -1.13546097e+00 9.78659391e-02 -1.02785861e+00 -7.80573368e-01 3.73415440e-01 4.58539933e-01 -1.10887158e+00 -5.36371887e-01 -1.21905541e+00 -4.70702350e-01 7.61578858e-01 -1.21132743e+00 -1.09152615e+00 -4.59953308e-01 5.75203300e-01 9.47264075e-01 -3.89759131e-02 1.12617910e+00 -2.39410281e-01 -3.69263917e-01 6.65234178e-02 -6.24471188e-01 1.53014228e-01 2.59448379e-01 -1.29365802e+00 1.64001152e-01 6.22058332e-01 -6.86052293e-02 1.17605805e+00 9.16358650e-01 -4.98877198e-01 -1.88958836e+00 -7.95200646e-01 1.48508623e-01 -7.35512733e-01 6.81876659e-01 -6.33114636e-01 -8.58206511e-01 1.48469830e+00 3.74505192e-01 -1.77037209e-01 5.88388264e-01 1.31527439e-01 -5.77615678e-01 4.62734222e-01 -9.87127244e-01 1.02610624e+00 1.46821642e+00 -6.13440096e-01 -1.29047191e+00 4.87457871e-01 1.10081387e+00 -8.51804793e-01 -7.11682975e-01 2.45370284e-01 3.56317848e-01 -9.22435284e-01 9.00312424e-01 -1.02980602e+00 7.43898094e-01 -4.30680811e-01 -3.07473183e-01 -1.29258990e+00 -3.67998034e-01 -3.82280022e-01 -1.58617616e-01 5.32102287e-01 1.67555675e-01 -5.71194887e-01 3.42043400e-01 5.37669837e-01 -5.76150417e-01 -7.63802648e-01 -5.35904408e-01 -9.54468668e-01 1.50806800e-01 -4.23003972e-01 4.73312736e-01 6.91022038e-01 3.47010255e-01 5.25495708e-01 1.20183393e-01 6.33911848e-01 4.20464277e-01 3.44898224e-01 1.00859284e+00 -8.70250881e-01 -6.47882521e-01 -4.33686316e-01 -3.86778742e-01 -1.49818158e+00 7.38624394e-01 -1.22335362e+00 3.40409607e-01 -1.38402379e+00 1.45589277e-01 -1.66424096e-01 -8.52524638e-02 7.29595840e-01 4.33444530e-02 -5.79899251e-01 2.66936302e-01 1.11843251e-01 -4.79803473e-01 7.67754078e-01 1.52495277e+00 -1.12240732e-01 -2.11652994e-01 -2.75702477e-01 -4.18122202e-01 9.36294794e-01 8.28684866e-01 -3.22451830e-01 -8.80808711e-01 -7.66022265e-01 -1.78194065e-02 2.21973896e-01 6.88543439e-01 -9.85015631e-01 1.15482770e-01 -4.89060283e-01 2.07559913e-01 -1.76119089e-01 4.38979805e-01 -9.69107985e-01 -3.53450298e-01 7.84984171e-01 -6.50165737e-01 1.73851460e-01 4.87833351e-01 5.23699105e-01 -1.00455292e-01 -3.79227370e-01 3.56323719e-01 -4.15182471e-01 -1.01173842e+00 -6.87519461e-02 -3.83561999e-01 -1.70494959e-01 1.09830439e+00 -1.49008110e-01 -3.71739835e-01 -2.30091006e-01 -6.92723691e-01 3.80754977e-01 6.53855562e-01 6.81645393e-01 5.35036802e-01 -1.02500498e+00 -3.66694272e-01 2.04922676e-01 2.14944348e-01 3.76635164e-01 -9.11969543e-02 6.10139608e-01 -5.68006396e-01 4.93040591e-01 -4.53531176e-01 -7.76841044e-01 -8.37628007e-01 9.30363536e-01 1.23299249e-01 7.57611468e-02 -8.43489051e-01 6.25172853e-01 7.32543945e-01 -9.76280451e-01 2.95607299e-01 -1.01846766e+00 1.18274428e-01 -7.31329739e-01 3.06859463e-01 3.32028489e-03 -4.02399451e-01 -4.06673461e-01 -1.33962706e-01 3.37925196e-01 2.93710642e-02 -1.98632516e-02 1.24936509e+00 1.09312177e-01 -5.16808219e-02 8.26232910e-01 1.00530076e+00 -3.92208397e-01 -1.57091796e+00 -1.05854556e-01 2.82740314e-03 -3.90444428e-01 -1.69419393e-01 -7.63900280e-01 -4.71873760e-01 1.03891814e+00 1.32360235e-01 -3.27914894e-01 9.84296024e-01 7.77077451e-02 3.17272902e-01 1.05390859e+00 7.30616748e-01 -7.47559428e-01 5.17999709e-01 7.59953499e-01 1.20275080e+00 -1.35410714e+00 -1.00094579e-01 -4.84337658e-01 -5.76253355e-01 1.20649362e+00 9.60931838e-01 -3.66117954e-01 3.20248902e-02 1.35073319e-01 -1.85317636e-01 -1.85648292e-01 -9.08552289e-01 1.08082648e-02 -6.91621304e-02 4.96329606e-01 4.41345274e-01 6.03774143e-03 1.12116508e-01 4.01221126e-01 -3.85045260e-01 6.42646924e-02 5.12061059e-01 1.40126109e+00 -4.18875188e-01 -8.29794168e-01 -1.62432134e-01 5.69737516e-02 6.70584887e-02 1.21926680e-01 -1.02061473e-01 9.44323123e-01 -1.94157194e-02 8.32500279e-01 -4.04014587e-02 -1.11417949e-01 4.77506250e-01 2.89099962e-01 1.09826446e+00 -1.12194395e+00 -4.68754500e-01 -4.40811932e-01 -1.69055030e-01 -1.06013238e+00 -2.64235944e-01 -7.00894117e-01 -1.93606472e+00 1.00497201e-01 1.65199712e-01 -2.62175590e-01 5.97353041e-01 9.55118477e-01 3.91986251e-01 8.72175276e-01 1.65520698e-01 -1.19492638e+00 -9.66277480e-01 -1.09639788e+00 -2.74080455e-01 6.17713749e-01 4.35918421e-01 -8.21446359e-01 -2.96705842e-01 2.85122782e-01]	[4.504756927490234, 0.7058550119400024]
86d42ac7-7654-44b2-b339-2d8387179b41	cardiac-arrhythmia-detection-from-ecg-with	2010.03204	null	https://arxiv.org/abs/2010.03204v1	https://arxiv.org/pdf/2010.03204v1.pdf	Cardiac Arrhythmia Detection from ECG with Convolutional Recurrent Neural Networks	Except for a few specific types, cardiac arrhythmias are not immediately life-threatening. However, if not treated appropriately, they can cause serious complications. In particular, atrial fibrillation, which is characterized by fast and irregular heart beats, increases the risk of stroke. We propose three neural network architectures to detect abnormal rhythms from single-lead ECG signals. These architectures combine convolutional layers to extract high-level features pertinent for arrhythmia detection from sliding windows and recurrent layers to aggregate these features over signals of varying durations. We applied the neural networks to the dataset used for the challenge of Computing in Cardiology 2017 and a dataset built by joining three databases available on PhysioNet. Our architectures achieved an accuracy of 86.23% on the first dataset, similar to the winning entries of the challenge, and an accuracy of 92.02% on the second dataset.	['Damien Ferrario Mathieu Lemay', 'Ricard Delgado-Gonzalo', 'Jérôme Van Zaen']	2020-10-07	null	null	null	null	['arrhythmia-detection']	['medical']	[ 2.37858444e-01 -2.65440196e-01 -3.95747870e-02 -1.99130297e-01 -7.66600728e-01 -5.40803611e-01 -3.36930454e-02 4.53600198e-01 -5.16493976e-01 8.63089502e-01 8.95368829e-02 -5.15028894e-01 -2.41049677e-01 -5.35904586e-01 -2.87681043e-01 -4.08606321e-01 -6.46312058e-01 1.15794368e-01 -2.65171260e-01 1.51239797e-01 -8.27024579e-02 7.28432298e-01 -1.04728937e+00 6.20963633e-01 6.88395917e-01 1.23575103e+00 -6.46166325e-01 9.38836634e-01 3.17962050e-01 7.65303016e-01 -8.65047991e-01 9.08877030e-02 -1.46261025e-02 -6.30894661e-01 -5.35546780e-01 -4.14663911e-01 9.12169516e-02 -1.00156479e-01 -2.44804919e-01 2.04151109e-01 1.22999620e+00 -5.46915710e-01 4.57259685e-01 -7.18861341e-01 -7.45794252e-02 7.34192967e-01 -1.24753870e-01 1.02249885e+00 1.88973814e-01 1.69908717e-01 5.52410483e-01 -8.29439044e-01 4.79361713e-01 4.35944557e-01 1.37644136e+00 3.77464145e-01 -1.20383084e+00 -4.51348990e-01 -4.21437114e-01 -4.76091132e-02 -1.34036088e+00 -4.51099336e-01 5.93280137e-01 -4.33963716e-01 1.01845741e+00 3.69516253e-01 1.05129123e+00 1.34710252e+00 4.47598338e-01 3.81121486e-01 7.52150297e-01 -9.09553692e-02 -4.58684824e-02 -3.37706238e-01 3.69198650e-01 2.45969698e-01 4.38860297e-01 1.65625334e-01 -3.79258782e-01 -5.71396530e-01 4.92796034e-01 1.42940387e-01 -4.84538436e-01 2.07536280e-01 -1.63926458e+00 4.67049807e-01 1.15082711e-01 5.52546680e-01 -7.41885245e-01 8.51810500e-02 7.87781298e-01 4.76109445e-01 2.04157367e-01 7.87007630e-01 -7.85700500e-01 -5.39544344e-01 -9.11982000e-01 1.48519993e-01 8.14513445e-01 2.62603849e-01 -6.11988269e-02 2.18696013e-01 -5.93835115e-01 6.65088952e-01 -8.33028331e-02 2.42653161e-01 5.44301867e-01 -6.22754812e-01 1.46685094e-01 5.35415053e-01 -9.61489603e-03 -6.94128931e-01 -1.03267884e+00 -1.12981796e+00 -1.36992633e+00 -1.34624794e-01 5.47048986e-01 -5.64596057e-01 -9.56790984e-01 1.51379442e+00 -2.43350580e-01 3.82020205e-01 5.80194592e-02 6.79344594e-01 1.25592852e+00 3.05569559e-01 6.01799972e-03 -4.97897983e-01 1.49961269e+00 -2.91604519e-01 -6.73677981e-01 1.03942908e-01 7.69460201e-01 -4.86264884e-01 5.92573762e-01 6.87369168e-01 -1.19537461e+00 -4.08168197e-01 -1.20550489e+00 2.01186642e-01 -1.18323028e-01 4.02227819e-01 3.94184500e-01 8.81552458e-01 -1.10806012e+00 8.37169588e-01 -7.58914948e-01 -3.25496972e-01 7.60109246e-01 2.75387436e-01 -1.02367653e-02 4.90045220e-01 -1.40041578e+00 7.63222396e-01 4.59246449e-02 3.81413937e-01 -8.05905223e-01 -1.17503476e+00 -4.75310475e-01 8.85459259e-02 -2.42497191e-01 -8.00465226e-01 8.31137419e-01 -5.59715509e-01 -1.06699860e+00 9.64404702e-01 6.32859319e-02 -9.95067418e-01 6.71270847e-01 -4.23583806e-01 -7.06657469e-01 7.75229111e-02 -2.97804698e-02 -5.93277402e-02 6.74687028e-01 -4.66949731e-01 -2.93317080e-01 -2.79290915e-01 -3.98114592e-01 -1.93797588e-01 -6.20493703e-02 9.81588885e-02 -1.42536029e-01 -8.15746427e-01 -2.06080638e-02 -7.94834554e-01 -5.54724634e-01 -3.64263803e-01 -4.01057303e-01 8.93005878e-02 4.56378132e-01 -6.11126900e-01 1.50505400e+00 -2.39657021e+00 -2.18273085e-02 2.27199629e-01 6.06865108e-01 4.27865922e-01 7.57998154e-02 9.43664610e-02 -5.57333112e-01 4.95482057e-01 -3.36795956e-01 8.44422430e-02 -5.88787794e-01 -8.96979868e-02 -3.30177724e-01 3.77419859e-01 4.26989704e-01 1.10016322e+00 -6.33729517e-01 -3.64655256e-02 -3.98103856e-02 5.76091051e-01 -1.10316701e-01 1.11629874e-01 4.05729294e-01 4.84697163e-01 -2.56000668e-01 4.90115106e-01 3.13384235e-01 -3.40439737e-01 1.80939496e-01 -1.18559986e-01 9.79019478e-02 5.16315699e-01 -7.69101381e-01 1.70610511e+00 -2.22449154e-01 6.49638474e-01 -4.97820258e-01 -9.68176425e-01 1.02624226e+00 6.61342680e-01 9.68843162e-01 -4.40581590e-01 9.11538750e-02 3.78439128e-01 4.64142889e-01 -3.05754125e-01 -2.01076850e-01 1.25219256e-01 -2.09659085e-01 6.34635746e-01 -2.80114084e-01 1.26540691e-01 1.74664676e-01 3.81379505e-03 1.56614983e+00 -2.47360453e-01 5.02273381e-01 -3.07162166e-01 3.36049020e-01 -3.52988929e-01 9.26123917e-01 9.97754157e-01 -2.21478432e-01 1.10261250e+00 7.70666420e-01 -1.55198276e+00 -6.52556002e-01 -1.19694495e+00 -4.03988212e-01 2.00936288e-01 -4.58394259e-01 -8.50158691e-01 -3.76588911e-01 -5.82652450e-01 -1.63107276e-01 1.00072315e-02 -6.64675534e-01 -3.77390742e-01 -7.22182214e-01 -1.13397145e+00 1.28923869e+00 6.27365947e-01 3.23782742e-01 -1.36009192e+00 -1.34213018e+00 6.39818192e-01 -3.30028594e-01 -9.82548356e-01 -1.90489054e-01 4.50515300e-01 -8.82839382e-01 -1.28201163e+00 -7.99643457e-01 -4.47643340e-01 2.38677766e-02 -4.77635324e-01 1.69975972e+00 4.58247542e-01 -9.25445914e-01 -3.71183343e-02 -1.14092000e-01 -9.60570037e-01 -2.73235887e-01 5.27195930e-01 8.25842917e-02 1.92756224e-02 2.78741658e-01 -7.92864740e-01 -8.53634238e-01 -2.13941690e-02 -5.25137365e-01 -3.79370958e-01 5.55468321e-01 7.29040265e-01 4.41188157e-01 -5.38831711e-01 1.10357535e+00 -7.65356481e-01 9.31655169e-01 -4.02403802e-01 -1.11883685e-01 -1.53942510e-01 -6.02352977e-01 -4.15093362e-01 5.86976886e-01 -1.77480653e-01 -1.09564491e-01 2.02715948e-01 -1.35149553e-01 -3.57511759e-01 -2.67608643e-01 5.72073042e-01 3.72175395e-01 4.09856141e-01 1.00996125e+00 1.50984943e-01 -2.55928207e-02 -1.08557411e-01 -3.12329173e-01 4.58970606e-01 5.58965981e-01 -1.83680594e-01 2.36136645e-01 2.70202011e-01 1.69364549e-02 -7.62149096e-01 -6.61732554e-01 -2.67760903e-01 -4.08679575e-01 1.16524920e-01 9.50041831e-01 -9.53782022e-01 -6.59023106e-01 6.08225942e-01 -1.10604179e+00 -1.20652400e-01 -5.98436177e-01 4.65911448e-01 -4.12820578e-01 2.82412201e-01 -6.60777688e-01 -5.82371116e-01 -1.05150616e+00 -6.97293222e-01 6.78320646e-01 -7.20436871e-02 -7.31118619e-01 -6.52027488e-01 2.67613888e-01 -3.24322045e-01 7.20689058e-01 9.61936653e-01 8.33598852e-01 -8.41744304e-01 -1.18566953e-01 -2.30401844e-01 1.15563452e-01 2.48246104e-01 4.04780447e-01 9.98498350e-02 -9.97578442e-01 -3.02563041e-01 -1.08578727e-02 -9.73974690e-02 1.07959449e+00 6.99617743e-01 1.44524705e+00 1.55495703e-01 -3.31902444e-01 9.30493236e-01 8.65128219e-01 4.23498392e-01 8.53259027e-01 1.57491297e-01 4.18324888e-01 -2.77328759e-01 -1.17463181e-02 6.53337657e-01 5.85389324e-02 3.92309546e-01 1.48939908e-01 -5.69877386e-01 4.67567630e-02 6.18771732e-01 -4.16306555e-02 5.37957430e-01 -6.42996192e-01 2.23357111e-01 -1.32485306e+00 6.52969062e-01 -1.65751553e+00 -9.88926649e-01 -3.92594814e-01 2.24751711e+00 8.75854850e-01 2.50539154e-01 3.34408492e-01 4.88684028e-01 3.86184365e-01 6.67219907e-02 -6.12398028e-01 -6.49775207e-01 -4.17074978e-01 6.49616063e-01 -4.10285927e-02 -1.14565395e-01 -1.34897161e+00 1.80783838e-01 7.25385618e+00 -5.55492900e-02 -1.43451631e+00 -6.52988404e-02 1.00135279e+00 -3.70971859e-01 1.02731727e-01 -3.51149470e-01 -2.61319727e-01 4.87584889e-01 1.39465117e+00 -2.68278211e-01 -2.45760512e-02 3.34115326e-01 1.69181958e-01 3.69964361e-01 -1.10203648e+00 1.19940400e+00 -1.95529029e-01 -1.65845990e+00 -2.48831838e-01 -1.65109873e-01 3.38056803e-01 3.80870342e-01 -5.76548837e-02 3.75507683e-01 -3.65104020e-01 -1.57430434e+00 1.95205241e-01 7.44186580e-01 1.12713981e+00 -8.57451320e-01 1.01013708e+00 2.80367900e-02 -9.51189101e-01 -1.92757234e-01 2.43325029e-02 -1.11822784e-01 5.60417734e-02 1.06682014e+00 -7.55543113e-01 5.52923203e-01 1.13682950e+00 1.17730319e+00 -5.87065279e-01 1.22893417e+00 8.01079199e-02 9.22985435e-01 -4.95174706e-01 3.65218312e-01 -2.33911097e-01 2.12341040e-01 6.08885348e-01 1.31785452e+00 3.34428728e-01 4.77060229e-02 -3.39982957e-02 6.43994033e-01 -2.95244306e-02 -6.01226985e-02 -8.48293662e-01 1.29208267e-01 2.68991113e-01 1.39469373e+00 -5.36972523e-01 -4.57236260e-01 -1.31722078e-01 5.48003256e-01 1.82745960e-02 3.58467042e-01 -9.17248905e-01 -6.83473051e-01 4.39589500e-01 1.02534682e-01 -1.44249186e-01 2.04928160e-01 -7.67000258e-01 -1.02754569e+00 3.02494556e-01 -1.10206473e+00 6.54337227e-01 -2.80221850e-01 -1.03566945e+00 1.09409106e+00 -6.78711116e-01 -1.34533668e+00 -5.41091025e-01 -2.17559189e-01 -8.18498969e-01 1.05918896e+00 -1.20496547e+00 -6.55411065e-01 -4.07290250e-01 5.00447750e-01 1.33966342e-01 -2.30343744e-01 1.43945134e+00 4.90710109e-01 -4.70178097e-01 5.95946610e-01 -5.10478079e-01 4.57292289e-01 7.60996640e-01 -1.32576597e+00 7.57295966e-01 7.42284358e-01 1.27490044e-01 6.32776201e-01 3.49107772e-01 -2.86375195e-01 -9.06332433e-01 -1.24249494e+00 1.17710745e+00 -7.01941073e-01 8.62228051e-02 -8.58759508e-02 -8.99315298e-01 3.88922691e-01 7.57681951e-02 3.40621799e-01 7.85947084e-01 2.50035226e-01 -1.36048988e-01 -1.91238582e-01 -7.31264472e-01 2.25773558e-01 8.22844386e-01 -4.28580701e-01 -4.31050330e-01 1.94019794e-01 2.07037508e-01 -5.07883787e-01 -1.26265693e+00 9.08211946e-01 9.35860991e-01 -1.13036048e+00 1.11381960e+00 -8.49122524e-01 4.27886605e-01 -3.05804648e-02 4.65994447e-01 -1.33993351e+00 -4.02379543e-01 -1.10215354e+00 -2.04268545e-01 5.05446434e-01 7.59943306e-01 -6.94185674e-01 6.89539909e-01 -2.56047100e-02 -3.14575523e-01 -1.20617008e+00 -8.66284609e-01 -4.99655604e-01 1.12406418e-01 -4.66650695e-01 4.95194435e-01 9.48968291e-01 -1.66300789e-01 3.24331373e-01 -3.06259662e-01 -1.03506461e-01 2.77050346e-01 1.78952277e-01 3.89267296e-01 -1.68580925e+00 -5.71646057e-02 -4.97916490e-01 -4.61444885e-01 1.49812158e-02 -3.12512904e-01 -9.81640518e-01 -3.49760503e-01 -1.52865696e+00 3.03592905e-02 -4.54771370e-01 -9.99141335e-01 6.61676764e-01 -2.77408630e-01 5.49512267e-01 -6.79007843e-02 -4.63207699e-02 -1.37650311e-01 -2.06141502e-01 6.52395189e-01 -1.72613174e-01 -5.94623446e-01 3.64327908e-01 -7.02858567e-01 7.65286148e-01 1.15436411e+00 -4.34321702e-01 -2.27095425e-01 -7.72504434e-02 5.37084699e-01 2.30738491e-01 3.59439641e-01 -1.33141029e+00 -1.73767343e-01 4.77624208e-01 7.89210200e-01 -7.31298983e-01 1.07524462e-01 -3.81636351e-01 2.95981973e-01 9.05210078e-01 -3.99801254e-01 3.04238170e-01 4.55996990e-01 2.09274113e-01 -1.04054943e-01 5.58803618e-01 5.72150886e-01 3.25896069e-02 4.16576043e-02 4.81676012e-01 -7.89202988e-01 3.45765322e-01 8.12465489e-01 -1.46251157e-01 -9.93135124e-02 -3.04052442e-01 -1.17600369e+00 -3.32221650e-02 -1.45653173e-01 5.50659299e-01 7.89136648e-01 -1.26896191e+00 -1.21873248e+00 3.95660043e-01 2.40043297e-01 -5.02806008e-02 1.75673023e-01 1.33485818e+00 -6.08180463e-01 3.30854356e-01 -3.98659080e-01 -9.51904476e-01 -1.16193080e+00 2.09879458e-01 8.79502535e-01 -4.71702725e-01 -1.09885001e+00 5.05524158e-01 -3.47829789e-01 -1.85428392e-02 1.84320182e-01 -7.61721075e-01 -3.54201227e-01 1.02021880e-01 7.25507021e-01 2.59611517e-01 5.91891050e-01 1.36504527e-02 -7.58369923e-01 4.47255701e-01 2.62533501e-02 3.40919465e-01 1.27936447e+00 4.63340521e-01 -1.87562540e-01 6.69392228e-01 8.35679531e-01 -1.83707491e-01 -4.74781156e-01 -1.50297210e-02 7.58454502e-02 2.15348691e-01 -1.48699492e-01 -1.14793849e+00 -1.29802012e+00 1.01269436e+00 9.03814375e-01 4.38264072e-01 1.29911900e+00 -4.71754164e-01 7.39841580e-01 4.10156429e-01 2.95432415e-02 -4.99767333e-01 -2.65368909e-01 5.23972094e-01 8.16767216e-01 -6.95638239e-01 3.54895331e-02 -1.24737034e-02 -3.34956914e-01 1.36282134e+00 1.23166710e-01 -2.62667924e-01 8.06681871e-01 5.27114749e-01 5.25604427e-01 -3.47939968e-01 -9.72414076e-01 1.83142528e-01 2.89062917e-01 5.16161263e-01 8.81186247e-01 3.08223795e-02 -5.46039045e-01 9.77841437e-01 1.90616436e-02 4.95553553e-01 6.51510477e-01 8.94102752e-01 1.24777451e-01 -8.39716256e-01 -3.71227190e-02 9.06611085e-01 -1.07686079e+00 -3.45587790e-01 -5.06852567e-01 4.82077509e-01 7.59017467e-02 7.63109207e-01 2.96216719e-02 -1.56460166e-01 4.70044822e-01 3.22806627e-01 1.20263368e-01 -4.60728198e-01 -1.21761250e+00 -5.28869703e-02 3.73785287e-01 -7.56534696e-01 -2.38918513e-01 -5.57246208e-01 -1.13574874e+00 3.40912551e-01 3.44365984e-01 -2.61387061e-02 3.99672061e-01 7.15099096e-01 8.83369327e-01 1.16204345e+00 4.92134899e-01 -3.55642676e-01 -5.04912674e-01 -1.10993350e+00 -5.66835761e-01 4.25244212e-01 7.87032187e-01 -8.00860077e-02 -3.49726826e-01 2.68867910e-02]	[14.334147453308105, 3.3007349967956543]
d0d2c206-2b3b-47a2-9fb9-e65427383d5f	invisible-backdoor-attacks-using-data	2207.04209	null	https://arxiv.org/abs/2207.04209v1	https://arxiv.org/pdf/2207.04209v1.pdf	Invisible Backdoor Attacks Using Data Poisoning in the Frequency Domain	With the broad application of deep neural networks (DNNs), backdoor attacks have gradually attracted attention. Backdoor attacks are insidious, and poisoned models perform well on benign samples and are only triggered when given specific inputs, which cause the neural network to produce incorrect outputs. The state-of-the-art backdoor attack work is implemented by data poisoning, i.e., the attacker injects poisoned samples into the dataset, and the models trained with that dataset are infected with the backdoor. However, most of the triggers used in the current study are fixed patterns patched on a small fraction of an image and are often clearly mislabeled, which is easily detected by humans or defense methods such as Neural Cleanse and SentiNet. Also, it's difficult to be learned by DNNs without mislabeling, as they may ignore small patterns. In this paper, we propose a generalized backdoor attack method based on the frequency domain, which can implement backdoor implantation without mislabeling and accessing the training process. It is invisible to human beings and able to evade the commonly used defense methods. We evaluate our approach in the no-label and clean-label cases on three datasets (CIFAR-10, STL-10, and GTSRB) with two popular scenarios (self-supervised learning and supervised learning). The results show our approach can achieve a high attack success rate (above 90%) on all the tasks without significant performance degradation on main tasks. Also, we evaluate the bypass performance of our approach for different kinds of defenses, including the detection of training data (i.e., Activation Clustering), the preprocessing of inputs (i.e., Filtering), the detection of inputs (i.e., SentiNet), and the detection of models (i.e., Neural Cleanse). The experimental results demonstrate that our approach shows excellent robustness to such defenses.	['Kai Chen', 'Ruigang Liang', 'Peizhuo Lv', 'Chang Yue']	2022-07-09	null	null	null	null	['data-poisoning']	['adversarial']	[ 8.96340311e-02 -1.77319348e-01 -2.53685508e-02 -1.08150221e-01 -1.86958134e-01 -1.07116425e+00 6.06240094e-01 -7.98142478e-02 -5.35454512e-01 4.40290004e-01 -5.98406315e-01 -4.49492782e-01 2.15296805e-01 -1.03196979e+00 -8.27308118e-01 -1.00431538e+00 1.11173607e-01 1.20920807e-01 3.67282212e-01 -1.85801819e-01 1.37865335e-01 5.37035704e-01 -1.28387463e+00 3.06612074e-01 8.22655976e-01 9.85837996e-01 -3.84641975e-01 1.37040958e-01 4.70536239e-02 8.01437557e-01 -1.30335486e+00 -7.71303713e-01 3.01653504e-01 -1.93015382e-01 -4.39418674e-01 -3.56667399e-01 3.53197068e-01 -4.03454214e-01 -5.49313009e-01 1.81496787e+00 3.25493306e-01 -2.50576735e-01 4.16568905e-01 -1.52743769e+00 -7.59800673e-01 6.62450194e-01 -5.89298844e-01 2.40686417e-01 -6.10660426e-02 3.90225202e-01 3.98546129e-01 -7.47360587e-01 2.49265313e-01 1.39356363e+00 5.03298700e-01 1.05916262e+00 -1.06664383e+00 -1.42079449e+00 1.24562204e-01 1.38931051e-01 -1.38345301e+00 -4.01300669e-01 8.25614035e-01 -1.95058450e-01 5.24451673e-01 5.26216447e-01 1.69371501e-01 1.98203444e+00 3.93835336e-01 7.91455090e-01 1.21622777e+00 -1.75952271e-01 5.78264236e-01 3.63495171e-01 6.10182762e-01 5.60786605e-01 5.65479815e-01 5.80639064e-01 -4.53472465e-01 -6.08330190e-01 4.38351810e-01 3.46560836e-01 -2.57762909e-01 2.65106142e-01 -7.64616132e-01 8.44351411e-01 4.18524802e-01 9.09851193e-02 -2.35787287e-01 -3.56187858e-03 4.79594797e-01 2.75563478e-01 4.23979342e-01 3.76459628e-01 -2.90637851e-01 3.21051955e-01 -5.96857131e-01 -9.65803042e-02 9.11427319e-01 6.70729220e-01 4.26930457e-01 3.26009840e-01 -1.80418864e-01 4.93443489e-01 1.28407672e-01 9.48303401e-01 5.53370535e-01 -3.04319739e-01 3.67872566e-01 4.45625782e-01 -1.15736879e-01 -1.23041761e+00 -2.20984399e-01 -6.36964560e-01 -1.00037706e+00 3.22650641e-01 3.33926350e-01 -4.75255549e-01 -1.35546243e+00 1.98960686e+00 4.37008381e-01 5.30467033e-01 1.83521986e-01 7.14136541e-01 6.99945033e-01 5.32545030e-01 2.68789202e-01 -9.04411525e-02 1.46663177e+00 -7.86617577e-01 -9.24891531e-01 -3.01069677e-01 5.44914126e-01 -2.55365968e-01 1.10611093e+00 7.76954889e-01 -4.00789976e-01 -2.12723285e-01 -1.22975004e+00 5.65676391e-01 -8.80507708e-01 -3.74016374e-01 6.17520988e-01 1.25271535e+00 -5.48332453e-01 5.71940184e-01 -7.46702313e-01 -5.57337180e-02 8.28625321e-01 4.44699526e-01 -3.64889741e-01 -8.52971897e-02 -1.50408423e+00 4.87764359e-01 3.83886009e-01 -8.58208239e-02 -1.68102622e+00 -4.39642072e-01 -4.92297500e-01 1.44255579e-01 5.07573903e-01 -2.27374598e-01 7.94070125e-01 -9.82068121e-01 -1.16940856e+00 7.98261285e-01 3.37793916e-01 -6.30694151e-01 4.04996306e-01 -3.36096853e-01 -7.03989744e-01 1.78127632e-01 -1.05355464e-01 3.01355928e-01 1.34080744e+00 -1.32628405e+00 -4.43492889e-01 -4.38673556e-01 2.17073545e-01 -3.17078203e-01 -1.16757882e+00 3.88128251e-01 -1.18365036e-02 -8.17783177e-01 -1.28224179e-01 -7.59734273e-01 -3.36466022e-02 -4.21886295e-01 -1.03562987e+00 -1.01426937e-01 1.23405445e+00 -3.40661347e-01 1.21868169e+00 -2.56273484e+00 -3.14241350e-01 2.86335468e-01 4.82431471e-01 8.46399128e-01 -1.14543609e-01 1.84722126e-01 -2.54096806e-01 7.54918158e-01 -3.35753977e-01 -3.98459226e-01 -8.41561109e-02 2.76619524e-01 -9.67281103e-01 6.57650173e-01 -1.23717755e-01 6.71256959e-01 -8.64773989e-01 -1.45709559e-01 -1.49534065e-02 3.72041792e-01 -2.07857728e-01 1.71151027e-01 3.98508646e-02 1.15444161e-01 -4.93139386e-01 9.97894883e-01 7.20879138e-01 7.96954036e-02 -3.17606658e-01 -8.59596282e-02 2.59563833e-01 1.21670812e-02 -8.32274914e-01 8.87764275e-01 -7.36604165e-03 1.78125352e-01 1.62913161e-03 -7.32164025e-01 8.74292970e-01 5.24427354e-01 -9.53215808e-02 -3.81574452e-01 4.98730034e-01 1.83370516e-01 4.47519831e-02 -3.32188487e-01 -2.20757991e-01 1.63493641e-02 -1.97051719e-01 6.62594914e-01 2.06557922e-02 5.06552339e-01 -1.65956169e-01 2.29862988e-01 1.44146073e+00 -6.98308289e-01 9.32528079e-03 -2.22594902e-01 3.29040438e-01 7.10536018e-02 7.90435255e-01 1.13005435e+00 -3.75225931e-01 1.57270238e-01 4.42509651e-01 -5.77961862e-01 -4.17806238e-01 -1.05544555e+00 -1.36089876e-01 8.36397350e-01 4.67569739e-01 -2.89885581e-01 -1.29790366e+00 -1.27495694e+00 1.19221592e-02 8.64978731e-01 -7.34735548e-01 -9.46392477e-01 -2.50566781e-01 -9.84332800e-01 1.34124398e+00 2.75590062e-01 8.96890581e-01 -1.37772894e+00 -4.98140812e-01 4.89320010e-02 7.70927966e-02 -1.01382923e+00 -2.01067194e-01 4.20956314e-01 -7.80058682e-01 -1.18877077e+00 -1.54766321e-01 -4.67391133e-01 8.31094325e-01 3.95958573e-01 6.95758224e-01 4.41262424e-01 -1.75589830e-01 -1.38270214e-01 -3.20421338e-01 -7.64013767e-01 -2.98059106e-01 -7.66496658e-02 6.22537136e-01 4.80678380e-01 6.64752662e-01 -5.50051510e-01 -2.89748311e-01 6.29005134e-01 -1.19448030e+00 -5.61445057e-01 4.98821080e-01 8.46627057e-01 4.66326803e-01 5.05804002e-01 7.15176880e-01 -1.38503039e+00 8.53959918e-01 -7.06826329e-01 -4.11215693e-01 3.56108546e-01 -3.42771530e-01 -3.84944201e-01 1.06542349e+00 -1.12110007e+00 -6.53383970e-01 -2.75519520e-01 -1.27404466e-01 -9.83425319e-01 -5.31283498e-01 1.96715802e-01 -5.84147573e-01 -3.91065150e-01 1.14373791e+00 1.64657146e-01 -4.01496172e-01 -6.34986639e-01 5.86750023e-02 6.90474331e-01 6.58084989e-01 -4.14622515e-01 1.38237131e+00 7.82802939e-01 -2.39475772e-01 -6.22010887e-01 -8.86960149e-01 -2.33371835e-02 -5.43980151e-02 -2.28589345e-02 7.63315499e-01 -5.88626325e-01 -6.76050782e-01 1.08295751e+00 -1.20784366e+00 -2.10082352e-01 -1.04828715e-01 1.64867908e-01 2.89043218e-01 3.62776130e-01 -8.37494433e-01 -9.24344361e-01 -6.89984739e-01 -1.08577967e+00 6.05551898e-01 4.55786020e-01 1.59109086e-01 -8.73671770e-01 -3.61321121e-01 -2.39326861e-02 2.77936488e-01 5.12432396e-01 9.96478856e-01 -1.37575376e+00 -3.35934341e-01 -6.19413912e-01 1.07166253e-01 5.76879084e-01 1.15673229e-01 -6.34437501e-02 -1.59956205e+00 -3.64137501e-01 7.54328251e-01 -5.07068872e-01 8.72372746e-01 -6.56723008e-02 1.31491506e+00 -5.63597322e-01 -5.62334776e-01 8.67609084e-01 1.05275917e+00 6.28897548e-01 6.90929294e-01 2.59522676e-01 9.22463417e-01 5.88249087e-01 4.28995401e-01 8.74764249e-02 -3.45683515e-01 1.75854698e-01 9.44106400e-01 -2.86752015e-01 3.54963720e-01 -3.12153250e-01 5.65870464e-01 3.95286083e-01 3.87283593e-01 -3.96404773e-01 -9.16671157e-01 1.83369204e-01 -1.64536572e+00 -8.66493642e-01 3.19255926e-02 2.20976901e+00 7.94437885e-01 4.40219760e-01 -2.27232620e-01 4.73193318e-01 8.77517760e-01 -1.10906176e-02 -7.97035873e-01 -3.24527919e-01 -2.06265613e-01 3.10550898e-01 6.46391273e-01 2.08216071e-01 -1.46552026e+00 1.26950514e+00 5.64605141e+00 1.27760768e+00 -1.17307281e+00 4.35198069e-01 8.51695538e-01 -4.93221283e-02 -3.09072547e-02 -2.42109790e-01 -9.66409445e-01 6.78718686e-01 7.81966150e-01 1.94507822e-01 6.13356292e-01 1.07050180e+00 -2.30561763e-01 3.13485265e-01 -1.02804112e+00 9.25217271e-01 7.06260800e-02 -9.14264798e-01 -7.50539359e-03 2.15454832e-01 5.06636918e-01 -2.70326454e-02 2.69358128e-01 4.76578295e-01 4.44303960e-01 -1.15442801e+00 7.48794079e-01 1.87973946e-01 7.42441237e-01 -1.00559628e+00 7.68537164e-01 9.05640483e-01 -5.99125803e-01 -4.23366487e-01 -4.96483564e-01 2.87407100e-01 -2.28613421e-01 8.36367130e-01 -1.89851090e-01 2.04600677e-01 8.02390277e-01 3.32990915e-01 -5.97591281e-01 7.63008177e-01 -7.16584802e-01 1.04286480e+00 -5.14540136e-01 -1.20264795e-02 1.86938673e-01 3.35468240e-02 6.82961166e-01 9.55833554e-01 -1.63117602e-01 1.08134158e-01 2.06318110e-01 9.67039168e-01 -3.74977142e-01 -2.58216709e-01 -9.23498809e-01 -1.56560503e-02 7.73406625e-01 1.31302452e+00 -7.73472071e-01 -3.93567204e-01 7.44613074e-03 8.11879039e-01 1.85606897e-01 5.72537005e-01 -1.03622746e+00 -6.54063940e-01 7.46991575e-01 -2.91972727e-01 -1.67678103e-01 2.13749915e-01 -5.55500150e-01 -1.14253891e+00 -2.46919040e-02 -1.19868791e+00 4.60545063e-01 -2.35994890e-01 -1.60996342e+00 8.88163090e-01 -1.47154242e-01 -8.00084174e-01 1.85558945e-01 -5.87777674e-01 -9.50218916e-01 6.96792662e-01 -1.21795273e+00 -7.34734654e-01 -1.56242192e-01 1.05137610e+00 1.58336848e-01 -3.95854473e-01 8.72144401e-01 4.51224118e-01 -1.14409125e+00 1.00311732e+00 -1.86826542e-01 4.90033478e-01 6.13453031e-01 -8.57711315e-01 5.40713429e-01 1.15946865e+00 3.35224569e-01 1.00598717e+00 4.66800183e-01 -8.41670394e-01 -1.23500073e+00 -1.24853516e+00 4.81818795e-01 -5.37198305e-01 5.03630102e-01 -9.51664388e-01 -1.06986117e+00 4.97671336e-01 -9.51286927e-02 1.69448242e-01 7.31986642e-01 -6.25653490e-02 -7.49565005e-01 -1.39535770e-01 -1.60218310e+00 7.04506695e-01 9.87263918e-01 -5.70985675e-01 -4.27865207e-01 6.43174112e-01 8.11093748e-01 -1.57659054e-01 -2.67440021e-01 3.60772818e-01 9.62951258e-02 -8.48668575e-01 1.02409315e+00 -7.49102950e-01 -2.45264526e-02 -1.89560026e-01 -9.84672830e-02 -1.11390126e+00 -1.47012070e-01 -7.51123250e-01 -4.96509045e-01 1.38621843e+00 2.36021534e-01 -1.14274907e+00 6.38249457e-01 4.11832958e-01 -3.05669685e-03 -6.78232968e-01 -1.01111591e+00 -1.04262483e+00 -2.61220410e-02 -3.17093045e-01 8.62099051e-01 1.35045123e+00 -2.04298645e-01 6.12106845e-02 -4.63804841e-01 5.53543985e-01 9.96833563e-01 -3.91729593e-01 6.16359234e-01 -1.18760121e+00 -2.44054824e-01 -1.46890998e-01 -1.92452118e-01 -6.14314139e-01 1.42741859e-01 -7.21240819e-01 -1.68260977e-01 -6.48015916e-01 -7.68626705e-02 -4.64189112e-01 -6.82126343e-01 1.11711776e+00 -2.49875888e-01 4.32334721e-01 7.99882933e-02 5.87087929e-01 -2.13701382e-01 3.06509346e-01 8.06151211e-01 -3.05552065e-01 2.19318364e-03 -1.08648958e-02 -8.22273374e-01 9.57825601e-01 1.04964387e+00 -1.21570337e+00 -5.34904182e-01 -4.28899199e-01 -9.05557275e-02 -4.87295628e-01 5.88589787e-01 -1.16882813e+00 2.99320877e-01 -5.31043075e-02 2.34232247e-01 -2.05898911e-01 1.95430115e-01 -9.09240007e-01 -1.10557459e-01 7.22654939e-01 1.05314376e-02 -8.88980106e-02 2.09833115e-01 6.64625525e-01 3.82466651e-02 -3.66458923e-01 9.16411281e-01 4.21086000e-03 -2.88246602e-01 4.43997592e-01 -2.45153785e-01 7.00757504e-02 1.23107100e+00 -1.16299018e-02 -9.46213484e-01 2.60995030e-02 -3.95473033e-01 3.15864235e-02 3.13369244e-01 3.53448778e-01 7.43355334e-01 -1.19032848e+00 -2.70642787e-01 5.10266244e-01 -1.29490837e-01 -1.62248433e-01 -7.21458718e-02 5.23617327e-01 -2.02484593e-01 1.79151837e-02 -1.10049285e-01 -5.09374499e-01 -1.16955781e+00 1.01790082e+00 4.64011312e-01 -1.33168519e-01 -5.64652443e-01 9.71983612e-01 5.97938001e-01 -2.97407568e-01 5.59711814e-01 8.90247300e-02 -1.53630152e-01 -1.36312023e-01 8.30743670e-01 5.84203005e-02 2.74317637e-02 -2.57129282e-01 -5.95326066e-01 -7.27807230e-04 -3.61517549e-01 1.84801966e-01 9.06114399e-01 6.50882900e-01 -1.44437388e-01 5.86642101e-02 9.25559103e-01 -2.22787876e-02 -1.01583457e+00 -1.37069777e-01 -1.74425259e-01 -3.89954656e-01 3.20927501e-02 -9.31883991e-01 -1.37270176e+00 1.06235445e+00 6.92922652e-01 5.10193348e-01 1.04097378e+00 -2.81197876e-01 9.89737153e-01 5.75113297e-01 5.72315454e-01 -7.74565578e-01 1.48548543e-01 4.06308621e-01 4.16298658e-01 -9.79785621e-01 -3.43715727e-01 -4.82829452e-01 -4.03277487e-01 7.23272622e-01 7.55154788e-01 -1.94883198e-01 6.55530393e-01 4.32926387e-01 2.92239994e-01 -4.45358247e-01 -6.18145764e-01 3.65760118e-01 -1.70373335e-01 6.78366125e-01 -5.14899492e-01 1.09996371e-01 8.35325867e-02 1.00699914e+00 -4.78679221e-03 -6.22887135e-01 3.64149421e-01 9.11615789e-01 -4.62653250e-01 -8.78207743e-01 -6.97675943e-01 3.59730512e-01 -8.30867589e-01 -2.95640916e-01 -7.96071649e-01 6.34536982e-01 3.00923467e-01 1.34582639e+00 -3.29175889e-01 -9.98191535e-01 3.45431477e-01 1.49590760e-01 -2.16207042e-01 -7.66395271e-01 -1.10043883e+00 -2.18309954e-01 -1.82977781e-01 -6.14934742e-01 1.36792555e-01 -2.38363460e-01 -1.01611638e+00 -4.04614955e-01 -5.68279326e-01 1.71448067e-01 6.91672623e-01 9.15080369e-01 1.91066176e-01 3.52471381e-01 9.38308537e-01 -4.33896929e-01 -1.03572357e+00 -8.56004596e-01 -6.38705492e-01 6.01816714e-01 8.74500126e-02 -8.62491786e-01 -9.35072601e-01 -2.02258855e-01]	[5.7022576332092285, 7.765721321105957]
3e725718-1ba0-44a6-a433-27f4c98ef693	adversarial-robustness-certification-for	2306.13614	null	https://arxiv.org/abs/2306.13614v1	https://arxiv.org/pdf/2306.13614v1.pdf	Adversarial Robustness Certification for Bayesian Neural Networks	We study the problem of certifying the robustness of Bayesian neural networks (BNNs) to adversarial input perturbations. Given a compact set of input points $T \subseteq \mathbb{R}^m$ and a set of output points $S \subseteq \mathbb{R}^n$, we define two notions of robustness for BNNs in an adversarial setting: probabilistic robustness and decision robustness. Probabilistic robustness is the probability that for all points in $T$ the output of a BNN sampled from the posterior is in $S$. On the other hand, decision robustness considers the optimal decision of a BNN and checks if for all points in $T$ the optimal decision of the BNN for a given loss function lies within the output set $S$. Although exact computation of these robustness properties is challenging due to the probabilistic and non-convex nature of BNNs, we present a unified computational framework for efficiently and formally bounding them. Our approach is based on weight interval sampling, integration, and bound propagation techniques, and can be applied to BNNs with a large number of parameters, and independently of the (approximate) inference method employed to train the BNN. We evaluate the effectiveness of our methods on various regression and classification tasks, including an industrial regression benchmark, MNIST, traffic sign recognition, and airborne collision avoidance, and demonstrate that our approach enables certification of robustness and uncertainty of BNN predictions.	['Marta Kwiatkowska', 'Luca Laurenti', 'Andrea Patane', 'Matthew Wicker']	2023-06-23	null	null	null	null	['adversarial-robustness', 'traffic-sign-recognition']	['adversarial', 'computer-vision']	[ 3.43571991e-01 4.45448995e-01 8.19207653e-02 -3.12475085e-01 -8.88821423e-01 -6.65926695e-01 3.66286449e-02 -5.93485218e-03 -4.51662391e-01 9.48539257e-01 -7.14666188e-01 -5.60951650e-01 -7.50970721e-01 -1.01512587e+00 -1.31887650e+00 -1.04465604e+00 -3.54915589e-01 4.08743262e-01 3.20366830e-01 -6.26374558e-02 -6.39292970e-02 8.15417528e-01 -1.10017312e+00 -3.68132353e-01 5.22161126e-01 1.63052750e+00 -6.47275567e-01 6.50703967e-01 5.69003582e-01 3.34528804e-01 -9.84340608e-01 -6.67905629e-01 4.79097635e-01 3.82316373e-02 -4.52626675e-01 -5.80318749e-01 3.76185387e-01 -1.12130083e-01 -5.25355756e-01 1.58551669e+00 3.65211874e-01 5.44352710e-01 8.72324228e-01 -1.53795218e+00 6.91904081e-03 8.57499659e-01 -2.37827674e-01 -5.03734946e-02 -1.75516799e-01 1.61671415e-01 6.80689037e-01 -1.06189445e-01 2.07690567e-01 1.05345488e+00 8.22414875e-01 7.02237308e-01 -1.36503184e+00 -1.12337148e+00 3.32568318e-01 -3.74974340e-01 -1.48053420e+00 -3.55476409e-01 3.57776582e-01 -4.37472910e-01 5.39227247e-01 2.67734081e-01 -2.84494553e-02 9.16544557e-01 3.64804149e-01 2.30437428e-01 6.84679389e-01 -8.79819915e-02 6.65597200e-01 1.19834118e-01 2.00499713e-01 6.93630219e-01 2.88691580e-01 6.38068736e-01 -3.29576820e-01 -3.35980535e-01 3.90882730e-01 -1.50995716e-01 -3.49185973e-01 -2.20862269e-01 -5.98655224e-01 8.42261434e-01 4.42948908e-01 -2.08763748e-01 -4.20682020e-02 6.77717865e-01 2.95281559e-01 3.10327351e-01 1.84085041e-01 2.76477396e-01 -5.65294087e-01 3.07447910e-01 -7.67122686e-01 4.70836967e-01 9.66841877e-01 9.89551306e-01 4.02717322e-01 2.56130546e-01 -1.22072399e-01 3.74814928e-01 2.57472038e-01 1.05212629e+00 -2.07734689e-01 -1.12126088e+00 6.89600766e-01 5.32717332e-02 1.53556272e-01 -9.52130020e-01 -2.72323489e-01 -2.31978387e-01 -8.90827060e-01 7.45693803e-01 7.43189037e-01 -3.52446944e-01 -8.75381291e-01 2.10959291e+00 8.37073177e-02 5.30746691e-02 9.98799577e-02 5.45215011e-01 1.67567819e-01 4.69494760e-01 -1.60991207e-01 -2.09509835e-01 7.02120602e-01 -3.72005142e-02 -2.44795322e-01 -2.65779551e-02 1.72401264e-01 -1.06813155e-01 4.56504017e-01 5.64651132e-01 -1.15784800e+00 -2.70581663e-01 -1.38412738e+00 6.48877263e-01 -4.41486865e-01 -4.58140910e-01 6.46433383e-02 1.06067264e+00 -5.97406805e-01 1.00189912e+00 -8.97116601e-01 4.44933414e-01 6.23963773e-01 7.14953840e-01 -3.17715704e-01 -1.84729695e-01 -1.36569953e+00 7.72355914e-01 4.21099454e-01 2.05543160e-01 -1.21156812e+00 -7.47417331e-01 -9.16458070e-01 -2.18430813e-02 4.80368018e-01 -2.98465520e-01 1.11229575e+00 -5.10674775e-01 -1.23793542e+00 1.95901349e-01 2.35340387e-01 -9.35498118e-01 7.40882456e-01 8.63737836e-02 -3.47628951e-01 9.46280956e-02 -2.69004732e-01 4.04179484e-01 1.16716826e+00 -9.89677131e-01 -5.96803665e-01 -6.15966201e-01 1.52345866e-01 -3.21377307e-01 -5.20446822e-02 -8.95856395e-02 -1.60729885e-01 -4.78183270e-01 1.30125523e-01 -9.82617974e-01 -4.39251333e-01 6.74041510e-02 -8.43214750e-01 7.91925639e-02 7.16064990e-01 -4.45331872e-01 9.38334882e-01 -2.08194637e+00 3.34254801e-02 1.07984614e+00 -9.75216255e-02 1.54521719e-01 2.20178992e-01 -3.60914797e-01 -7.74609223e-02 3.06969196e-01 -6.76221073e-01 -7.80527145e-02 4.50652182e-01 2.84068465e-01 -8.33117425e-01 7.73416579e-01 5.39403781e-02 3.70712668e-01 -5.46121776e-01 -1.52464539e-01 1.65858164e-01 3.70612144e-01 -5.53265750e-01 9.45776924e-02 -4.03560549e-01 1.56612039e-01 -4.72446531e-01 5.08005321e-01 6.18363023e-01 3.23081672e-01 -1.25116348e-01 1.21736722e-02 4.35324907e-01 6.16035238e-03 -1.56746340e+00 8.82043421e-01 -2.42268980e-01 3.33733141e-01 2.42924303e-01 -1.07841659e+00 7.66656637e-01 2.77550668e-01 3.12678605e-01 -2.43701041e-01 3.22026730e-01 1.13196941e-02 -6.42070174e-02 1.75014719e-01 1.60486817e-01 -3.93162191e-01 -6.19884729e-01 4.25397635e-01 7.02586100e-02 -4.55416590e-01 1.00516304e-02 -5.60173504e-02 1.35639548e+00 -9.71431285e-02 -1.95940450e-01 -1.30870327e-01 2.69307673e-01 -5.09187996e-01 7.69450188e-01 1.18095791e+00 -3.29405993e-01 2.61740506e-01 8.12470913e-01 2.73564178e-02 -7.06891596e-01 -1.64392865e+00 -4.35124278e-01 8.74973357e-01 1.08968139e-01 2.97369778e-01 -7.78736293e-01 -1.10002685e+00 3.33783031e-01 1.01051581e+00 -6.48308992e-01 -3.57993543e-01 -2.69237578e-01 -6.13078654e-01 8.98197949e-01 5.95946968e-01 1.99539676e-01 -8.07395518e-01 -3.61397803e-01 -2.88929790e-02 2.48996094e-01 -1.02166486e+00 -3.48778516e-01 6.48047745e-01 -8.86263371e-01 -1.09798992e+00 -2.70329565e-01 -1.96773961e-01 8.23598504e-01 -6.68695331e-01 8.63116264e-01 -3.94893706e-01 -1.87894478e-01 3.14830869e-01 3.34001064e-01 -7.23522425e-01 -5.65098822e-01 -2.66372800e-01 4.55066264e-01 -2.88915128e-01 -3.07976842e-01 -5.03661156e-01 -1.66499928e-01 6.57623231e-01 -9.14653242e-01 -7.83718944e-01 1.00939788e-01 5.92849910e-01 8.29027832e-01 7.75082767e-01 4.25577015e-01 -7.02505350e-01 3.01777542e-01 -2.72047341e-01 -1.31999171e+00 2.78189957e-01 -3.65032256e-01 3.18891048e-01 7.81756401e-01 -5.10915279e-01 -4.36849743e-01 -1.28027378e-02 -9.88721550e-02 -6.98947430e-01 -8.44386816e-02 1.71316415e-01 -4.72767800e-01 -1.65323824e-01 7.50710666e-01 -2.76974201e-01 -5.98210730e-02 7.22110132e-03 1.90697655e-01 1.83314666e-01 7.27380812e-01 -9.65386629e-01 1.19099927e+00 3.95567268e-01 6.25191212e-01 -4.63641852e-01 -7.15832055e-01 2.21350133e-01 -2.00362265e-01 -2.52422929e-01 4.39801514e-01 -3.29899341e-01 -1.32499123e+00 2.44005322e-01 -7.81170845e-01 -3.11946869e-01 -6.12811387e-01 3.90681237e-01 -6.99511528e-01 9.49774757e-02 -5.89429438e-02 -1.21837211e+00 -1.65783018e-01 -1.30783713e+00 5.61159015e-01 3.81276645e-02 -1.02617983e-02 -8.40739489e-01 -4.59656447e-01 9.86504704e-02 1.63998082e-01 6.77486300e-01 1.10454404e+00 -9.52476501e-01 -5.04795492e-01 -9.87905860e-01 -1.06334515e-01 9.77746129e-01 -3.57772917e-01 1.74483672e-01 -1.04729915e+00 -2.45103747e-01 1.51909173e-01 -3.69878113e-01 8.58093321e-01 6.62940681e-01 1.50543737e+00 -6.93903565e-01 -4.20344353e-01 5.38200319e-01 1.21153593e+00 2.72777140e-01 5.11128247e-01 -1.32188862e-02 2.07126468e-01 5.28412819e-01 5.13020873e-01 2.72829890e-01 -3.26983184e-01 4.59583014e-01 9.22954977e-01 4.91728693e-01 6.55097306e-01 7.20407888e-02 4.98364598e-01 -2.11040512e-01 1.43591508e-01 -3.45326722e-01 -6.60734117e-01 1.54418826e-01 -1.50117588e+00 -9.12493825e-01 5.54078162e-01 2.66125727e+00 8.70503187e-01 8.50669444e-01 -6.73157871e-02 5.18075287e-01 7.23052621e-01 -6.89941347e-02 -9.56280887e-01 -5.14984846e-01 1.31759390e-01 5.99222243e-01 1.05472112e+00 6.35622323e-01 -1.17251158e+00 3.08434844e-01 5.99842453e+00 1.04162049e+00 -7.18085408e-01 -1.72119543e-01 8.72134447e-01 -3.53614479e-01 -7.04136193e-02 -3.53473097e-01 -1.09467840e+00 5.63514590e-01 1.05840147e+00 5.19693792e-02 6.01372302e-01 1.01549459e+00 -2.20145479e-01 3.42266001e-02 -1.36421895e+00 3.84372860e-01 -2.07669288e-01 -1.13719535e+00 -3.50418329e-01 1.69085432e-02 6.01800025e-01 -1.12155408e-01 6.23667359e-01 3.63272041e-01 8.89101207e-01 -1.46757817e+00 8.54347408e-01 6.05528355e-01 8.10196102e-01 -1.39293039e+00 7.68602908e-01 3.67749721e-01 -8.09068620e-01 -3.22910488e-01 -1.57692239e-01 4.70618963e-01 -1.32211626e-01 7.95793891e-01 -6.21253848e-01 4.59354132e-01 7.30793953e-01 9.95015353e-02 3.07216123e-02 6.79846764e-01 -3.19991410e-01 5.83099186e-01 -7.71744132e-01 1.78997830e-01 -5.00752963e-02 4.43373993e-02 8.11725318e-01 9.37287748e-01 1.57643974e-01 -4.58924063e-02 1.88082103e-02 1.10200191e+00 -2.67653167e-01 -6.41457915e-01 -6.60253108e-01 2.03489259e-01 6.59407973e-01 7.49030828e-01 -3.71459246e-01 1.72271535e-01 3.26485127e-01 1.78342909e-01 -3.36229764e-02 5.00336647e-01 -1.22607505e+00 -6.95308626e-01 1.03901100e+00 -2.03515917e-01 4.61634874e-01 -4.75236289e-02 -5.78420758e-01 -3.54848921e-01 1.36254951e-01 -6.97902322e-01 6.87867641e-01 -4.23847049e-01 -1.25469232e+00 4.89860982e-01 2.63842255e-01 -9.66726899e-01 -2.81529278e-01 -9.76419926e-01 -4.63393182e-01 9.61669743e-01 -9.95077491e-01 -5.21851182e-01 2.97743410e-01 7.21293688e-01 -2.04309314e-01 -3.45240474e-01 7.64408827e-01 -1.53341025e-01 -8.67340267e-01 1.12043262e+00 1.32486075e-01 3.16424042e-01 1.76738009e-01 -1.14602125e+00 1.15506575e-01 1.07751429e+00 -2.43693173e-01 4.41958368e-01 9.02767122e-01 -4.20698524e-01 -1.04272664e+00 -1.54106557e+00 1.79950505e-01 -5.11933625e-01 6.67373359e-01 -1.62110448e-01 -4.94514018e-01 6.30604625e-01 -5.52746177e-01 3.15808237e-01 3.69830698e-01 3.15701663e-02 -6.40273571e-01 -5.18237352e-01 -1.77409697e+00 7.01233625e-01 6.55128956e-01 -3.63917887e-01 -3.80093187e-01 2.33893484e-01 7.79516280e-01 -6.22495294e-01 -1.04159451e+00 9.66234624e-01 5.58856249e-01 -7.36610591e-01 1.22638309e+00 -6.50129557e-01 4.27897722e-02 -3.07806820e-01 -6.96001589e-01 -1.03050447e+00 3.84474397e-01 -8.19228649e-01 -2.57910937e-01 9.94935513e-01 6.33837163e-01 -8.18276882e-01 7.65269279e-01 9.62617934e-01 -6.50191680e-02 -7.24361897e-01 -1.68930602e+00 -1.00666714e+00 3.25673431e-01 -1.14339066e+00 5.58556139e-01 1.99680895e-01 -3.74519944e-01 -5.65269709e-01 1.17499731e-01 8.38300765e-01 9.04164374e-01 -2.36799091e-01 4.03157264e-01 -1.05568135e+00 -4.53781068e-01 -6.11800253e-01 -5.93033433e-01 -4.89474356e-01 4.74621654e-01 -6.71220720e-01 4.84679282e-01 -7.79668689e-01 -3.89367580e-01 -8.17883372e-01 -6.32014871e-01 4.96234477e-01 3.59201908e-01 1.02338366e-01 -1.92794744e-02 -4.10763204e-01 -4.35758471e-01 1.88191310e-01 7.11008966e-01 -4.36542511e-01 9.21968892e-02 7.86587238e-01 -4.67793018e-01 9.83449697e-01 6.55401647e-01 -7.27713525e-01 -2.36630335e-01 1.41017511e-01 2.39557624e-01 2.83016592e-01 6.08085930e-01 -1.26109803e+00 8.24161172e-02 -2.41556808e-01 4.56622958e-01 -4.75235671e-01 4.54457670e-01 -1.07126677e+00 3.57971787e-02 5.22075474e-01 -5.42533696e-01 -2.33758926e-01 4.56217647e-01 8.27681482e-01 2.49083504e-01 -4.34814274e-01 1.20272970e+00 2.77601093e-01 6.69258982e-02 4.25154716e-01 -2.39742115e-01 1.97992966e-01 1.08122408e+00 6.53642640e-02 -3.28535676e-01 -2.98372835e-01 -6.94587350e-01 1.96981177e-01 1.01764187e-01 -6.55552521e-02 6.34155095e-01 -1.10771871e+00 -3.58556896e-01 4.09341246e-01 -1.85110033e-01 4.69088405e-01 1.64321020e-01 4.49883938e-01 -7.09812939e-02 1.97221458e-01 1.71052471e-01 -5.09607792e-01 -8.49553585e-01 3.56753230e-01 8.15074325e-01 -2.75412977e-01 -8.31641257e-02 1.11942935e+00 -3.97789814e-02 -4.46920514e-01 9.62160468e-01 -6.84142470e-01 2.47748032e-01 -4.07407373e-01 2.87952304e-01 6.38658881e-01 1.48195416e-01 -2.34161302e-01 -3.00173968e-01 2.35878959e-01 1.10931113e-01 -4.75818574e-01 9.24322963e-01 4.34935391e-01 8.00034478e-02 1.97947681e-01 9.67761993e-01 -2.05310404e-01 -1.53197813e+00 -6.41542748e-02 -2.01145172e-01 -1.14809200e-01 -1.09370470e-01 -9.17911589e-01 -1.28957486e+00 7.72569478e-01 6.14173889e-01 1.39957830e-01 1.13351262e+00 -1.73950851e-01 4.79490638e-01 8.05203080e-01 4.39195395e-01 -1.18127835e+00 -2.77348906e-01 6.85827672e-01 8.15965772e-01 -8.04692388e-01 -7.43988380e-02 2.93379347e-03 -4.39649463e-01 9.38746929e-01 4.64707106e-01 -2.27440059e-01 1.07931745e+00 5.86203158e-01 -3.73366028e-01 2.93937922e-01 -5.11091471e-01 3.96539629e-01 3.86016965e-01 6.55124187e-01 -3.66002619e-01 4.86018844e-02 5.81556857e-01 9.61067915e-01 -3.20091486e-01 -2.68422246e-01 1.94009528e-01 7.90915132e-01 -4.24000531e-01 -6.32842302e-01 -5.10868728e-01 5.45698762e-01 -5.83239198e-01 4.67218682e-02 1.50973663e-01 7.75450528e-01 1.72120988e-01 1.02928197e+00 -2.54064593e-02 -5.16635180e-01 4.91896331e-01 1.61642075e-01 4.85661685e-01 -3.01491916e-01 -2.81141639e-01 -4.52007413e-01 -8.86852071e-02 -7.08216786e-01 1.66789398e-01 -7.02522337e-01 -1.37146473e+00 -2.80187100e-01 -3.39614123e-01 1.85071632e-01 9.44358230e-01 1.10295725e+00 -1.99505240e-01 4.92717177e-01 8.70175600e-01 -5.28211355e-01 -1.37589800e+00 -8.06846082e-01 -8.11674714e-01 -6.06575459e-02 4.53037143e-01 -5.11832595e-01 -7.81632543e-01 -1.89456642e-01]	[5.604480743408203, 7.654757976531982]
9756ced7-5ead-4d37-9a2f-b745855243fd	slue-phase-2-a-benchmark-suite-of-diverse	2212.10525	null	https://arxiv.org/abs/2212.10525v2	https://arxiv.org/pdf/2212.10525v2.pdf	SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks	Spoken language understanding (SLU) tasks have been studied for many decades in the speech research community, but have not received as much attention as lower-level tasks like speech and speaker recognition. In particular, there are not nearly as many SLU task benchmarks, and many of the existing ones use data that is not freely available to all researchers. Recent work has begun to introduce such benchmark datasets for several tasks. In this work, we introduce several new annotated SLU benchmark tasks based on freely available speech data, which complement existing benchmarks and address gaps in the SLU evaluation landscape. We contribute four tasks: question answering and summarization involve inference over longer speech sequences; named entity localization addresses the speech-specific task of locating the targeted content in the signal; dialog act classification identifies the function of a given speech utterance. We follow the blueprint of the Spoken Language Understanding Evaluation (SLUE) benchmark suite. In order to facilitate the development of SLU models that leverage the success of pre-trained speech representations, we will be publishing for each task (i) annotations for a relatively small fine-tuning set, (ii) annotated development and test sets, and (iii) baseline models for easy reproducibility and comparisons. In this work, we present the details of data collection and annotation and the performance of the baseline models. We also perform sensitivity analysis of pipeline models' performance (speech recognizer + text model) to the speech recognition accuracy, using more than 20 state-of-the-art speech recognition models.	['Shinji Watanabe', 'Karen Livescu', 'Hung-Yi Lee', 'Wei-Lun Wu', 'Roshan Sharma', 'Felix Wu', 'Ankita Pasad', 'Chyi-Jiunn Lin', 'Siddhant Arora', 'Suwon Shon']	2022-12-20	null	null	null	null	['dialog-act-classification', 'spoken-language-understanding', 'speaker-recognition', 'spoken-language-understanding']	['natural-language-processing', 'natural-language-processing', 'speech', 'speech']	[ 5.23816824e-01 3.61477047e-01 5.00952639e-03 -7.75655985e-01 -1.35108101e+00 -7.71594465e-01 6.71797752e-01 1.33369014e-01 -3.41840506e-01 5.01501977e-01 8.65776360e-01 -5.85080981e-01 3.05703878e-01 -1.46646664e-01 -4.99190897e-01 -1.90822616e-01 5.32496255e-03 5.85104108e-01 2.33760297e-01 -1.99559480e-01 -8.12805537e-03 -5.55219948e-02 -1.54376304e+00 6.19587183e-01 6.80272758e-01 9.05366480e-01 1.30655587e-01 1.03269124e+00 -3.28647554e-01 9.17161882e-01 -1.02845359e+00 -2.07039453e-02 -4.76630002e-01 -6.58902705e-01 -1.38252008e+00 -1.44639639e-02 4.70915556e-01 -3.93530309e-01 -3.34547251e-01 5.81396878e-01 8.42103958e-01 3.34420949e-01 5.06864130e-01 -9.07962203e-01 -6.25689685e-01 9.21608865e-01 1.27259806e-01 5.98921657e-01 7.12070525e-01 1.18636675e-01 1.28645718e+00 -8.01908195e-01 6.57123029e-01 1.48899817e+00 3.26635599e-01 9.53389525e-01 -1.05272615e+00 -4.63366061e-01 2.53509313e-01 1.95313618e-01 -1.04517162e+00 -1.24299634e+00 2.40421653e-01 -2.10520610e-01 1.72414994e+00 4.06999618e-01 -5.11114895e-02 1.32887053e+00 -3.90672773e-01 1.24132311e+00 6.99806511e-01 -5.01371264e-01 2.79643685e-01 -1.27789774e-03 7.61135042e-01 4.29519504e-01 -5.78440368e-01 -6.00322224e-02 -7.01433003e-01 -9.61972848e-02 8.98165628e-02 -6.52779698e-01 -7.11651623e-01 3.13456327e-01 -1.26977634e+00 7.79639006e-01 2.05700733e-02 5.31744480e-01 3.41392569e-02 -1.35793373e-01 8.27489555e-01 4.88145471e-01 7.83357918e-01 2.76592553e-01 -8.33173215e-01 -6.01305723e-01 -7.70298958e-01 -1.93735212e-02 1.33305812e+00 9.35314953e-01 5.16608357e-01 1.56056419e-01 -4.51003939e-01 1.35039735e+00 2.95773774e-01 1.67225718e-01 6.89876497e-01 -6.01885855e-01 6.60405815e-01 3.13635141e-01 -3.12107682e-01 -1.66030139e-01 -3.42406690e-01 -5.04992381e-02 -4.27594781e-01 -3.81204396e-01 3.54186445e-01 -2.73142040e-01 -8.97254646e-01 1.69241822e+00 7.04120174e-02 3.80243838e-01 5.82489192e-01 6.01048231e-01 1.57209802e+00 1.18393409e+00 1.30405098e-01 -1.45221084e-01 1.47956645e+00 -1.23598361e+00 -8.78882349e-01 -5.05139649e-01 8.54151309e-01 -8.58504176e-01 1.21401036e+00 -5.53376004e-02 -1.06307650e+00 -4.27980810e-01 -8.47275436e-01 -2.82510012e-01 -4.55178976e-01 8.46969187e-02 3.00737828e-01 8.52813601e-01 -1.27085221e+00 6.61919937e-02 -6.17769122e-01 -7.03874469e-01 1.27863526e-01 1.37929738e-01 -3.08559358e-01 1.85364977e-01 -1.38391185e+00 9.74277556e-01 2.44522601e-01 -1.20316327e-01 -1.11852753e+00 -8.18152666e-01 -1.14469838e+00 2.29698002e-01 3.84764582e-01 -2.48009577e-01 2.05370116e+00 -7.04778731e-01 -1.74660599e+00 1.02650523e+00 -4.72336471e-01 -5.95883667e-01 -2.69770008e-02 -1.04431912e-01 -5.08312762e-01 -1.62144318e-01 -6.92180917e-02 6.42488360e-01 4.67351794e-01 -7.66901672e-01 -6.65833414e-01 -2.76252598e-01 -1.30389407e-01 1.59299433e-01 -2.71017052e-04 4.74439889e-01 -3.55632484e-01 -4.88513440e-01 -2.28026599e-01 -5.78835666e-01 2.64945894e-01 -5.16182899e-01 -4.33248460e-01 -7.92116880e-01 8.21365774e-01 -9.30089056e-01 1.49905550e+00 -2.30540299e+00 1.81376971e-02 -4.17155266e-01 -2.04245672e-01 5.88087916e-01 -3.56161267e-01 7.21090019e-01 -1.34930700e-01 2.33428210e-01 -4.17056918e-01 -7.72250891e-01 1.32982716e-01 3.30112427e-01 -6.50410116e-01 7.89247453e-02 2.89981544e-01 8.33179414e-01 -8.84694874e-01 4.56148991e-03 2.59016395e-01 2.87553370e-01 -3.87794316e-01 5.42411029e-01 -2.88524747e-01 4.01041627e-01 -3.02990109e-01 6.12093747e-01 2.50395566e-01 1.35451019e-01 4.42881882e-03 -5.26639149e-02 -1.80330768e-01 1.23490274e+00 -8.85416389e-01 1.70286322e+00 -7.32460320e-01 8.67068648e-01 5.12410641e-01 -8.93397570e-01 7.88237453e-01 8.63583028e-01 -7.82879069e-02 -4.11991149e-01 1.13158803e-02 3.08751911e-01 1.49780467e-01 -4.50625002e-01 2.82067329e-01 1.16614372e-01 -2.27961782e-02 6.90577388e-01 5.88601112e-01 -3.31439197e-01 9.81645435e-02 1.72149688e-01 1.32148278e+00 -2.87990659e-01 5.81946075e-01 -1.79934949e-01 8.71768057e-01 -2.66993314e-01 1.84374243e-01 7.74491608e-01 -5.92368305e-01 5.98721266e-01 3.99650753e-01 -1.52156383e-01 -7.11245775e-01 -9.31424320e-01 -3.15562665e-01 1.77707314e+00 -4.21921730e-01 -5.62960505e-01 -1.12186718e+00 -6.37337804e-01 -1.73589885e-01 1.02176774e+00 -4.17107195e-01 8.76671895e-02 -4.97630626e-01 -5.59343457e-01 1.13399136e+00 5.71626067e-01 3.64525855e-01 -1.42160130e+00 9.00294855e-02 2.40201354e-01 -3.40131730e-01 -1.28191483e+00 -7.90387273e-01 2.55707175e-01 -4.39773172e-01 -8.97634208e-01 -4.97229517e-01 -1.00053871e+00 1.82381555e-01 1.45728961e-01 1.23604739e+00 -1.77571192e-01 -3.62839997e-02 7.84913421e-01 -5.63617408e-01 -5.52499235e-01 -1.10215974e+00 4.47336376e-01 -1.68935936e-02 -1.33678308e-02 4.76959020e-01 -1.02008946e-01 -1.22522570e-01 4.33109075e-01 -7.64046311e-01 -1.51199296e-01 2.75427550e-01 9.05827165e-01 1.82948798e-01 -7.34363616e-01 1.05874169e+00 -6.79417133e-01 9.25941169e-01 -3.60783815e-01 -3.24776381e-01 4.14296359e-01 2.27437261e-03 -8.08117539e-02 2.65818000e-01 -1.34696364e-01 -1.10331082e+00 -1.44608200e-01 -8.66714418e-01 5.14309555e-02 -5.11191368e-01 5.45261800e-01 -3.14077705e-01 3.56113017e-01 6.44453228e-01 4.68697667e-01 1.52833685e-01 -7.41155267e-01 4.65590090e-01 1.34650505e+00 3.73260647e-01 -4.79019463e-01 -1.11010913e-02 -1.23999402e-01 -9.52258527e-01 -1.57188559e+00 -9.39691246e-01 -7.90680647e-01 -4.42762017e-01 3.81518677e-02 9.42315578e-01 -8.47648025e-01 -7.02687860e-01 4.38167989e-01 -1.51675594e+00 -4.46429789e-01 -7.71436021e-02 2.76551664e-01 -4.22692657e-01 3.97012591e-01 -7.24589586e-01 -1.13163602e+00 -6.09370530e-01 -1.41673589e+00 1.33091056e+00 -2.32278742e-03 -5.85722268e-01 -9.79432762e-01 2.23167643e-01 8.19561779e-01 5.01065314e-01 -5.04513085e-01 7.88359880e-01 -1.40564537e+00 -2.88334489e-01 3.84779721e-02 -6.93314001e-02 6.76385403e-01 1.67537883e-01 -1.00457527e-01 -1.63949859e+00 -2.17099681e-01 4.18106141e-03 -7.48654127e-01 9.58821476e-01 4.19843465e-01 9.38641548e-01 -2.18404949e-01 -2.03384906e-01 2.53153831e-01 3.34015787e-01 3.26111078e-01 3.89154166e-01 -6.11023940e-02 2.73681939e-01 1.03655946e+00 1.60726532e-01 -6.00697137e-02 4.16157871e-01 6.19011521e-01 -1.38405990e-02 2.40561217e-01 -3.24820429e-01 -1.74849093e-01 6.94639802e-01 1.11349511e+00 3.90849978e-01 -5.28494120e-01 -1.05560172e+00 7.73981750e-01 -1.74642110e+00 -7.59327888e-01 1.52793646e-01 2.05586863e+00 9.31681752e-01 -1.21897951e-01 4.26634736e-02 -7.20828250e-02 5.92111230e-01 4.44253594e-01 -4.05213743e-01 -5.46535194e-01 -5.32974862e-02 2.06644848e-01 -1.54484987e-01 8.76097620e-01 -1.20446920e+00 1.24921918e+00 6.98371077e+00 7.80422032e-01 -8.60799730e-01 2.82105386e-01 7.85385489e-01 1.69835120e-01 -1.41243175e-01 -1.96613610e-01 -1.16731465e+00 1.81223005e-01 1.53054357e+00 -2.31609061e-01 3.41208726e-01 9.09058332e-01 2.52547622e-01 9.69533324e-02 -1.45893955e+00 8.85265529e-01 2.71478564e-01 -1.28957844e+00 2.31193881e-02 -3.55534941e-01 2.75014400e-01 5.78004360e-01 -4.09388363e-01 7.54775524e-01 2.24690467e-01 -1.12224126e+00 4.47409600e-01 -1.35402411e-01 6.61516607e-01 -3.35188776e-01 7.58605540e-01 3.58001173e-01 -1.05473673e+00 1.28613964e-01 -1.63877502e-01 3.03424019e-02 4.63793457e-01 6.54265285e-03 -1.31137419e+00 3.99197549e-01 6.19635403e-01 5.86995780e-01 -2.10199177e-01 5.90439022e-01 -3.49249303e-01 1.33779836e+00 -3.43497455e-01 -3.54570419e-01 4.36487168e-01 8.03374648e-02 5.88009417e-01 1.68867648e+00 -4.82911430e-03 1.31905794e-01 1.82739347e-01 6.67708695e-01 -3.22161704e-01 4.04074937e-01 -5.34476757e-01 -3.63687873e-01 5.91065705e-01 9.23786521e-01 -2.78973758e-01 -2.74109066e-01 -8.46640646e-01 8.69012535e-01 3.04095119e-01 3.49353075e-01 -2.82472432e-01 -1.20724775e-01 1.12628078e+00 -2.54007161e-01 -1.16508063e-02 -1.27075344e-01 5.92568740e-02 -1.07489169e+00 -2.28034005e-01 -1.09910059e+00 5.24729848e-01 -5.90598643e-01 -1.31151235e+00 9.31292713e-01 -1.12570167e-01 -6.07331872e-01 -7.46740639e-01 -6.17372036e-01 -8.25803638e-01 1.00358462e+00 -1.45673752e+00 -1.14915025e+00 3.55292410e-02 2.56343365e-01 1.36117554e+00 -4.35692161e-01 1.19280052e+00 1.83925003e-01 -8.48974228e-01 5.81870079e-01 5.14241643e-02 4.39750999e-01 7.89427698e-01 -1.11303389e+00 9.59996283e-01 5.46512604e-01 3.13872457e-01 6.39449596e-01 5.58845162e-01 -3.75170112e-01 -1.06809521e+00 -8.41734350e-01 1.12888765e+00 -8.12079489e-01 1.02357733e+00 -6.80061519e-01 -1.19355404e+00 1.01260996e+00 4.88078773e-01 -3.37611198e-01 9.79658902e-01 4.22517121e-01 -1.65656447e-01 5.73884919e-02 -7.28402853e-01 2.66626835e-01 8.97884309e-01 -9.25550938e-01 -8.71097147e-01 2.39681199e-01 1.05961871e+00 -4.21823472e-01 -6.35397613e-01 2.50902236e-01 3.70665878e-01 -6.79051638e-01 7.39444792e-01 -8.58223617e-01 8.82399976e-02 -7.12111965e-02 -3.19801629e-01 -1.40307593e+00 1.76538900e-01 -6.59147799e-01 5.08224033e-02 1.65251553e+00 8.03199172e-01 -6.56118512e-01 2.69574374e-01 3.86827022e-01 -7.57188201e-01 -7.20339239e-01 -1.32593834e+00 -5.32625675e-01 1.27811944e-02 -6.88999057e-01 3.70490491e-01 7.05846846e-01 1.97475493e-01 9.87538815e-01 -5.33262603e-02 8.71145129e-02 8.60168040e-02 -2.68810272e-01 7.91799903e-01 -7.87217915e-01 -2.54780293e-01 -6.08079791e-01 -3.11997950e-01 -1.40640414e+00 5.99411249e-01 -1.02035916e+00 3.31220597e-01 -1.62495875e+00 -9.24587548e-02 5.77757917e-02 2.80937199e-02 6.11876369e-01 -2.43611872e-01 -3.00880373e-01 -1.11034950e-02 7.91824311e-02 -4.72510576e-01 7.99371243e-01 6.93999767e-01 -2.88893163e-01 -2.73428589e-01 2.82420665e-01 -5.87021649e-01 4.73381966e-01 5.68703711e-01 4.27369401e-02 -5.18984914e-01 -5.73711693e-01 -4.73786801e-01 7.78030679e-02 -5.59360236e-02 -7.60312617e-01 2.12197483e-01 4.66430277e-01 -3.32076013e-01 -6.51681840e-01 3.21645975e-01 -2.16215089e-01 -6.36163592e-01 1.07860565e-01 -5.91471016e-01 -3.49871814e-01 4.60896075e-01 2.55327225e-01 -6.12861395e-01 -4.75502133e-01 7.39592910e-01 5.43933287e-02 -9.81323063e-01 -2.37112269e-02 -7.45862842e-01 3.23931932e-01 6.76127255e-01 1.01391599e-01 -5.12187719e-01 -8.91057730e-01 -7.66318500e-01 4.76139754e-01 -1.73874691e-01 9.50564623e-01 3.91730189e-01 -6.27160192e-01 -9.96603966e-01 1.33054018e-01 4.31982070e-01 -8.55228603e-02 2.98899770e-01 5.29181004e-01 -2.14182422e-01 8.80896986e-01 4.08912569e-01 -6.05947614e-01 -1.46986818e+00 8.66179839e-02 4.39359158e-01 -1.20942175e-01 -2.74454474e-01 1.08322191e+00 4.95531023e-01 -1.06371784e+00 5.79731941e-01 -6.46952331e-01 -4.12711620e-01 2.03818753e-01 1.12586951e+00 3.29578310e-01 3.63781214e-01 -7.14645684e-01 -5.74459970e-01 -4.92812023e-02 -3.56167495e-01 -1.39223799e-01 1.15168679e+00 -2.25280210e-01 -1.01094777e-02 6.55331552e-01 1.16198146e+00 -2.49975592e-01 -8.77388477e-01 -2.71395534e-01 1.73309579e-01 1.91836998e-01 9.59627181e-02 -9.43567276e-01 -5.00435472e-01 1.05718601e+00 4.30280596e-01 4.78708774e-01 7.42787957e-01 4.91921037e-01 7.50394523e-01 4.62188631e-01 5.66065870e-02 -9.20101166e-01 -9.30926427e-02 1.18257296e+00 1.15175426e+00 -1.33357608e+00 -6.10156775e-01 -6.42405152e-01 -7.80006766e-01 9.08938944e-01 5.88934541e-01 5.22152185e-01 5.63837707e-01 2.52480775e-01 3.40547919e-01 -3.66117023e-02 -9.27767217e-01 -4.53583151e-01 3.60087931e-01 5.60698390e-01 1.06299174e+00 -3.44970375e-02 -8.87064487e-02 8.55506361e-01 -2.94768572e-01 -3.03205907e-01 3.48969370e-01 7.45328486e-01 -7.21993864e-01 -1.12258065e+00 -2.29220837e-01 3.59778434e-01 -4.01553005e-01 -4.23535168e-01 -7.48326063e-01 4.81190652e-01 -4.79314774e-01 1.37816811e+00 1.53201550e-01 -9.66921300e-02 7.13094771e-01 6.28675997e-01 9.97543335e-03 -1.15559649e+00 -6.99344814e-01 4.06117141e-02 7.64590979e-01 -4.66930091e-01 -2.10210025e-01 -7.18152106e-01 -1.15699482e+00 3.53683680e-02 -2.34017938e-01 3.04503024e-01 7.11853981e-01 1.17623341e+00 4.35457259e-01 6.49581850e-01 3.33129555e-01 -8.38893175e-01 -5.52575171e-01 -1.57423902e+00 -2.86325514e-01 6.56346977e-02 3.85455847e-01 -3.79586905e-01 -5.56017280e-01 1.02840789e-01]	[14.035834312438965, 6.972362518310547]
e7075d2e-d238-492b-985c-160989b3abea	dureader-retrieval-a-large-scale-chinese	2203.10232	null	https://arxiv.org/abs/2203.10232v4	https://arxiv.org/pdf/2203.10232v4.pdf	DuReader_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine	In this paper, we present DuReader_retrieval, a large-scale Chinese dataset for passage retrieval. DuReader_retrieval contains more than 90K queries and over 8M unique passages from a commercial search engine. To alleviate the shortcomings of other datasets and ensure the quality of our benchmark, we (1) reduce the false negatives in development and test sets by manually annotating results pooled from multiple retrievers, and (2) remove the training queries that are semantically similar to the development and testing queries. Additionally, we provide two out-of-domain testing sets for cross-domain evaluation, as well as a set of human translated queries for for cross-lingual retrieval evaluation. The experiments demonstrate that DuReader_retrieval is challenging and a number of problems remain unsolved, such as the salient phrase mismatch and the syntactic mismatch between queries and paragraphs. These experiments also show that dense retrievers do not generalize well across domains, and cross-lingual retrieval is essentially challenging. DuReader_retrieval is publicly available at https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval.	['Haifeng Wang', 'Hua Wu', 'Jing Liu', 'Qiaoqiao She', 'Ying Chen', 'Yingqi Qu', 'Hongyu Li', 'Yifu Qiu']	2022-03-19	null	null	null	null	['passage-retrieval']	['natural-language-processing']	[-4.90598261e-01 -6.58552170e-01 -2.73914456e-01 -1.06821083e-01 -1.89406359e+00 -1.06874013e+00 5.69228768e-01 9.60775912e-02 -4.85326350e-01 8.49928081e-01 3.60846907e-01 -3.66461184e-03 -6.52596727e-02 -4.75629568e-01 -6.23209655e-01 -2.95314103e-01 2.73037434e-01 7.15240657e-01 5.37081122e-01 -4.94535804e-01 1.80767030e-01 9.57723893e-03 -1.15135956e+00 5.48580825e-01 1.14899850e+00 7.65948951e-01 3.11164916e-01 5.39937317e-01 -1.00278445e-02 2.40365893e-01 -9.89690542e-01 -4.66205746e-01 6.99183792e-02 -5.22267520e-01 -1.02997518e+00 -3.94294113e-01 5.46721637e-01 -2.60157764e-01 -4.00092781e-01 8.04948747e-01 8.80615890e-01 2.02097669e-01 7.45237291e-01 -8.16947222e-01 -1.32080603e+00 4.83104259e-01 -2.61328518e-01 4.02269542e-01 7.02712417e-01 -1.80204645e-01 1.18475842e+00 -1.28699350e+00 8.24175060e-01 1.02298415e+00 2.43143499e-01 4.75178152e-01 -8.11508179e-01 -8.50342274e-01 -5.89695983e-02 7.03026652e-02 -1.79808116e+00 -5.80015659e-01 3.90691191e-01 -1.89598486e-01 1.07796228e+00 4.86234009e-01 1.61284998e-01 1.39280283e+00 -9.96582657e-02 1.13596237e+00 6.75343871e-01 -4.98512626e-01 -2.93268710e-01 2.50637233e-01 2.91098922e-01 2.56623447e-01 -2.17459053e-02 -1.72748193e-01 -4.62414056e-01 -3.58466357e-01 3.83595526e-01 -2.86046028e-01 -7.38393128e-01 1.92305729e-01 -1.27946997e+00 7.49231398e-01 1.38381958e-01 3.94548118e-01 2.43228786e-02 -4.04302329e-01 5.54850817e-01 6.49265826e-01 6.74321294e-01 7.71915793e-01 -7.35513985e-01 -1.35396585e-01 -7.72662997e-01 5.06391466e-01 9.63679433e-01 1.66083992e+00 5.75036228e-01 -5.53693891e-01 -5.42993784e-01 1.42605925e+00 4.85311672e-02 1.03377676e+00 7.84811020e-01 -5.61449230e-01 9.40236807e-01 3.00031602e-01 2.12170154e-01 -8.73168826e-01 2.21680608e-02 -4.02458489e-01 -5.59481144e-01 -9.60645914e-01 1.71039671e-01 -7.46268556e-02 -6.83843315e-01 1.57569408e+00 6.77749664e-02 -4.36787546e-01 1.15685001e-01 9.97070372e-01 1.26526511e+00 9.85756874e-01 -1.54282928e-01 -2.16546208e-02 1.24078202e+00 -1.37584186e+00 -5.56922555e-01 -1.94029540e-01 9.37728047e-01 -1.46392989e+00 1.51572359e+00 -8.66592526e-02 -1.10093474e+00 -4.93289053e-01 -7.49337971e-01 -4.20052588e-01 -6.51980102e-01 4.26212192e-01 4.10750918e-02 4.93686385e-02 -1.00212848e+00 5.53691536e-02 -3.67642492e-01 -4.95263487e-01 -1.78393304e-01 -1.46529555e-01 -2.75419831e-01 -4.17663455e-01 -1.73350739e+00 8.79764974e-01 4.53641683e-01 -1.42470792e-01 -7.56429076e-01 -6.83071554e-01 -7.11503983e-01 -2.28121527e-03 1.79359332e-01 -6.00418031e-01 1.30574632e+00 -5.31229198e-01 -1.06470227e+00 1.04673862e+00 -2.02951372e-01 1.11021362e-01 3.15374970e-01 -6.07383430e-01 -8.24427605e-01 2.49346584e-01 5.69774866e-01 5.03524780e-01 3.90842855e-01 -9.12999153e-01 -4.63474810e-01 -6.28316030e-02 -1.10605724e-01 5.04516542e-01 -3.89684439e-01 2.54872382e-01 -1.45206296e+00 -9.22324359e-01 -1.78239107e-01 -9.60611403e-01 3.67355555e-01 -5.48454702e-01 -6.24395847e-01 -4.64560241e-01 5.18156528e-01 -8.53068173e-01 1.60598052e+00 -2.29679179e+00 -5.89568466e-02 -2.68270038e-02 -2.25008652e-01 3.07114840e-01 -6.14485919e-01 9.35918927e-01 3.09521496e-01 3.66914153e-01 7.44509548e-02 -2.71199375e-01 7.79405907e-02 -4.65830006e-02 -6.35272384e-01 8.85962620e-02 6.80920258e-02 1.04013526e+00 -8.96140516e-01 -7.16568351e-01 -3.26188624e-01 1.08752415e-01 -3.32276702e-01 3.71982515e-01 -2.31238902e-01 2.60515094e-01 -9.08882320e-01 8.66014779e-01 4.36261892e-01 -3.99445564e-01 -2.45500967e-01 6.36716709e-02 1.34135514e-01 8.99447083e-01 -5.99893808e-01 1.96493435e+00 -3.16580296e-01 6.26216948e-01 -2.50953615e-01 -4.05519098e-01 7.37762690e-01 4.19961512e-01 8.56189951e-02 -1.30022776e+00 -2.27188289e-01 5.22586405e-01 -6.80398643e-01 -5.64357638e-01 1.05993760e+00 4.05738741e-01 -6.18093669e-01 6.11493945e-01 1.54582225e-02 -2.03781366e-01 5.24254143e-01 4.24228430e-01 9.70523298e-01 -3.07739843e-02 -2.50420999e-02 -3.58592808e-01 4.85573798e-01 5.50799429e-01 5.15148759e-01 8.77507329e-01 6.89261481e-02 9.16979432e-01 2.09506586e-01 7.29359910e-02 -1.02728891e+00 -1.18491352e+00 -2.67511964e-01 1.24609637e+00 4.27838027e-01 -5.92358232e-01 -5.97015560e-01 -6.00085497e-01 7.59504959e-02 4.46301997e-01 -2.76203185e-01 -2.64252067e-01 -6.80288970e-01 -6.64688706e-01 1.01720750e+00 2.90841699e-01 4.02454793e-01 -9.85153556e-01 2.44271457e-01 1.33542910e-01 -7.98681200e-01 -1.11248016e+00 -1.16935718e+00 -2.93644637e-01 -5.09355485e-01 -1.05478501e+00 -1.00337660e+00 -1.33203018e+00 4.02245075e-01 6.46398187e-01 1.68208981e+00 2.57888317e-01 -2.16704346e-02 4.81690943e-01 -8.45817387e-01 -1.69430211e-01 -3.31800133e-01 6.60444260e-01 -1.50398359e-01 -8.75169873e-01 6.15460396e-01 -7.99754262e-02 -7.13291883e-01 7.18600094e-01 -8.41182709e-01 -3.11260104e-01 4.00127798e-01 1.00984597e+00 8.63201082e-01 -1.53485805e-01 8.16380799e-01 -7.85823762e-01 1.16739249e+00 -7.70310700e-01 -5.96303165e-01 8.33392262e-01 -4.19425756e-01 -1.98880643e-01 5.06378412e-01 -5.04682183e-01 -7.37659812e-01 -8.03733706e-01 -1.35869592e-01 -3.06688517e-01 1.98009640e-01 7.73782730e-01 7.07178190e-02 4.69790012e-01 6.79908633e-01 4.48167384e-01 -3.30614150e-01 -8.80696654e-01 1.84653476e-01 9.48553026e-01 2.19917431e-01 -9.45556879e-01 6.06995940e-01 -9.29490328e-02 -1.02789474e+00 -7.17615128e-01 -9.98435795e-01 -9.06391621e-01 -3.86702299e-01 8.72593150e-02 5.95898867e-01 -1.26160181e+00 -1.25446767e-01 3.61290514e-01 -1.18154812e+00 -3.43729556e-01 1.62500422e-02 4.26927805e-01 -1.50775518e-02 2.48093545e-01 -1.08772528e+00 4.98120161e-03 -7.30169952e-01 -1.08830702e+00 1.33881176e+00 1.72262907e-01 -1.98518008e-01 -9.13456798e-01 3.53181094e-01 4.99729306e-01 4.06818867e-01 -4.43966955e-01 9.02409792e-01 -9.89537895e-01 -5.01399934e-01 -3.91974390e-01 -1.07141107e-01 3.77365083e-01 1.46272883e-01 1.46033010e-02 -7.04961061e-01 -5.93944848e-01 -2.91814506e-01 -8.10664237e-01 7.19893336e-01 -1.69143677e-02 8.78531873e-01 -1.74794644e-01 -3.17957878e-01 2.31269807e-01 1.19105637e+00 2.17427373e-01 4.79177564e-01 4.39078808e-01 3.87802243e-01 4.16953772e-01 8.89653683e-01 2.34942380e-02 5.33327043e-01 7.60652602e-01 -4.11849320e-01 3.61099504e-02 -2.33556941e-01 -4.81184870e-01 4.23794299e-01 1.66855621e+00 5.43257296e-01 -6.73020542e-01 -9.01070476e-01 7.84746945e-01 -1.71223533e+00 -7.45452642e-01 1.45059362e-01 2.17329168e+00 1.20339084e+00 -1.35478616e-01 -4.37548421e-02 -6.26995981e-01 6.41930282e-01 5.20688528e-03 -3.20809573e-01 -5.29214442e-02 -4.44906622e-01 1.67949483e-01 1.56637013e-01 4.99309450e-01 -1.07880759e+00 1.23509204e+00 6.56145906e+00 1.33113134e+00 -9.49512422e-01 9.93479714e-02 3.77476543e-01 -5.67268878e-02 -4.64274555e-01 -1.34850860e-01 -1.27040195e+00 5.73241472e-01 6.96267903e-01 -5.77658772e-01 1.33686393e-01 7.41656840e-01 -1.57055855e-01 5.37168793e-02 -9.55465257e-01 6.40057564e-01 3.05840552e-01 -1.08500147e+00 2.36958459e-01 -2.90785283e-01 8.16459119e-01 5.19255638e-01 1.25491291e-01 8.18389237e-01 1.17488116e-01 -7.47100770e-01 5.88604569e-01 2.04674095e-01 8.51548076e-01 -5.55209696e-01 7.30643094e-01 3.14323366e-01 -1.09122550e+00 5.64025044e-01 -7.07491219e-01 4.65219647e-01 -3.57160456e-02 4.32067603e-01 -5.51526546e-01 7.89827049e-01 8.84215355e-01 8.59896779e-01 -8.59093070e-01 1.09222209e+00 -2.97232479e-01 3.92487049e-01 -3.84440303e-01 -2.54974872e-01 3.66686910e-01 -1.41079307e-01 5.78182399e-01 1.62363636e+00 4.02167171e-01 -5.96890114e-02 2.17969924e-01 7.73184597e-01 -3.72443885e-01 4.38298076e-01 -6.37932360e-01 -8.89565572e-02 1.00331509e+00 8.46942067e-01 -2.44303882e-01 -4.38965827e-01 -5.04816234e-01 1.06196940e+00 4.80483651e-01 8.28595579e-01 -6.91774189e-01 -6.18587375e-01 6.86654508e-01 -2.37358138e-01 2.65609771e-01 -7.30578676e-02 3.28024417e-01 -1.64491630e+00 5.27090490e-01 -1.14589667e+00 7.38758028e-01 -7.89130211e-01 -1.73676789e+00 7.50547886e-01 7.70453885e-02 -1.71257603e+00 -3.07869017e-01 -1.55704513e-01 -1.53135985e-01 1.14227748e+00 -1.71870339e+00 -8.44391108e-01 4.58873808e-02 7.54552662e-01 9.01572764e-01 -5.46575710e-02 1.01330709e+00 8.95682037e-01 -5.81537843e-01 9.65456486e-01 6.08389914e-01 5.90526104e-01 1.41423774e+00 -8.43045652e-01 3.23859602e-01 7.66583323e-01 1.23740435e-01 1.00861835e+00 2.67166317e-01 -5.16725898e-01 -1.35310984e+00 -1.01749277e+00 1.21613264e+00 -6.79220378e-01 7.55014539e-01 -3.70018303e-01 -1.18983877e+00 6.04654133e-01 4.42398995e-01 -2.78799385e-01 8.07410657e-01 2.87550688e-01 -5.16592979e-01 1.08385459e-02 -6.18028939e-01 6.55615747e-01 7.33549833e-01 -9.37014580e-01 -8.16486120e-01 6.96395755e-01 1.11340249e+00 -7.71270871e-01 -1.02351940e+00 3.90351385e-01 4.45951343e-01 -4.55256015e-01 1.01237464e+00 -5.30914843e-01 4.01880890e-01 -1.04720183e-01 -1.49121135e-01 -1.30149877e+00 -1.73751235e-01 -2.68001586e-01 1.22016236e-01 1.58040285e+00 9.42122400e-01 -6.03546679e-01 2.02891096e-01 3.69438797e-01 -3.42821389e-01 -7.21451461e-01 -7.07787514e-01 -1.02163160e+00 5.86315453e-01 -1.87266439e-01 5.65050900e-01 1.17528248e+00 7.36019239e-02 5.39696276e-01 -1.21812142e-01 4.71997373e-02 1.69378340e-01 4.94928241e-01 6.54809952e-01 -5.20100594e-01 -1.69260457e-01 -4.15306777e-01 2.40421489e-01 -1.64951539e+00 2.08891794e-01 -1.05288708e+00 1.41444042e-01 -1.34163034e+00 3.40365320e-01 -6.53209865e-01 -2.61946470e-01 3.45577210e-01 -2.64662892e-01 2.32223496e-01 -9.91060734e-02 7.26550460e-01 -9.44601834e-01 6.29080474e-01 1.55498028e+00 -2.08779961e-01 -1.04740709e-01 -2.42833897e-01 -7.46784091e-01 3.92805561e-02 6.20773375e-01 -5.64020991e-01 -4.05076087e-01 -1.14376843e+00 2.23244771e-01 1.27319887e-01 -1.36415549e-02 -4.77855414e-01 3.65094811e-01 7.14081898e-02 3.26375395e-01 -7.92660952e-01 2.47157872e-01 -3.61633182e-01 -2.17737675e-01 3.69433649e-02 -5.52057028e-01 5.39596081e-01 4.01592046e-01 2.73625284e-01 -7.58763433e-01 -1.51522622e-01 3.23207110e-01 -5.73310591e-02 -6.96805894e-01 1.91885725e-01 -1.68482006e-01 8.56049776e-01 5.10738671e-01 2.98358023e-01 -9.69309449e-01 -3.31950426e-01 -3.81792724e-01 8.05453300e-01 5.43452561e-01 9.19387460e-01 5.57084501e-01 -1.49405658e+00 -9.58341897e-01 -8.51852521e-02 6.90802515e-01 4.98016179e-03 1.98222756e-01 6.56612396e-01 -5.47723889e-01 8.73812079e-01 3.12259436e-01 -4.38174754e-01 -1.09504068e+00 3.73536706e-01 3.22681442e-02 -4.54604775e-01 -5.58769584e-01 9.81821179e-01 9.23460126e-02 -6.72015369e-01 2.07683936e-01 -3.25658545e-02 -1.21544562e-01 8.87726545e-02 6.71131849e-01 5.66573106e-02 1.87515825e-01 -5.78204393e-01 -3.89722884e-01 5.59111059e-01 -6.36566401e-01 -1.57194257e-01 9.83299136e-01 -4.65763032e-01 -3.15926939e-01 3.19138736e-01 1.67404079e+00 1.09255888e-01 -3.91957879e-01 -5.11940122e-01 1.59897819e-01 -4.36738163e-01 -2.99367934e-01 -9.10196006e-01 -8.14435542e-01 4.66816843e-01 2.34884955e-02 5.64139262e-02 1.16511571e+00 3.11449111e-01 1.17762399e+00 6.92234039e-01 3.86037290e-01 -1.31376982e+00 3.09401434e-02 8.50592732e-01 1.08365154e+00 -1.27376461e+00 -3.46170403e-02 -2.75058627e-01 -5.88793099e-01 7.75660157e-01 6.68779731e-01 4.98456284e-02 4.84121770e-01 -1.39401823e-01 3.73649985e-01 -2.50459254e-01 -9.60425258e-01 -4.03033718e-02 6.73457026e-01 7.59892389e-02 7.04268754e-01 -1.36364251e-01 -5.32655835e-01 4.62931573e-01 -3.46805066e-01 -2.75926381e-01 1.18167296e-01 1.09431279e+00 -1.77340820e-01 -1.18653274e+00 -1.10988334e-01 3.33983362e-01 -5.78759968e-01 -5.71010530e-01 -5.53895414e-01 1.01134694e+00 -6.57006860e-01 9.86528158e-01 -1.91650495e-01 -3.22622448e-01 5.52612782e-01 8.48479196e-02 1.98323771e-01 -7.56304979e-01 -5.21069467e-01 3.64719212e-01 3.47969621e-01 -4.39098001e-01 -1.59878567e-01 -3.84277821e-01 -8.04415226e-01 -2.18201086e-01 -4.91995603e-01 8.17522049e-01 2.89241850e-01 7.04688847e-01 6.34524465e-01 1.40236363e-01 6.09936714e-01 -1.25215217e-01 -5.29716849e-01 -1.16046166e+00 -4.27198678e-01 4.33238775e-01 2.30630681e-01 -3.04652780e-01 -5.30702353e-01 -9.51316357e-02]	[11.505043983459473, 7.861293315887451]
271dfa23-bb8d-4aae-aac2-60394b8e8dcb	a-light-weight-contextual-spelling-correction	2108.07493	null	https://arxiv.org/abs/2108.07493v1	https://arxiv.org/pdf/2108.07493v1.pdf	A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems	It's challenging to customize transducer-based automatic speech recognition (ASR) system with context information which is dynamic and unavailable during model training. In this work, we introduce a light-weight contextual spelling correction model to correct context-related recognition errors in transducer-based ASR systems. We incorporate the context information into the spelling correction model with a shared context encoder and use a filtering algorithm to handle large-size context lists. Experiments show that the model improves baseline ASR model performance with about 50% relative word error rate reduction, which also significantly outperforms the baseline method such as contextual LM biasing. The model also shows excellent performance for out-of-vocabulary terms not seen during training.	['Jinyu Li', 'Sheng Zhao', 'Yanqing Liu', 'Xiaoqiang Wang']	2021-08-17	null	null	null	null	['spelling-correction']	['natural-language-processing']	[ 6.37564480e-01 -1.35282815e-01 4.24939469e-02 -4.53035682e-01 -1.40978038e+00 -4.42813814e-01 2.06539750e-01 -5.38618714e-02 -6.50202453e-01 4.77190137e-01 4.47708964e-01 -1.11384082e+00 5.43863773e-01 -1.90913871e-01 -6.52679622e-01 -3.20987076e-01 4.01748031e-01 2.70378798e-01 3.58892262e-01 -5.75846553e-01 1.55474111e-01 2.08681166e-01 -1.06957352e+00 5.76594114e-01 9.75353479e-01 5.87711096e-01 8.47629905e-01 1.10660100e+00 -2.90928096e-01 7.89611578e-01 -9.95382726e-01 -1.87505230e-01 2.44572461e-02 -2.50530511e-01 -6.38331592e-01 -2.46877432e-01 5.64203143e-01 5.27582429e-02 -6.01495624e-01 7.92482257e-01 6.27579033e-01 4.18412447e-01 1.43601120e-01 -2.71721840e-01 -8.28580439e-01 8.42254877e-01 -3.51774842e-02 7.80750334e-01 5.22139728e-01 -8.60520229e-02 1.11752748e+00 -1.35320961e+00 2.33062744e-01 1.15677786e+00 5.09319663e-01 9.54169691e-01 -9.58668828e-01 -5.18341362e-01 6.72295153e-01 4.14893985e-01 -1.83165038e+00 -8.83833468e-01 5.43955147e-01 5.77183440e-02 1.98537123e+00 7.00320065e-01 1.31432280e-01 9.92293239e-01 5.04610054e-02 8.89857888e-01 6.77800000e-01 -1.02296829e+00 3.59992906e-02 -2.09822759e-01 2.54179865e-01 2.43378654e-01 -1.10252954e-01 1.18951865e-01 -7.15605855e-01 1.92890584e-01 3.70259583e-01 -3.54965359e-01 -3.11552227e-01 6.03396177e-01 -9.11815166e-01 5.70513904e-01 -2.41863489e-01 4.97190863e-01 -2.34990478e-01 2.67379194e-01 2.99823552e-01 4.53071266e-01 4.51118886e-01 3.67650896e-01 -8.23553085e-01 -3.55782300e-01 -1.01916146e+00 -2.33125448e-01 3.81797642e-01 1.40723741e+00 4.03136998e-01 7.40421057e-01 -4.55268919e-01 1.54690611e+00 3.54631126e-01 1.07068872e+00 9.41122174e-01 -3.77750099e-01 6.83698237e-01 2.09211290e-01 -2.21952379e-01 -3.15539479e-01 1.78317860e-01 -5.53092957e-01 -3.52768213e-01 -6.05573416e-01 -1.35345638e-01 -6.62069023e-02 -1.56931317e+00 1.62914979e+00 3.09356339e-02 3.24227542e-01 2.43931577e-01 6.08197033e-01 6.64499581e-01 9.80010569e-01 1.21477962e-01 -4.77477342e-01 1.15232682e+00 -1.17460907e+00 -1.34022439e+00 -7.86003530e-01 9.55572069e-01 -1.08149159e+00 1.34087741e+00 2.68239588e-01 -1.24405742e+00 -4.08277750e-01 -1.08399153e+00 -2.48056248e-01 -3.29143941e-01 2.79306114e-01 1.48745999e-01 8.97212505e-01 -1.24870002e+00 2.06545353e-01 -7.07654953e-01 -1.72111750e-01 -2.42780089e-01 2.22328186e-01 -1.02117233e-01 -3.04349989e-01 -1.47429729e+00 1.11755228e+00 1.88575327e-01 2.48995069e-02 -7.15491831e-01 -6.54746175e-01 -1.03535736e+00 -1.16617829e-01 5.03418267e-01 -1.96648747e-01 1.83641863e+00 -7.85573483e-01 -1.76885521e+00 4.97217715e-01 -1.11881053e+00 -4.94328231e-01 -3.30209494e-01 -3.96191180e-01 -1.05204618e+00 -3.84917170e-01 -5.23546338e-01 -7.36831501e-02 7.33396471e-01 -7.75340319e-01 -7.74129391e-01 -8.40291306e-02 -4.81926292e-01 3.99005055e-01 -1.27848044e-01 7.09818304e-01 -5.77530026e-01 -1.16217613e+00 2.06653342e-01 -1.01239312e+00 -2.24939376e-01 -1.08246005e+00 7.72467703e-02 -4.40240741e-01 7.33672440e-01 -1.18681848e+00 2.39772487e+00 -1.89239562e+00 -1.10869266e-01 1.52762040e-01 -7.00704455e-01 9.72511411e-01 -3.07856143e-01 5.77490926e-01 -5.52716441e-02 2.28362933e-01 -2.99284577e-01 -4.13678616e-01 -1.86390311e-01 5.76941788e-01 -5.60935497e-01 -3.07746053e-01 1.87045634e-01 9.64391410e-01 -8.08472872e-01 -1.10310100e-01 2.98968196e-01 3.36122215e-01 -3.89994055e-01 4.25488710e-01 -2.76584864e-01 1.28973663e-01 1.22880884e-01 6.60550535e-01 2.20701292e-01 3.31852317e-01 4.19253707e-01 2.77689278e-01 1.15833610e-01 1.57274973e+00 -9.74328458e-01 1.77002168e+00 -1.01432383e+00 4.93634850e-01 3.96992043e-02 -6.15244508e-01 8.43243301e-01 7.94571340e-01 -4.13382500e-01 -7.91312039e-01 -4.77731861e-02 5.01268268e-01 3.00060242e-01 -1.56138584e-01 8.63140881e-01 -2.55248249e-01 7.96734169e-02 7.04528987e-02 -1.06457779e-02 -2.63408273e-01 -1.83464885e-01 9.23446566e-02 1.36265016e+00 -3.58869791e-01 3.10524881e-01 6.03197291e-02 8.37112188e-01 -2.63435155e-01 6.35055482e-01 7.36212194e-01 -2.71084532e-03 7.44116724e-01 -5.65447032e-01 7.81990960e-02 -7.11571991e-01 -7.48947978e-01 5.03965542e-02 1.57743454e+00 -4.28323656e-01 -7.05754578e-01 -6.18722618e-01 -6.28888786e-01 -2.32295886e-01 1.36286795e+00 -1.01746418e-01 -2.72553086e-01 -1.20983016e+00 -3.22558612e-01 7.27966368e-01 7.61917114e-01 -1.87829629e-01 -9.55912650e-01 6.01160228e-01 4.82178152e-01 -2.62312531e-01 -1.16169953e+00 -1.20633376e+00 3.95596445e-01 -8.79260838e-01 -3.45742345e-01 -3.86919469e-01 -9.60141838e-01 2.86272496e-01 4.47131425e-01 9.99187946e-01 2.21837237e-01 2.80953616e-01 1.64245650e-01 -7.06622601e-01 -3.71506900e-01 -7.96481788e-01 5.22570275e-02 2.08133489e-01 -3.23449075e-01 7.94092238e-01 -3.41098249e-01 -2.14546084e-01 4.37948465e-01 -6.78004205e-01 -4.28376257e-01 5.03064513e-01 9.52187538e-01 8.96716714e-01 -5.48547924e-01 6.84939146e-01 -8.17435980e-01 5.57764888e-01 -1.00891985e-01 -2.49309018e-01 6.10695958e-01 -8.99951994e-01 4.35401388e-02 5.24345398e-01 -6.26173258e-01 -1.26450443e+00 -3.84851433e-02 -7.82014847e-01 -4.61871833e-01 5.72602078e-02 6.24747872e-01 -5.79396904e-01 1.27473757e-01 4.40127432e-01 4.90792990e-01 -4.66877937e-01 -8.20081532e-01 4.85543251e-01 1.27021146e+00 4.97565687e-01 -3.65230918e-01 4.65239167e-01 -5.07380366e-01 -6.35273874e-01 -9.26090002e-01 -6.61724448e-01 -8.39161575e-01 -1.84272945e-01 2.24527121e-01 3.67765933e-01 -1.03662586e+00 9.53047797e-02 3.18075478e-01 -1.18540239e+00 -5.44039786e-01 -1.59410536e-01 6.15552723e-01 -1.20112196e-01 4.70516264e-01 -8.84983957e-01 -1.00643921e+00 -5.73392391e-01 -9.94987369e-01 8.84066343e-01 -2.27221265e-01 -2.98594147e-01 -8.87235761e-01 9.45515558e-02 4.14790958e-01 6.62633300e-01 -1.17221785e+00 6.48963094e-01 -9.24126804e-01 -4.57462043e-01 -1.27758875e-01 2.91453063e-01 7.20092058e-01 1.55586988e-01 -2.79374212e-01 -1.11208081e+00 -2.59507954e-01 -1.22786768e-01 2.80443460e-01 8.32185388e-01 3.06143880e-01 1.22161996e+00 -4.80785728e-01 -2.34144658e-01 4.75895286e-01 9.76317108e-01 8.33345473e-01 8.62240732e-01 -1.77382097e-01 8.31863046e-01 1.21517994e-01 6.96272433e-01 -1.66952148e-01 2.41340801e-01 9.25789952e-01 -2.53409803e-01 4.84052747e-01 -7.18243778e-01 -5.32165647e-01 6.55053020e-01 2.01141644e+00 4.10714179e-01 -5.69972634e-01 -1.00952005e+00 8.86404574e-01 -1.55870104e+00 -6.33997858e-01 -2.03958571e-01 2.38817525e+00 1.31691563e+00 1.11663260e-03 -4.64844495e-01 -9.30261984e-03 8.47301662e-01 6.96617365e-02 -9.90523621e-02 -1.12230790e+00 -2.64088333e-01 6.63693607e-01 6.91754162e-01 1.19180238e+00 -6.52801752e-01 1.67940032e+00 7.20106745e+00 1.28618157e+00 -9.88658547e-01 5.34373343e-01 4.06163046e-03 -1.25814170e-01 -6.25315011e-01 1.01551749e-01 -1.12006629e+00 3.45463663e-01 1.64193368e+00 -6.67696819e-02 6.02827132e-01 8.66992950e-01 2.26568282e-01 1.95965752e-01 -1.03687692e+00 1.08442390e+00 3.17934304e-01 -9.40632463e-01 1.29279718e-01 -3.27885151e-01 5.12965798e-01 2.87160933e-01 -8.49959403e-02 6.07368946e-01 4.42688197e-01 -1.02020311e+00 5.46158075e-01 4.14533056e-02 1.15066695e+00 -6.81290805e-01 5.58472514e-01 1.91664815e-01 -1.11417568e+00 5.63076623e-02 -3.02515626e-01 -1.55914813e-01 3.56310904e-01 4.45688218e-01 -1.09413373e+00 2.25772828e-01 9.46470499e-02 2.86399961e-01 -3.68245751e-01 8.07409286e-01 -5.57212412e-01 1.58231926e+00 -3.43050569e-01 -1.87096685e-01 -1.17639594e-01 2.05674931e-01 8.31369281e-01 1.87768197e+00 4.62543011e-01 4.36793774e-01 -1.48271188e-01 -6.04822263e-02 -1.22638896e-01 3.76761854e-01 -3.65717053e-01 -1.45664383e-02 1.08889329e+00 5.84757090e-01 4.05965298e-02 -4.83558118e-01 -3.90759468e-01 1.13739514e+00 3.05217028e-01 3.95369798e-01 -3.72717500e-01 -4.28978622e-01 9.58915949e-01 -9.43289474e-02 5.82352817e-01 -5.76922596e-01 -4.10571277e-01 -1.15705788e+00 7.85490498e-02 -1.06765246e+00 1.85376853e-01 -8.03283691e-01 -9.88153100e-01 7.29952276e-01 -3.96556884e-01 -8.32948148e-01 -3.07503492e-01 -6.48492396e-01 -5.52500606e-01 1.21913254e+00 -1.74805903e+00 -9.96793032e-01 5.89791000e-01 2.74290919e-01 1.11967421e+00 -2.79093534e-01 9.56354976e-01 5.57125449e-01 -6.49257421e-01 1.27483070e+00 3.28570381e-02 6.68842793e-02 8.16334903e-01 -1.28254485e+00 9.30438399e-01 1.45712328e+00 3.51167500e-01 1.18267453e+00 5.59629142e-01 -1.00399685e+00 -1.45922577e+00 -1.26587474e+00 1.66333342e+00 -7.41590977e-01 6.48013711e-01 -5.44776201e-01 -1.37192726e+00 9.51240242e-01 2.21751571e-01 -1.46367535e-01 9.12496388e-01 5.08479953e-01 -4.97574896e-01 -2.12738305e-01 -6.26221418e-01 6.95273340e-01 1.38783109e+00 -1.08742571e+00 -1.22391272e+00 8.41518268e-02 1.41717803e+00 -6.30746305e-01 -4.99297261e-01 4.16904777e-01 3.42618853e-01 1.13363981e-01 6.31452799e-01 -5.55196047e-01 -2.81454712e-01 -4.16939408e-01 -7.14551449e-01 -1.67618608e+00 -3.81884158e-01 -9.47545528e-01 -4.70933795e-01 1.28321624e+00 9.11346018e-01 -4.96757179e-01 2.30323851e-01 6.13489151e-01 -8.68456185e-01 -3.87997031e-01 -1.24975157e+00 -1.07071817e+00 1.28997982e-01 -1.03287208e+00 6.96130514e-01 5.46902597e-01 2.32628599e-01 5.69246054e-01 -2.02861115e-01 3.98419678e-01 -1.33651525e-01 -4.74102587e-01 1.72406346e-01 -3.39103281e-01 -2.91377276e-01 -1.24337263e-01 -8.13014954e-02 -1.55854535e+00 6.50484711e-02 -9.52319860e-01 5.74539661e-01 -1.22259152e+00 -3.71445179e-01 -6.50828421e-01 -7.10151255e-01 5.20889103e-01 -6.03231490e-01 -3.15750800e-02 1.38250828e-01 -1.37248397e-01 -5.41541219e-01 5.52554905e-01 5.95889151e-01 6.96801767e-02 -2.78425545e-01 -2.51214169e-02 -4.92480397e-01 3.44080716e-01 7.36041367e-01 -5.12132466e-01 -3.40712041e-01 -9.72177684e-01 -1.33411866e-02 5.84551729e-02 -3.99320960e-01 -8.29258204e-01 3.24174285e-01 -2.92315274e-01 -1.52549893e-01 -6.96140707e-01 2.42030993e-01 -7.12572932e-01 -1.33351967e-01 -6.09210283e-02 -5.54576695e-01 3.08373898e-01 4.28181738e-01 3.98267627e-01 -2.09412381e-01 -3.41523260e-01 4.78476793e-01 1.01041876e-01 -7.74811447e-01 -6.75339103e-02 -9.30437267e-01 2.36776948e-01 3.06121081e-01 -8.13206062e-02 -7.87504017e-02 -3.58453929e-01 -6.32430732e-01 4.06123139e-02 1.24176130e-01 8.50982428e-01 7.10269809e-01 -1.19463742e+00 -6.87105119e-01 4.18957353e-01 3.82565737e-01 -2.08416224e-01 1.73355594e-01 4.19959486e-01 3.68923694e-03 7.90758133e-01 8.85820866e-01 -2.91055590e-01 -1.66580629e+00 5.81640720e-01 3.99222493e-01 -1.06941931e-01 -2.58696467e-01 1.35040593e+00 -1.56542823e-01 -4.85801637e-01 4.80747342e-01 -6.90199614e-01 7.42821395e-02 -5.02951026e-01 1.00861657e+00 1.39896274e-01 8.90542209e-01 -8.08587551e-01 -6.05890572e-01 2.08680421e-01 -5.12738645e-01 -3.83192599e-01 7.75862694e-01 -7.13666856e-01 3.11779976e-01 5.81895411e-01 9.09469604e-01 5.06437659e-01 -6.29181147e-01 -6.46985590e-01 2.61719882e-01 -4.01985794e-01 4.16660756e-01 -1.36896718e+00 -4.82741356e-01 1.01899087e+00 4.27513450e-01 -2.85830975e-01 1.00329792e+00 -2.20964298e-01 1.31988049e+00 5.69817126e-01 3.43859047e-01 -1.61496699e+00 -3.63162726e-01 1.34292912e+00 9.66867447e-01 -1.04031050e+00 -5.25986433e-01 -4.05547500e-01 -7.08323777e-01 5.97973049e-01 5.08272350e-01 1.80393398e-01 6.00871682e-01 4.56239879e-01 4.55690056e-01 4.91608441e-01 -1.22846091e+00 -4.69390184e-01 5.79475403e-01 6.22093797e-01 7.90220082e-01 4.08468813e-01 -6.72318816e-01 7.49865294e-01 -2.30185211e-01 -3.10066462e-01 3.17193389e-01 9.45758164e-01 -6.92554057e-01 -1.60715926e+00 -3.02095324e-01 2.14511976e-01 -7.91956484e-01 -9.06237483e-01 -3.38853091e-01 2.69558299e-02 -3.41036439e-01 1.40525842e+00 -1.03227578e-01 -5.69581747e-01 5.02781034e-01 8.18495572e-01 2.78788537e-01 -1.19542432e+00 -6.98442459e-01 3.24289083e-01 5.40890098e-01 -5.21023989e-01 2.63189018e-01 -6.15623891e-01 -1.26782691e+00 1.69772819e-01 -8.41875494e-01 9.28942934e-02 9.36030149e-01 9.92177904e-01 4.99290884e-01 6.48810267e-01 5.59153855e-01 -1.16371103e-01 -5.13832331e-01 -1.37044346e+00 -2.35486358e-01 2.54943036e-02 4.12941843e-01 -2.11330235e-01 -3.45953584e-01 -1.33448467e-02]	[14.333955764770508, 6.8020920753479]
a6c98700-83b3-4b3f-ac74-35d71f6484bd	road-network-representation-learning-a-dual	2304.07298	null	https://arxiv.org/abs/2304.07298v1	https://arxiv.org/pdf/2304.07298v1.pdf	Road Network Representation Learning: A Dual Graph based Approach	Road network is a critical infrastructure powering many applications including transportation, mobility and logistics in real life. To leverage the input of a road network across these different applications, it is necessary to learn the representations of the roads in the form of vectors, which is named \emph{road network representation learning} (RNRL). While several models have been proposed for RNRL, they capture the pairwise relationships/connections among roads only (i.e., as a simple graph), and fail to capture among roads the high-order relationships (e.g., those roads that jointly form a local region usually have similar features such as speed limit) and long-range relationships (e.g., some roads that are far apart may have similar semantics such as being roads in residential areas). Motivated by this, we propose to construct a \emph{hypergraph}, where each hyperedge corresponds to a set of multiple roads forming a region. The constructed hypergraph would naturally capture the high-order relationships among roads with hyperedges. We then allow information propagation via both the edges in the simple graph and the hyperedges in the hypergraph in a graph neural network context. The graph reconstruction and hypergraph reconstruction tasks are conventional ones and can capture structural information. The hyperedge classification task can capture long-range relationships between pairs of roads that belong to hyperedges with the same label. We call the resulting model \emph{HyperRoad}. We further extend HyperRoad to problem settings when additional inputs of road attributes and/or trajectories that are generated on the roads are available.	['Cheng Long', 'Liang Zhang']	2023-04-13	null	null	null	null	['hyperedge-classification', 'graph-reconstruction']	['graphs', 'graphs']	[ 1.30024493e-01 5.29627740e-01 -5.31199455e-01 -5.04708111e-01 1.75916702e-01 -5.82813501e-01 7.06187308e-01 1.59935132e-01 1.00577883e-01 6.51141644e-01 4.43571627e-01 -6.85120106e-01 -6.70652270e-01 -1.71589112e+00 -8.82324576e-01 -4.93881047e-01 -3.12491655e-01 4.29680377e-01 1.79402992e-01 -3.66112947e-01 -2.10801020e-01 7.66557038e-01 -1.31582832e+00 -2.14038044e-01 7.24022031e-01 5.78682601e-01 1.86404541e-01 3.81641835e-01 -2.78156042e-01 4.78027344e-01 -1.09201431e-01 -3.55187595e-01 1.93129092e-01 -3.57152261e-02 -6.59949124e-01 2.54712850e-01 1.54330537e-01 -1.78488433e-01 -1.20870924e+00 7.38273144e-01 -6.81021512e-02 2.71741301e-01 9.35214639e-01 -1.81861103e+00 -7.77988374e-01 8.66033673e-01 -6.51190698e-01 -2.63608508e-02 1.64145336e-01 -5.17998971e-02 1.34444451e+00 -4.87206489e-01 4.97386783e-01 1.25803626e+00 3.88551533e-01 9.48966369e-02 -1.11049604e+00 -6.09805346e-01 6.77288830e-01 5.62201254e-02 -1.40832448e+00 -5.04177287e-02 8.36054385e-01 -3.78373861e-01 5.72880864e-01 3.31442446e-01 6.41162515e-01 9.88384485e-01 -2.14107074e-02 5.77778935e-01 7.30124891e-01 1.04754932e-01 -1.36135399e-01 5.26578575e-02 5.89480340e-01 6.88284874e-01 5.31747222e-01 7.99277797e-02 -1.82563458e-02 1.81962371e-01 8.26044738e-01 5.26395977e-01 -2.38762185e-01 -3.16754669e-01 -8.54220152e-01 9.73203123e-01 1.15500593e+00 -8.62380303e-03 -3.84514689e-01 2.81242043e-01 3.88484076e-02 1.07092552e-01 1.87849291e-02 -2.01683138e-02 -2.81308860e-01 4.85125214e-01 -3.41451377e-01 -4.18471210e-02 7.86549628e-01 1.29707873e+00 1.35565567e+00 -5.03349900e-02 2.83553433e-02 7.43038714e-01 4.05136496e-01 4.76278692e-01 -2.40828812e-01 -6.48417413e-01 9.25448775e-01 9.90762115e-01 -2.54477143e-01 -1.37583041e+00 -7.59577572e-01 -2.78636128e-01 -1.25113225e+00 -2.34572187e-01 2.32041299e-01 -1.91470459e-01 -1.09802139e+00 1.91483021e+00 2.83675492e-01 6.25433743e-01 2.14928705e-02 5.80536067e-01 1.07408333e+00 7.85597146e-01 -2.16771420e-02 1.29765525e-01 1.14332771e+00 -8.25354874e-01 -4.17931795e-01 -2.95576930e-01 5.46021819e-01 -4.35786247e-02 8.97281110e-01 -2.55503923e-01 -7.75352597e-01 -3.48738909e-01 -7.31413484e-01 1.78264871e-01 -8.88240576e-01 -3.44393611e-01 7.38374233e-01 2.16337845e-01 -9.64905739e-01 4.33722824e-01 -3.63241851e-01 -4.59049702e-01 3.65599871e-01 3.42408836e-01 -5.70863187e-01 -4.36784059e-01 -1.53292286e+00 6.62579119e-01 2.60740846e-01 2.66372830e-01 -5.20571411e-01 -4.44657326e-01 -1.24499941e+00 1.81439787e-01 6.55999541e-01 -5.26671112e-01 5.08188009e-01 -4.60352957e-01 -6.94974601e-01 5.10721684e-01 -1.58293843e-01 -1.34761035e-01 1.52887478e-01 2.45676771e-01 -8.74445498e-01 -1.70901924e-01 1.22538812e-01 5.30165255e-01 4.96191055e-01 -1.60554373e+00 -6.94629908e-01 -2.37057149e-01 5.00001788e-01 1.65949732e-01 -3.89853477e-01 -5.22099733e-01 -8.10078859e-01 -4.07272607e-01 1.71863452e-01 -1.19331849e+00 -3.24934602e-01 -2.53506124e-01 -1.16532063e+00 -2.48163819e-01 1.00860560e+00 -3.93984854e-01 1.61059761e+00 -1.74168038e+00 6.89053088e-02 1.00913846e+00 5.26882768e-01 9.60767642e-02 -3.76808494e-01 6.28611088e-01 -1.94101021e-01 4.73983586e-01 -3.93016875e-01 2.37115502e-01 -4.02849764e-02 8.04826617e-01 -1.21660210e-01 4.22637701e-01 1.78108305e-01 1.10890579e+00 -1.13607383e+00 -1.80153504e-01 2.67746925e-01 5.43404043e-01 -1.71681046e-01 5.55051751e-02 7.44595332e-03 2.53248721e-01 -9.03350055e-01 2.23613411e-01 7.11433947e-01 -4.01728034e-01 2.61931062e-01 -1.80857226e-01 8.98838490e-02 2.70396233e-01 -1.28618169e+00 1.07295024e+00 -6.09430075e-01 6.58316135e-01 -1.58459052e-01 -1.03544593e+00 1.02205229e+00 -8.54447708e-02 5.37409902e-01 -5.98741710e-01 -2.39654616e-01 -3.55226457e-01 3.47659513e-02 -4.27159071e-01 4.50656831e-01 3.18329215e-01 -2.34516010e-01 5.06216228e-01 -3.81219566e-01 2.11233988e-01 1.84607401e-01 5.17836094e-01 1.24425244e+00 -1.58948496e-01 2.61403531e-01 1.41732723e-01 3.74304384e-01 -3.73224556e-01 5.64271033e-01 7.09457934e-01 2.20862538e-01 5.41322649e-01 7.78911054e-01 -3.01201612e-01 -8.99323642e-01 -1.30212200e+00 -4.18498069e-02 7.48732507e-01 2.46188924e-01 -5.29187143e-01 -1.60846621e-01 -8.65855634e-01 3.96935791e-01 5.25469482e-01 -6.43439353e-01 -3.12614858e-01 -6.39436901e-01 -5.73560476e-01 3.57331038e-01 6.31430626e-01 3.26088578e-01 -7.80042827e-01 1.18827112e-01 1.98706359e-01 -4.31868248e-02 -1.21861959e+00 -4.10003841e-01 1.33384271e-02 -5.71227491e-01 -1.29274368e+00 -2.33963996e-01 -6.61298394e-01 9.76091087e-01 6.05930448e-01 1.04419327e+00 3.08398068e-01 8.28668848e-02 2.55510956e-01 -2.53469616e-01 -2.18518041e-02 7.29786754e-02 2.05821395e-01 -6.93002418e-02 3.72840613e-01 1.53626010e-01 -7.97425985e-01 -5.47491312e-01 6.99893415e-01 -7.94294298e-01 1.18721835e-01 5.76746643e-01 5.28994203e-01 6.93970621e-01 5.71277499e-01 7.37266183e-01 -1.37936234e+00 4.76398319e-01 -1.28768766e+00 -4.35764641e-01 2.31715709e-01 -5.78300118e-01 5.91973960e-02 5.90937555e-01 -2.65725374e-01 -6.14100099e-01 -9.53759328e-02 -2.78938618e-02 -3.35474163e-01 -2.00933859e-01 8.77428770e-01 -6.53422713e-01 2.07091764e-01 7.23166540e-02 -7.64509812e-02 -3.33374888e-01 -3.09210390e-01 7.38905549e-01 4.89549190e-01 2.77902335e-01 -3.97816420e-01 1.13396978e+00 3.99621338e-01 5.69572747e-01 -1.00720322e+00 -6.62964046e-01 -5.22915125e-01 -6.36660576e-01 -4.08748299e-01 7.33034790e-01 -7.19502628e-01 -7.48964846e-01 1.26899064e-01 -8.46667230e-01 -3.49047720e-01 -8.87997150e-02 3.75356913e-01 -2.55607545e-01 1.27388313e-01 -2.85960764e-01 -6.58477664e-01 2.41157666e-01 -9.34030712e-01 8.13438714e-01 2.87015051e-01 -2.99984007e-03 -1.43180299e+00 -2.36866817e-01 -2.40755137e-02 1.35530293e-01 4.83710021e-01 1.32710338e+00 -4.85672563e-01 -7.74695337e-01 -1.62215814e-01 -5.94972134e-01 8.11813679e-03 3.77441198e-01 1.35035723e-01 -5.65630853e-01 -5.61001673e-02 -9.68604743e-01 2.04456657e-01 9.42859888e-01 4.57004219e-01 1.25926137e+00 -5.88840902e-01 -8.09552610e-01 6.90427542e-01 1.21500373e+00 -4.36871909e-02 8.05993140e-01 -1.66527070e-02 1.35217237e+00 1.19342196e+00 2.12945819e-01 4.51165251e-02 1.02586520e+00 6.63388729e-01 6.96005762e-01 -3.62123996e-01 -1.45303607e-01 -8.50376070e-01 1.90166920e-01 6.74379408e-01 -3.94606255e-02 -7.11934328e-01 -1.02035749e+00 4.72994536e-01 -2.08482671e+00 -8.55346501e-01 -6.94223583e-01 2.23490047e+00 4.38735969e-02 2.01798126e-01 1.81914076e-01 -5.23801446e-02 1.02195632e+00 3.86616170e-01 -8.61590743e-01 -2.71061748e-01 -1.78017721e-01 -1.64116770e-01 8.01832974e-01 5.83828390e-01 -8.11582983e-01 9.28437233e-01 5.43458462e+00 4.15896654e-01 -5.38161635e-01 -3.29919636e-01 5.42278349e-01 3.29499215e-01 -8.57870996e-01 2.33769059e-01 -8.90330017e-01 4.30413902e-01 8.61382186e-01 1.64277665e-02 5.91951132e-01 4.60462391e-01 3.34923387e-01 1.87209100e-01 -9.51640368e-01 5.63310564e-01 -1.87930346e-01 -1.19945276e+00 3.75339597e-01 4.76705372e-01 7.13405550e-01 1.66232750e-01 1.09927617e-02 3.07786405e-01 8.96889210e-01 -1.32050443e+00 1.90477490e-01 6.66152298e-01 8.95318687e-01 -7.14189231e-01 3.04303169e-01 3.05450380e-01 -1.90359235e+00 -1.84081718e-01 -2.07519054e-01 1.79534927e-01 4.60480392e-01 4.86798525e-01 -6.65807962e-01 9.97991323e-01 4.05759037e-01 1.24821579e+00 -3.63321364e-01 9.02348340e-01 -5.74195683e-01 6.62383676e-01 -2.92451918e-01 1.61224902e-01 4.87935573e-01 -8.50483656e-01 5.38106322e-01 8.92279327e-01 2.85675287e-01 1.03341043e-01 3.14197719e-01 8.31055164e-01 -4.09094453e-01 -2.52725780e-01 -1.31247175e+00 1.63891822e-01 7.46202111e-01 1.32013142e+00 -5.30097008e-01 -9.10856668e-03 -8.91602099e-01 4.26347345e-01 5.16058445e-01 9.73263860e-01 -7.85979450e-01 -4.57479507e-01 1.19144750e+00 5.48641920e-01 8.04890543e-02 -2.40875646e-01 -2.55860053e-02 -7.07124829e-01 -1.08127184e-01 -1.54263049e-01 4.26760823e-01 -8.89746010e-01 -1.44527507e+00 5.10522902e-01 2.11359277e-01 -1.12147903e+00 4.20039371e-02 -4.41434234e-01 -1.07269990e+00 8.63026857e-01 -1.99181342e+00 -1.39283526e+00 -4.67694402e-01 9.75979209e-01 9.39119458e-02 5.43634035e-02 3.09266537e-01 2.25178331e-01 -7.90275216e-01 3.72698098e-01 -1.39530271e-01 3.82394880e-01 1.98723748e-02 -1.12674832e+00 5.71034312e-01 7.09176779e-01 1.43116474e-01 6.32433772e-01 1.42586201e-01 -8.77611518e-01 -1.32183766e+00 -1.82414961e+00 9.46405292e-01 -2.57725477e-01 9.01436687e-01 -4.00554508e-01 -1.00857258e+00 1.10921681e+00 -2.45419160e-01 1.41476318e-01 4.03532535e-01 3.00027221e-01 -4.28695440e-01 -1.78678095e-01 -8.04972172e-01 7.96100676e-01 1.64586210e+00 -5.88802695e-01 -3.12030226e-01 4.13350523e-01 8.83335829e-01 1.87841743e-01 -7.59200275e-01 3.15191150e-01 2.94707239e-01 -4.25208569e-01 1.23597288e+00 -9.45174038e-01 3.59835505e-01 -3.21261883e-01 -8.09651464e-02 -1.59665203e+00 -5.42537332e-01 -4.81758118e-01 -2.17342138e-01 1.45601726e+00 6.60839438e-01 -8.49084556e-01 7.89722264e-01 6.23935699e-01 -2.03672484e-01 -7.89884627e-01 -7.12611079e-01 -6.64883494e-01 4.36816551e-02 -5.09370565e-01 1.19729745e+00 9.54315722e-01 -1.51286945e-01 7.26661205e-01 -4.67091024e-01 4.53069627e-01 5.21422684e-01 8.81376714e-02 7.37314343e-01 -1.62787354e+00 1.13973126e-01 -5.78699708e-01 -5.13705969e-01 -1.25243199e+00 6.56994820e-01 -1.37977338e+00 -2.66649425e-01 -2.07193327e+00 1.20288059e-01 -1.13641489e+00 -1.86963961e-01 5.74777365e-01 -4.90048230e-02 -2.23461181e-01 -7.62750208e-02 2.27286853e-02 -1.61668241e-01 4.68561620e-01 1.42398632e+00 -2.72256374e-01 -3.36940378e-01 4.67489928e-01 -8.81014347e-01 7.25180268e-01 7.39458561e-01 -3.48268747e-01 -7.98896492e-01 -4.77617532e-01 5.56802392e-01 2.48703569e-01 3.78600359e-01 -4.71868128e-01 3.44763994e-01 -3.57152790e-01 -2.98255924e-02 -5.64113736e-01 3.20367992e-01 -1.13466120e+00 4.79461193e-01 -1.00291498e-01 -3.64225477e-01 2.62309194e-01 -3.34681660e-01 1.11170709e+00 -1.01266228e-01 2.24711284e-01 2.74434686e-01 4.54201587e-02 -7.36984909e-01 9.79839206e-01 -2.70043910e-01 2.27664113e-02 1.12179232e+00 -4.09429252e-01 -5.78767896e-01 -7.11391330e-01 -6.67771935e-01 9.02707160e-01 2.50902116e-01 7.55245447e-01 7.84464240e-01 -1.48101938e+00 -5.91417313e-01 2.51006573e-01 4.35312331e-01 2.29054675e-01 -4.33805063e-02 5.35172760e-01 1.34389594e-01 2.71849394e-01 -1.28474742e-01 -3.09062481e-01 -1.06217301e+00 5.40102899e-01 1.44103691e-01 -3.52780759e-01 -9.57087576e-01 5.09509265e-01 5.69377482e-01 -7.60536551e-01 1.14476271e-01 -2.42631152e-01 -7.56772339e-01 1.24665789e-01 4.26268056e-02 5.01997411e-01 -3.35005254e-01 -1.22633922e+00 -2.22632766e-01 7.83845007e-01 1.27772018e-01 1.85873300e-01 1.32355165e+00 -3.45420986e-01 -3.34168412e-02 4.28996712e-01 1.38846612e+00 -2.00657293e-01 -1.21667027e+00 -5.15031397e-01 -7.74508491e-02 -4.43499327e-01 9.22114402e-02 -4.15631801e-01 -1.68765461e+00 7.56913126e-01 -7.90830106e-02 2.95802027e-01 8.06354642e-01 2.88403779e-01 8.71614635e-01 2.85909146e-01 3.50497812e-01 -8.36966455e-01 -2.42673308e-01 5.94893932e-01 6.27035558e-01 -9.65488970e-01 -1.48666918e-01 -8.45936835e-01 -6.69402778e-01 1.00370169e+00 5.92613101e-01 1.02786310e-01 1.06474459e+00 2.34137513e-02 -5.29125988e-01 -4.76889014e-01 -4.46937174e-01 -7.48751223e-01 3.90391529e-01 8.19236934e-01 -1.20298624e-01 6.65045381e-01 1.02803349e-01 4.18153465e-01 -8.77751261e-02 -4.84626949e-01 5.56642652e-01 5.67889333e-01 -2.91249901e-01 -1.05056071e+00 1.33024141e-01 1.04401219e+00 4.03351545e-01 4.78243344e-02 -3.20872515e-01 9.00765002e-01 8.67833570e-02 1.20780969e+00 4.06665564e-01 -8.48874688e-01 6.62577868e-01 -4.17432904e-01 -7.52682835e-02 -5.87367892e-01 -2.61310995e-01 -5.50699532e-01 3.33544403e-01 -5.78702271e-01 -1.33688122e-01 -6.39422596e-01 -1.43289340e+00 -6.82722330e-01 -2.32485175e-01 2.97200438e-02 3.68359506e-01 8.28002155e-01 2.56295979e-01 6.58229291e-01 1.00289357e+00 -4.77552712e-01 2.73163795e-01 -5.54077744e-01 -9.56524253e-01 6.21479392e-01 4.02138799e-01 -8.88006985e-01 -2.92756706e-01 -3.35948706e-01]	[6.481655120849609, 2.1111128330230713]
14170a00-0302-4e0a-ba51-2dacec153ee0	zero-shot-transfer-for-implicit-discourse-1	null	null	https://aclanthology.org/W19-5927	https://aclanthology.org/W19-5927.pdf	Zero-shot transfer for implicit discourse relation classification	Automatically classifying the relation between sentences in a discourse is a challenging task, in particular when there is no overt expression of the relation. It becomes even more challenging by the fact that annotated training data exists only for a small number of languages, such as English and Chinese. We present a new system using zero-shot transfer learning for implicit discourse relation classification, where the only resource used for the target language is unannotated parallel text. This system is evaluated on the discourse-annotated TED-MDB parallel corpus, where it obtains good results for all seven languages using only English training data.	['Robert {\\"O}stling', 'Murathan Kurfal{\\i}']	2019-09-01	null	null	null	ws-2019-9	['implicit-discourse-relation-classification']	['natural-language-processing']	[ 3.55700813e-02 6.81402504e-01 -5.43074965e-01 -2.44222328e-01 -8.39799643e-01 -4.73185152e-01 9.48163211e-01 3.21123183e-01 -5.13021231e-01 1.24072862e+00 5.35913646e-01 -5.03379941e-01 3.07458609e-01 -7.83625424e-01 -3.61864567e-01 -2.98781127e-01 -6.10588454e-02 8.07726085e-01 5.18191040e-01 -7.95052826e-01 -1.09414998e-02 -2.31259912e-01 -1.11089242e+00 8.46945226e-01 7.52207935e-01 8.16022038e-01 2.63689369e-01 5.24914145e-01 -4.55223411e-01 1.81778955e+00 -8.93585324e-01 -4.33807105e-01 -3.93602192e-01 -6.53149605e-01 -1.73502803e+00 -7.02989288e-03 2.41313260e-02 -2.11536512e-01 -2.75242925e-01 7.73840725e-01 3.40938091e-01 2.43168786e-01 6.95076644e-01 -7.29893506e-01 -6.31977141e-01 7.74449646e-01 -7.19587132e-02 5.34555733e-01 5.35251975e-01 -3.55563045e-01 1.24065220e+00 -6.10625207e-01 1.09851146e+00 1.31904829e+00 3.52248669e-01 4.82173979e-01 -9.35887694e-01 -2.28654012e-01 -7.01768920e-02 8.33098531e-01 -1.06848633e+00 -4.52094555e-01 6.86379015e-01 -6.96526706e-01 1.59118211e+00 2.71467477e-01 1.86975494e-01 1.21574378e+00 -1.22490890e-01 8.22607815e-01 8.05588126e-01 -9.29735839e-01 1.47420987e-01 1.20283797e-01 5.44626176e-01 2.78085083e-01 -4.54192549e-01 -4.00781274e-01 -4.24175322e-01 1.15922898e-01 1.53843954e-01 -7.13209450e-01 -3.18051398e-01 1.25757605e-01 -1.00924897e+00 1.03358829e+00 2.30563074e-01 7.79517591e-01 4.85567078e-02 -6.10097110e-01 1.05443132e+00 6.76720738e-01 1.01331890e+00 5.92415452e-01 -4.56469238e-01 -4.99604732e-01 -3.43366563e-01 2.43670031e-01 1.12241828e+00 1.02246654e+00 4.73869503e-01 -3.15295637e-01 -1.64659813e-01 1.11199677e+00 -2.87619382e-01 3.73598561e-02 5.71617007e-01 -7.56393194e-01 1.00003004e+00 8.75068128e-01 1.46989390e-01 -8.04270089e-01 -3.16015542e-01 2.66725928e-01 -6.29988134e-01 -1.24183975e-01 5.98695993e-01 -4.07954395e-01 -9.37180370e-02 1.61963499e+00 3.81441236e-01 -2.76920140e-01 6.99494302e-01 7.92558670e-01 1.39045548e+00 9.27729905e-01 8.71822834e-02 -5.83334863e-01 1.46738446e+00 -1.17851341e+00 -1.38843083e+00 -1.90702483e-01 1.09532487e+00 -6.67786002e-01 9.82911289e-01 -6.53427616e-02 -8.07901680e-01 -3.55522364e-01 -1.10051811e+00 -5.24467409e-01 -4.38381225e-01 1.29499221e-02 4.54769492e-01 1.83043569e-01 -4.60992813e-01 3.08606774e-01 -5.66227138e-01 -4.21594650e-01 2.85760313e-01 -1.37887588e-02 -3.82419288e-01 1.13311581e-01 -1.68502784e+00 1.50275290e+00 7.68482089e-01 -1.57390878e-01 -3.57470006e-01 -2.79444098e-01 -1.18666911e+00 -7.69157708e-02 5.98231137e-01 2.50524282e-02 1.41300654e+00 -1.15752149e+00 -1.63303339e+00 1.22545791e+00 -6.12331107e-02 -6.85274899e-01 4.13870305e-01 -2.98079610e-01 -4.40712959e-01 -3.62543911e-02 6.62543848e-02 -1.32527379e-02 3.90737981e-01 -7.87367046e-01 -5.15042067e-01 -1.32263720e-01 4.78640616e-01 4.32671338e-01 -4.75730360e-01 4.88874614e-01 1.56450123e-02 -3.15068185e-01 -4.78409201e-01 -6.52760863e-01 1.41487256e-01 -5.22442520e-01 -4.06959444e-01 -1.09134698e+00 1.25084889e+00 -9.46627200e-01 1.37050200e+00 -2.10863638e+00 3.78122300e-01 -6.92695737e-01 -2.59730034e-02 5.48967481e-01 1.63327605e-01 4.71000552e-01 -9.79389027e-02 -8.76308307e-02 -1.19874708e-01 2.44218903e-03 -3.35415065e-01 5.18388748e-01 -3.54403317e-01 3.43392789e-01 5.07896602e-01 6.51326358e-01 -1.16114533e+00 -8.59347343e-01 3.19103077e-02 -1.11391105e-01 -6.58833459e-02 7.11539447e-01 -4.62437093e-01 5.29579580e-01 -5.12294710e-01 1.63097888e-01 4.05501612e-02 -3.53345096e-01 6.18312061e-01 -5.11813499e-02 -2.63182759e-01 1.04409015e+00 -6.37135446e-01 1.39054489e+00 -4.82748389e-01 1.21838772e+00 -1.32374421e-01 -1.35124588e+00 8.27590823e-01 9.06333148e-01 1.57280102e-01 -6.24956667e-01 4.40607071e-01 9.23364162e-02 4.10930276e-01 -1.04091907e+00 5.01547456e-01 -3.38137597e-01 -3.79421353e-01 5.16154051e-01 2.14739516e-01 -7.96025619e-02 5.20277321e-01 1.67244915e-02 1.07954335e+00 -2.67540812e-02 1.00018597e+00 -3.11515719e-01 7.68057525e-01 4.64143842e-01 5.22081792e-01 -3.26718241e-02 -1.30006343e-01 2.93413281e-01 9.29082870e-01 -3.99218380e-01 -1.01634789e+00 -5.04671335e-01 -2.64971942e-01 1.15073562e+00 1.15895480e-01 -5.42238235e-01 -6.22768164e-01 -7.89678693e-01 -4.52903241e-01 9.17326510e-01 -7.00291991e-01 2.44873807e-01 -9.81531918e-01 -4.62149054e-01 4.36559647e-01 3.73801291e-01 5.96189797e-01 -1.36733758e+00 -6.32301688e-01 1.25731125e-01 -7.04859614e-01 -1.37797618e+00 -1.47475287e-01 2.10466415e-01 -3.67617786e-01 -1.35965204e+00 -3.46449077e-01 -1.12500226e+00 2.66764522e-01 -2.43716002e-01 1.29190075e+00 7.20358565e-02 1.70023933e-01 -1.69185579e-01 -6.95112467e-01 -3.54542345e-01 -8.59485388e-01 2.82273471e-01 -3.86631638e-01 -3.36330712e-01 6.05470002e-01 1.10353470e-01 2.47270733e-01 8.90371501e-02 -2.56673634e-01 1.98991433e-01 -1.74027726e-01 1.22675359e+00 1.04878031e-01 -1.34127125e-01 7.58538663e-01 -1.28873396e+00 8.83488536e-01 -6.39188886e-01 -1.50357515e-01 3.12227130e-01 1.26308158e-01 -1.60642609e-01 5.14550745e-01 -6.74320221e-01 -1.49630785e+00 -5.16971886e-01 -1.70836896e-01 1.62833393e-01 3.70129831e-02 7.31435239e-01 -4.27896172e-01 7.18568921e-01 9.52922225e-01 -4.26603734e-01 2.54237484e-02 -4.83274311e-01 3.49010795e-01 1.16002548e+00 3.29946995e-01 -4.87442195e-01 4.05485295e-02 -7.07321567e-03 -3.84576350e-01 -1.44346619e+00 -1.23759305e+00 -4.90702361e-01 -8.97662461e-01 -2.69143552e-01 1.26166558e+00 -7.65720427e-01 -6.20627820e-01 2.01856837e-01 -1.67407537e+00 -7.47797251e-01 -3.56587976e-01 4.90698427e-01 -5.73594689e-01 2.23551780e-01 -1.06492531e+00 -6.90804780e-01 -2.81860739e-01 -8.88241053e-01 3.57609749e-01 -1.45805299e-01 -8.14546585e-01 -1.11100852e+00 3.69733304e-01 4.06988591e-01 4.41280007e-03 2.21008107e-01 1.29023278e+00 -1.07627225e+00 -9.20734257e-02 9.67269838e-02 -1.62159532e-01 4.66492534e-01 3.98694158e-01 -2.13711724e-01 -8.26605439e-01 -3.87715660e-02 2.09117249e-01 -1.14215577e+00 2.90232331e-01 -2.57186498e-02 5.88915586e-01 -4.14377242e-01 -2.31365114e-01 -2.48522863e-01 8.96157980e-01 3.12335968e-01 5.75770795e-01 4.05613244e-01 5.50185978e-01 1.06575024e+00 9.04766798e-01 5.51239401e-02 4.11157161e-01 8.15725207e-01 -1.29906803e-01 4.94034169e-03 -3.36637944e-01 2.24378169e-01 1.22557186e-01 1.39279866e+00 -2.19888151e-01 -3.65288556e-01 -1.13071132e+00 6.64300382e-01 -2.01829123e+00 -1.05085802e+00 -3.25848520e-01 1.71678138e+00 1.55741286e+00 1.90419003e-01 -9.02404562e-02 1.02234505e-01 6.79863214e-01 3.37735564e-01 -2.01179102e-01 -4.38939542e-01 -3.05646002e-01 6.53091893e-02 -2.44709864e-01 7.68186033e-01 -1.43815720e+00 1.05650008e+00 6.04068089e+00 8.31837237e-01 -9.99357760e-01 7.42206693e-01 5.55737376e-01 2.66811818e-01 2.33438879e-01 -9.93535295e-02 -5.91411352e-01 2.21419081e-01 1.00754666e+00 -4.12964433e-01 -1.87218681e-01 9.45979774e-01 -2.35690206e-01 -2.70605475e-01 -1.37522805e+00 6.33077383e-01 1.81492612e-01 -1.52423859e+00 -3.78420651e-01 -4.40590322e-01 4.98242885e-01 -1.92466695e-02 -5.86295187e-01 8.47653329e-01 1.78720266e-01 -1.00790334e+00 4.83503699e-01 -2.18574658e-01 9.24434423e-01 -4.50535268e-01 1.01296151e+00 6.45695448e-01 -7.95154035e-01 3.28617007e-01 -2.88479805e-01 -6.06518328e-01 2.41513729e-01 -1.96369682e-02 -1.08535063e+00 3.78829658e-01 5.13001382e-01 7.57689118e-01 -1.34460628e-01 2.49409690e-01 -5.95255792e-01 7.12486029e-01 -7.76906237e-02 -4.18219358e-01 1.01993211e-01 2.50385236e-02 5.56394696e-01 1.30643213e+00 -1.21208042e-01 5.41823328e-01 3.00871015e-01 4.18762594e-01 -2.08138257e-01 4.60424840e-01 -7.27569044e-01 6.49993420e-02 3.29559147e-01 9.91316915e-01 -4.76081342e-01 -5.26376367e-01 -6.85238957e-01 6.51386499e-01 1.01069248e+00 2.31611058e-01 -4.79227751e-01 -1.64031103e-01 1.50001556e-01 4.87995654e-04 1.22806720e-01 -1.76756561e-01 -3.37379128e-02 -1.08034503e+00 -1.63905695e-01 -8.48141015e-01 5.92038453e-01 -5.38647354e-01 -1.55346191e+00 8.93967390e-01 2.68087775e-01 -1.14449060e+00 -7.13875890e-01 -7.44663477e-01 -5.91203034e-01 9.69505966e-01 -1.18746078e+00 -1.12626946e+00 -1.41773224e-02 3.93775284e-01 1.01416218e+00 -3.89518529e-01 1.26372027e+00 3.45851570e-01 -4.66354281e-01 2.37396896e-01 -1.51357397e-01 6.45774901e-01 9.16837394e-01 -1.30963504e+00 -2.30093952e-02 4.07009572e-01 -7.88734406e-02 3.23434770e-01 8.47885251e-01 -5.49251795e-01 -8.84884775e-01 -7.99138725e-01 1.35696208e+00 -4.41970646e-01 1.10502219e+00 -4.89838600e-01 -1.27860153e+00 9.07898903e-01 1.05966163e+00 -1.11269832e-01 1.01020670e+00 6.96272612e-01 -1.43054143e-01 2.84744173e-01 -7.24474669e-01 5.62970698e-01 6.07354522e-01 -6.94787085e-01 -1.43507719e+00 7.53472209e-01 9.50109243e-01 -8.82603228e-01 -1.02176058e+00 3.55068803e-01 -1.31190091e-01 -3.11596990e-01 5.89954138e-01 -9.40506876e-01 9.98112500e-01 -1.11053877e-01 -2.36235797e-01 -1.14068830e+00 1.93490371e-01 -3.40041667e-01 -3.23748022e-01 1.48391449e+00 7.30818927e-01 -2.87656456e-01 3.53759944e-01 5.16998231e-01 -1.03108615e-01 -7.29288697e-01 -1.41351628e+00 -7.81736016e-01 3.47241133e-01 -1.24175355e-01 1.09553084e-01 1.43046331e+00 9.33735013e-01 1.39723051e+00 -3.34884197e-01 -4.83175367e-01 -1.21814542e-01 3.35928887e-01 6.64326668e-01 -8.90425384e-01 -2.53129035e-01 -1.24833599e-01 -2.57613719e-01 -8.99905384e-01 8.06752026e-01 -1.00958276e+00 1.87746435e-01 -1.38829780e+00 1.23216502e-01 -4.42168295e-01 3.16542685e-01 4.07373965e-01 -1.54941320e-01 -1.73708275e-01 -1.21513516e-01 2.21431389e-01 -7.32284188e-01 9.20776308e-01 1.20439506e+00 -3.96840245e-01 -1.06850430e-01 -1.62760600e-01 2.95724161e-02 8.46070707e-01 5.24994135e-01 -2.35222369e-01 -4.76087004e-01 -3.64127278e-01 -3.15178111e-02 4.02148068e-01 -1.64173827e-01 -4.08142984e-01 2.05365699e-02 -1.59039512e-01 -1.98896661e-01 -6.40897512e-01 3.66387874e-01 -5.22012174e-01 -3.36996108e-01 1.94518238e-01 -6.42923176e-01 -1.83671162e-01 2.02540308e-01 2.07248822e-01 -6.50402427e-01 -5.48234701e-01 6.13007963e-01 -7.36986324e-02 -9.10295367e-01 -4.27204102e-01 -5.61298192e-01 6.46170199e-01 1.15892935e+00 3.98812801e-01 -8.14508200e-01 -3.21982384e-01 -6.59095824e-01 1.99441209e-01 7.36230835e-02 5.50311744e-01 2.36087173e-01 -1.20695341e+00 -9.32505667e-01 -3.48138630e-01 2.44091228e-01 1.98938027e-01 1.07973762e-01 6.63639843e-01 -3.81777823e-01 3.70039761e-01 -1.14240900e-01 -4.65847343e-01 -1.69817710e+00 7.70506799e-01 1.66700751e-01 -5.99246621e-01 -9.04297590e-01 6.15440130e-01 -3.21133528e-03 -3.35665196e-01 4.51165959e-02 -1.57730639e-01 -8.21392953e-01 4.71564680e-01 6.77630365e-01 6.34928420e-02 -5.61088882e-02 -1.06757796e+00 -2.92736799e-01 -1.95711225e-01 -1.85029954e-01 2.34385058e-02 1.31435668e+00 -1.56489283e-01 -4.02611732e-01 1.07163608e+00 1.23902881e+00 -1.26226738e-01 -7.64980733e-01 -4.32323456e-01 5.66408277e-01 -9.52987596e-02 -2.51765758e-01 -3.12509745e-01 -3.53520602e-01 9.69769359e-01 4.93358225e-02 5.63190043e-01 6.23723209e-01 4.04129416e-01 6.56091154e-01 6.36602044e-01 2.57602781e-01 -1.32231164e+00 1.24943815e-01 1.18183410e+00 1.20584631e+00 -1.46651685e+00 1.43177047e-01 -6.61378324e-01 -7.18625724e-01 9.81463075e-01 7.75271833e-01 -7.71807209e-02 6.28564000e-01 3.01753074e-01 1.46238834e-01 -2.19307244e-01 -8.42782259e-01 -1.51315555e-01 1.04048684e-01 5.70568323e-01 1.19630945e+00 7.35364780e-02 -6.99980021e-01 7.61058152e-01 -2.56052434e-01 -3.19118232e-01 5.46426892e-01 9.60852563e-01 -1.30670637e-01 -1.26275623e+00 -7.74227008e-02 2.94243187e-01 -5.02315760e-01 -7.31351078e-02 -4.06707883e-01 1.12959218e+00 -7.13918284e-02 1.10301900e+00 4.07661498e-01 6.19169371e-03 3.10948163e-01 8.82736668e-02 3.97834301e-01 -1.04225719e+00 -5.42719662e-01 1.65046356e-03 1.20500839e+00 -1.98752463e-01 -1.01255786e+00 -6.09169245e-01 -1.36659741e+00 -1.78922877e-01 -3.43362749e-01 4.07420576e-01 -6.26592934e-02 1.39437532e+00 -1.81973785e-01 7.71304429e-01 2.54631519e-01 -4.77502555e-01 -2.23995999e-01 -1.53693640e+00 -2.96304017e-01 6.57039225e-01 2.65964329e-01 -8.15329373e-01 1.11884959e-02 3.96337688e-01]	[10.840078353881836, 9.306209564208984]
1dc35de0-0b79-4035-859a-cc4d6fae0c3d	image-super-resolution-with-non-local-sparse	null	null	http://openaccess.thecvf.com//content/CVPR2021/html/Mei_Image_Super-Resolution_With_Non-Local_Sparse_Attention_CVPR_2021_paper.html	http://openaccess.thecvf.com//content/CVPR2021/papers/Mei_Image_Super-Resolution_With_Non-Local_Sparse_Attention_CVPR_2021_paper.pdf	Image Super-Resolution With Non-Local Sparse Attention	Both non-local (NL) operation and sparse representation are crucial for Single Image Super-Resolution (SISR). In this paper, we investigate their combinations and propose a novel Non-Local Sparse Attention (NLSA) with dynamic sparse attention pattern. NLSA is designed to retain long-range modeling capability from NL operation while enjoying robustness and high-efficiency of sparse representation. Specifically, NLSA rectifies NL attention with spherical locality sensitive hashing (LSH) that partitions the input space into hash buckets of related features. For every query signal, NLSA assigns a bucket to it and only computes attention within the bucket. The resulting sparse attention prevents the model from attending to locations that are noisy and less-informative, while reducing the computational cost from quadratic to asymptotic linear with respect to the spatial size. Extensive experiments validate the effectiveness and efficiency of NLSA. With a few non-local sparse attention modules, our architecture, called non-local sparse network (NLSN), reaches state-of-the-art performance for SISR quantitatively and qualitatively.	['Yuqian Zhou', 'Yuchen Fan', 'Yiqun Mei']	2021-06-19	null	null	null	cvpr-2021-1	['long-range-modeling']	['natural-language-processing']	[ 5.68237752e-02 -5.96652515e-02 -3.11389655e-01 -1.19014271e-01 -1.05817163e+00 1.67872733e-03 1.83003515e-01 -5.50669208e-02 -1.45956621e-01 4.32834834e-01 6.67559445e-01 4.19685036e-01 -5.75690828e-02 -5.87318540e-01 -8.12591672e-01 -8.22236180e-01 -1.61590442e-01 7.92377964e-02 5.34257829e-01 -1.08797818e-01 2.10905492e-01 6.22746766e-01 -1.56707931e+00 6.01253450e-01 5.79078197e-01 1.14651442e+00 6.90508187e-01 4.09934938e-01 -2.48010326e-02 1.11287379e+00 -4.43169594e-01 1.26433402e-01 2.36200809e-01 -4.35567617e-01 -5.45972943e-01 -2.47166425e-01 4.91327077e-01 -2.91298211e-01 -8.32368791e-01 9.60611284e-01 6.01998508e-01 2.17243224e-01 3.30453753e-01 -8.99780989e-01 -1.26079619e+00 6.88920617e-01 -1.05213261e+00 6.37431026e-01 2.33705997e-01 3.96090224e-02 1.03460443e+00 -1.16920245e+00 4.93364781e-01 1.34628570e+00 7.76431918e-01 2.20807925e-01 -1.13249290e+00 -6.81642473e-01 1.75710455e-01 3.09130341e-01 -1.90232170e+00 -5.47912717e-01 7.27233887e-01 -7.84645900e-02 9.00136113e-01 3.04902434e-01 3.48289669e-01 7.43565142e-01 1.47585711e-02 8.14029813e-01 8.24665308e-01 -9.73137394e-02 2.50057638e-01 1.58820245e-02 -3.10418960e-02 6.63523018e-01 2.10101947e-01 -1.68258131e-01 -9.67707217e-01 -4.56630141e-02 1.22380602e+00 3.26434076e-01 -3.59869689e-01 -3.38346034e-01 -1.29769504e+00 8.58601272e-01 9.47906435e-01 5.23821890e-01 -5.66636920e-01 2.09572703e-01 2.20439419e-01 5.45851402e-02 2.13615075e-01 2.62448430e-01 7.45005980e-02 3.68390411e-01 -1.17951107e+00 2.06008088e-02 2.74737239e-01 1.03517461e+00 8.47525358e-01 2.61677533e-01 -5.29695213e-01 7.93577135e-01 -8.19950998e-02 6.20147943e-01 7.31008947e-01 -9.45623398e-01 1.47630826e-01 5.38555801e-01 3.71934869e-03 -1.44187999e+00 -1.81541339e-01 -7.08232164e-01 -1.33632123e+00 -3.21022600e-01 -2.46578962e-01 4.20330673e-01 -8.66197586e-01 1.58206463e+00 1.51689038e-01 4.90200400e-01 -3.20289768e-02 1.28028035e+00 1.05076981e+00 1.00607955e+00 8.88446495e-02 -2.23291144e-01 1.28351450e+00 -9.95718062e-01 -6.07483625e-01 -1.14831403e-01 1.52386785e-01 -5.69379508e-01 1.12179434e+00 -1.29910950e-02 -1.26904929e+00 -6.58904970e-01 -7.27783322e-01 -5.73730528e-01 -8.74090716e-02 -3.92947197e-02 4.12164748e-01 2.27016653e-03 -1.22833431e+00 2.27974251e-01 -6.59094334e-01 -2.58663744e-01 5.70594907e-01 2.67119676e-01 -3.97356659e-01 -3.79587322e-01 -1.17885697e+00 3.81526411e-01 4.89077307e-02 -1.87390149e-01 -9.71661448e-01 -8.98180664e-01 -1.03913176e+00 5.98623753e-01 2.27680206e-01 -5.22194982e-01 7.88349867e-01 -6.05738759e-01 -1.18589604e+00 5.34019053e-01 -5.77145875e-01 -6.83774054e-01 -3.14869612e-01 -1.80436343e-01 -2.82601684e-01 5.06469429e-01 3.76816124e-01 8.19549859e-01 1.18318951e+00 -1.19848716e+00 -3.54667723e-01 -4.13193315e-01 -2.83975571e-01 2.86728799e-01 -4.19723004e-01 8.95297825e-02 -6.08276725e-01 -9.85824883e-01 3.41757327e-01 -5.68256736e-01 -3.34218830e-01 3.04150265e-02 -2.81675726e-01 8.39456469e-02 1.01248598e+00 -6.11095846e-01 1.54550171e+00 -2.57319951e+00 2.69682854e-01 2.23099217e-02 4.73089367e-01 2.31098592e-01 -3.70412469e-01 2.48849839e-01 7.57384449e-02 -5.69406599e-02 -3.72789383e-01 -3.28575760e-01 -4.45272118e-01 -2.53347447e-03 -5.60968816e-01 5.74853599e-01 1.69506863e-01 1.20109642e+00 -8.44223320e-01 -6.57841206e-01 2.09210038e-01 8.56708646e-01 -6.89712405e-01 1.93630591e-01 1.27287045e-01 3.20879340e-01 -5.36497474e-01 1.04582620e+00 5.52594006e-01 -7.41159558e-01 -2.92265892e-01 -5.60455859e-01 -1.38684809e-01 7.74951652e-02 -1.06800103e+00 1.83561504e+00 -4.86135840e-01 4.03566718e-01 1.35565385e-01 -7.52591670e-01 9.23765123e-01 -4.57175635e-02 4.31054145e-01 -1.03721476e+00 -2.15308800e-01 1.01269595e-01 -4.41162735e-01 -3.15082014e-01 5.98740876e-01 9.07160640e-02 -5.25804609e-02 2.15727106e-01 1.62418470e-01 4.58645582e-01 -2.62331188e-01 5.23037851e-01 1.12360847e+00 -4.59423184e-01 6.14441335e-01 -2.48291194e-01 6.02715015e-01 -3.49964142e-01 5.32726705e-01 9.31023359e-01 -1.84554666e-01 9.85811532e-01 1.31018281e-01 -5.09765267e-01 -1.10773873e+00 -1.04929757e+00 -1.23435315e-02 1.38406658e+00 5.32920420e-01 -4.20337260e-01 -4.03003305e-01 -3.60407889e-01 1.34322762e-01 2.89372474e-01 -6.63225055e-01 -1.44558311e-01 -7.10511327e-01 -3.53448749e-01 3.25356096e-01 5.68474472e-01 5.18153667e-01 -1.31045735e+00 -7.30200112e-01 -1.70864761e-02 -2.58844495e-01 -1.03884196e+00 -8.38630378e-01 3.30759585e-02 -6.18077457e-01 -5.25243104e-01 -1.05790889e+00 -8.67415845e-01 5.69679677e-01 9.91118133e-01 8.49840701e-01 -6.94714636e-02 -4.01293874e-01 1.17046930e-01 -5.12914181e-01 1.46292508e-01 2.73552090e-01 2.62949973e-01 -8.83902162e-02 2.88572699e-01 3.06834072e-01 -8.02745700e-01 -8.93777430e-01 2.18477905e-01 -1.01652348e+00 -2.35102788e-01 1.08264709e+00 9.00526404e-01 1.01818776e+00 -1.52010560e-01 6.68246806e-01 -6.67752028e-01 1.93178043e-01 -8.39788914e-01 -2.19473436e-01 -5.45740202e-02 -7.37682963e-03 5.86024811e-03 7.69513071e-01 -4.09239978e-01 -7.46833444e-01 1.63662016e-01 1.84336841e-01 -8.96633685e-01 6.55187154e-03 2.19400600e-01 -3.97854894e-02 -4.03591305e-01 4.22692865e-01 8.56917262e-01 -1.13818839e-01 -5.87786794e-01 4.53217864e-01 6.08142734e-01 6.86134756e-01 -1.45767033e-01 8.11240852e-01 8.47262323e-01 -7.86576644e-02 -1.14612687e+00 -1.05377471e+00 -7.06379056e-01 -2.56449819e-01 2.10675210e-01 6.49215937e-01 -1.34465086e+00 -5.27108431e-01 1.61984667e-01 -8.34768951e-01 7.64944851e-02 -6.52339220e-01 1.39825329e-01 -4.00504172e-01 3.36518496e-01 -6.37935758e-01 -7.92953372e-01 -3.72125953e-01 -9.01352346e-01 1.42781842e+00 1.83695927e-01 1.11947488e-02 -3.28962177e-01 -1.55813426e-01 2.18042195e-01 8.90152752e-01 -5.12127206e-02 6.27779543e-01 -4.30855006e-01 -9.91455793e-01 1.32721178e-02 -7.42259860e-01 5.13568446e-02 -6.68652803e-02 -7.78181434e-01 -9.62907314e-01 -5.76415718e-01 6.01000376e-02 -4.20294791e-01 1.22581911e+00 5.51088989e-01 1.51532662e+00 -6.47561789e-01 -1.67731538e-01 1.00616229e+00 1.52257395e+00 -1.15869567e-01 7.59265602e-01 2.13835940e-01 9.79475737e-01 2.33808175e-01 4.45315003e-01 6.25173628e-01 4.70139176e-01 6.35534525e-01 4.35872108e-01 -3.28917891e-01 -5.12933850e-01 -3.64360124e-01 2.80469954e-01 9.73190665e-01 2.85227358e-01 -8.23464803e-03 -4.25750524e-01 9.19111729e-01 -1.70235550e+00 -1.12102902e+00 3.52206767e-01 2.05406547e+00 7.80740738e-01 -2.15909004e-01 4.94557880e-02 -1.27389073e-01 7.44422853e-01 7.17638314e-01 -6.82314992e-01 -5.34589812e-02 -5.24510682e-01 1.53401211e-01 5.88651121e-01 5.40606380e-01 -9.68127668e-01 1.08621860e+00 5.82312441e+00 1.18962169e+00 -1.06615996e+00 2.84453064e-01 7.00144589e-01 -3.45187455e-01 -4.57041174e-01 -3.02859843e-01 -8.82256210e-01 6.02102339e-01 7.77467847e-01 3.87178026e-02 6.25120640e-01 8.72733355e-01 4.42502229e-03 -2.21322607e-02 -6.53526545e-01 1.18024588e+00 3.25510532e-01 -1.57411408e+00 5.47784209e-01 -1.81589499e-01 8.94356489e-01 1.73947394e-01 3.52132291e-01 2.14456916e-01 -1.21037111e-01 -1.22489190e+00 5.69955945e-01 4.52501744e-01 1.07800770e+00 -9.24636185e-01 6.42145991e-01 1.49388582e-01 -1.53406954e+00 -4.85301465e-01 -5.78369021e-01 2.71617860e-01 1.71404287e-01 5.69264591e-01 -2.04506949e-01 3.51315618e-01 1.12775779e+00 8.36282492e-01 -5.10903180e-01 9.93204057e-01 1.77266374e-01 3.73585671e-01 -3.40269208e-01 4.06050920e-01 4.00360942e-01 1.88024685e-01 7.86178470e-01 1.34550190e+00 4.23127443e-01 3.43259394e-01 1.62709936e-01 9.03132260e-01 -1.56252041e-01 3.56103666e-02 -6.41147912e-01 1.37037084e-01 9.72848833e-01 9.37402189e-01 -5.57984173e-01 -3.14671844e-01 -4.06764001e-01 1.19547331e+00 4.54904348e-01 3.93626064e-01 -5.68755448e-01 -5.08486271e-01 6.48127973e-01 5.41634977e-01 8.07062924e-01 -5.45512848e-02 -3.32454413e-01 -1.03940606e+00 -5.58018424e-02 -8.77664506e-01 4.39112425e-01 -7.45391488e-01 -1.17408812e+00 7.97018528e-01 -3.12393129e-01 -1.07709396e+00 1.70290455e-01 2.08032146e-01 -2.75618553e-01 8.57295275e-01 -1.87949955e+00 -1.28034103e+00 -4.23382878e-01 8.93889904e-01 7.28692949e-01 -1.59919426e-01 6.18130267e-01 4.14690286e-01 -4.95458096e-01 7.40784943e-01 -2.87547018e-02 -1.53599292e-01 5.95793486e-01 -7.88903356e-01 4.26633209e-01 7.67633021e-01 1.20407917e-01 7.86243677e-01 3.78591657e-01 -5.35253704e-01 -1.43663967e+00 -1.29738951e+00 1.00970352e+00 3.11272033e-02 6.18645012e-01 -3.16191614e-01 -1.32517540e+00 5.18889546e-01 -1.40242726e-01 6.06270552e-01 4.98382539e-01 -2.40652502e-01 -8.02597404e-01 -3.10425878e-01 -1.18457627e+00 3.18459719e-01 1.01765382e+00 -8.87221813e-01 -4.15120870e-01 1.06867947e-01 1.22736502e+00 -1.97500676e-01 -7.80206740e-01 2.97777683e-01 3.03735048e-01 -1.11203003e+00 1.41517568e+00 -1.68872550e-01 4.50756609e-01 -5.66527903e-01 -5.57866037e-01 -8.18359792e-01 -1.01426005e+00 -6.86504245e-01 -5.84481776e-01 8.37014318e-01 -1.18571036e-01 -3.09908479e-01 6.25039816e-01 -1.45276830e-01 -1.40756473e-01 -9.66593921e-01 -9.70911264e-01 -7.16940403e-01 -4.37338144e-01 1.24193206e-01 5.58945239e-01 9.57466245e-01 -3.08916599e-01 2.77152359e-01 -8.28938007e-01 6.30667984e-01 9.03873324e-01 3.37808043e-01 3.18030149e-01 -8.61864626e-01 -2.15357780e-01 -2.19417289e-01 -5.41669726e-01 -1.33104551e+00 -4.24832404e-02 -7.18424618e-01 -5.44329844e-02 -1.18478644e+00 5.75455070e-01 -3.20126384e-01 -6.50024474e-01 5.41791439e-01 -1.31305382e-01 7.35606492e-01 3.10820162e-01 6.47744477e-01 -1.20631337e+00 8.44710588e-01 1.09649384e+00 3.00317183e-02 -2.54719019e-01 -5.37180960e-01 -9.68159258e-01 5.27848184e-01 5.02099574e-01 -4.09241915e-01 -2.59986162e-01 -5.89484334e-01 -2.18404889e-01 9.96216834e-02 4.47517365e-01 -1.11930072e+00 5.82499921e-01 9.03013274e-02 4.11270738e-01 -6.99928522e-01 2.96499252e-01 -6.81192636e-01 -5.27638644e-02 1.36733115e-01 -5.25114715e-01 -1.98024645e-01 -3.57003473e-02 7.38459766e-01 -4.81017500e-01 3.00845861e-01 1.18202972e+00 -2.08429873e-01 -7.87705302e-01 5.05027652e-01 5.41070616e-03 3.05994898e-02 9.24387217e-01 -1.42531738e-01 -1.77027345e-01 -3.54790479e-01 -5.54086447e-01 1.55029938e-01 4.16885376e-01 2.73555130e-01 9.22267497e-01 -1.43570995e+00 -7.34164119e-01 5.33367634e-01 1.15032054e-01 2.10287258e-01 8.24305415e-01 7.90791690e-01 -2.39524245e-01 7.71424890e-01 -7.07633495e-02 -5.12527406e-01 -8.43119204e-01 8.78310680e-01 -1.63327888e-01 -1.89519912e-01 -1.08633316e+00 1.14031887e+00 6.93699598e-01 1.07952744e-01 4.71231610e-01 -3.11081894e-02 -2.13201523e-01 -2.04782873e-01 1.07111263e+00 4.01780933e-01 -2.22228691e-01 -9.72136199e-01 -3.81323457e-01 6.97711945e-01 -2.88521111e-01 4.44943964e-01 1.46240449e+00 -4.63788360e-01 -1.54891551e-01 2.89010972e-01 1.25749719e+00 -3.19637246e-02 -1.29602051e+00 -6.19951487e-01 -4.33315903e-01 -7.78248370e-01 4.51090634e-01 -5.83754599e-01 -1.30764151e+00 6.00530684e-01 4.37385350e-01 -5.85558712e-02 1.33593500e+00 3.38833690e-01 1.34503734e+00 8.57193395e-02 3.92373115e-01 -4.60515380e-01 2.27795199e-01 4.51671809e-01 1.21512306e+00 -1.17409587e+00 -3.38079780e-02 -2.71618873e-01 -6.83670580e-01 4.18072820e-01 5.47687948e-01 -5.52215159e-01 5.35142839e-01 3.18661928e-01 -4.10830438e-01 -2.23327458e-01 -5.63754916e-01 -2.03330070e-01 3.51365328e-01 7.01662719e-01 5.40760085e-02 -1.08478792e-01 1.97138533e-01 7.12504864e-01 8.88471976e-02 -1.35181740e-01 1.74609780e-01 6.30502641e-01 -8.14943075e-01 -3.83883685e-01 -3.24160308e-01 2.72522658e-01 -3.88052791e-01 -4.50609922e-01 -6.66924715e-02 4.76536542e-01 4.61615669e-03 4.10769790e-01 2.83885151e-01 -2.13883772e-01 1.01917937e-01 -5.22131264e-01 4.98628430e-02 -5.68841815e-01 -4.36485052e-01 2.30103895e-01 -6.12934172e-01 -1.11231780e+00 -1.54898226e-01 -4.03745592e-01 -1.14493084e+00 -2.27743253e-01 7.52020720e-03 7.94791058e-03 1.70722842e-01 5.15730381e-01 8.85744750e-01 4.56441283e-01 8.17907214e-01 -9.91876125e-01 -4.74161565e-01 -7.21724451e-01 -8.20974410e-01 2.47372344e-01 7.82960653e-01 -4.39636022e-01 -4.51823115e-01 -1.16855249e-01]	[10.945137023925781, -1.8701817989349365]
e55e2e09-90d5-4666-affd-9d1d84972642	chinese-grammatical-error-detection-based-on	null	null	https://aclanthology.org/2020.nlptea-1.15	https://aclanthology.org/2020.nlptea-1.15.pdf	Chinese Grammatical Error Detection Based on BERT Model	Automatic grammatical error correction is of great value in assisting second language writing. In 2020, the shared task for Chinese grammatical error diagnosis(CGED) was held in NLP-TEA. As the LDU team, we participated the competition and submitted the final results. Our work mainly focused on grammatical error detection, that is, to judge whether a sentence contains grammatical errors. We used the BERT pre-trained model for binary classification, and we achieve 0.0391 in FPR track, ranking the second in all teams. In error detection track, the accuracy, recall and F-1 of our submitted result are 0.9851, 0.7496 and 0.8514 respectively.	['Mofan Duan', 'Yong Cheng']	null	null	null	null	aacl-nlp-tea-2020-12-1	['grammatical-error-detection']	['natural-language-processing']	[-3.72281253e-01 3.28685284e-01 2.86884397e-01 -4.38370019e-01 -9.27284002e-01 -2.11263776e-01 -2.05742434e-01 5.60919940e-01 -6.38314903e-01 1.23255563e+00 1.44913629e-01 -3.86176944e-01 3.43352258e-01 -4.40671593e-01 -6.12937212e-01 1.01478338e-01 2.25270391e-01 2.77858019e-01 -3.40814441e-02 -2.56821632e-01 6.32242382e-01 -2.47734264e-01 -8.84588718e-01 5.34676492e-01 1.90699971e+00 6.89123392e-01 3.79853427e-01 1.06788349e+00 7.16416240e-02 9.40758526e-01 -1.08067119e+00 -9.23454523e-01 -6.12298191e-01 -4.70388502e-01 -1.25372791e+00 -7.06939280e-01 2.04645067e-01 -1.17172189e-01 -7.44243711e-02 1.29143369e+00 7.35832870e-01 3.60738598e-02 5.20691335e-01 -8.38009834e-01 -9.37493503e-01 7.46031940e-01 -5.24801649e-02 4.11745846e-01 5.44881880e-01 -3.20222527e-01 8.28716636e-01 -1.31882846e+00 7.15649366e-01 1.03446090e+00 8.07667971e-01 1.05806303e+00 -4.38590378e-01 -4.63400662e-01 8.64917487e-02 3.11270028e-01 -1.28191781e+00 -4.10364419e-01 6.46444634e-02 -3.05176318e-01 1.50954723e+00 2.70235062e-01 1.09528661e-01 7.37571776e-01 4.92809385e-01 8.06541204e-01 7.85443902e-01 -1.00692427e+00 -2.57807940e-01 1.32772148e-01 5.04723907e-01 9.92054343e-01 3.59105885e-01 -3.86920184e-01 -5.94331682e-01 2.29613036e-01 -2.53887951e-01 -4.35400635e-01 -4.02417749e-01 1.36119795e+00 -7.18477011e-01 5.25290370e-01 1.25657395e-01 4.72909421e-01 1.82926301e-02 9.18439254e-02 4.60698217e-01 7.34727979e-01 7.66314745e-01 3.93640846e-01 -6.99792385e-01 -5.58201730e-01 -6.13472044e-01 2.27081433e-01 7.22231030e-01 1.20048976e+00 1.43509865e-01 -3.26345712e-01 -4.74206984e-01 1.12194765e+00 4.39031184e-01 4.02473181e-01 6.83219135e-01 -5.13436019e-01 9.27757859e-01 6.15560532e-01 4.30947468e-02 -8.28212082e-01 -5.41409850e-01 -4.54718798e-01 -8.66655350e-01 -4.86121714e-01 2.23862171e-01 -5.01781762e-01 -8.09827745e-01 1.48307729e+00 -3.51909459e-01 -3.25790346e-01 2.53886450e-02 5.44627428e-01 1.18726456e+00 4.78042930e-01 3.22252452e-01 -2.23872125e-01 1.05775309e+00 -1.08254492e+00 -1.04743528e+00 -7.65011758e-02 1.49689341e+00 -1.06218529e+00 1.02457702e+00 6.40510261e-01 -1.05169463e+00 -4.14068431e-01 -8.72667313e-01 -3.11011195e-01 -3.75439115e-02 7.90333748e-01 2.25823939e-01 6.46937191e-01 -8.60554516e-01 7.23935068e-01 -6.88011527e-01 -2.82190025e-01 3.73011708e-01 4.84133512e-03 -4.18417305e-01 -1.92020729e-01 -1.23507762e+00 1.06697905e+00 3.42754930e-01 1.51168942e-01 -3.69330227e-01 -5.67045927e-01 -4.12605286e-01 -2.75898337e-01 -2.28354290e-01 -3.53788108e-01 1.32994211e+00 -3.96510243e-01 -1.05848193e+00 1.33298683e+00 -5.03735662e-01 -3.64767373e-01 5.85038424e-01 -4.58681494e-01 -9.33212817e-01 -4.09145117e-01 3.08936626e-01 3.31627846e-01 1.22798402e-02 -3.99999887e-01 -1.06191635e+00 -5.47358394e-01 -3.63645643e-01 8.13608691e-02 -1.65080324e-01 7.61117756e-01 -2.71376073e-01 -7.06252337e-01 1.99109823e-01 -5.00628293e-01 1.37941509e-01 -3.99100304e-01 -4.58364993e-01 -9.02182817e-01 1.84585571e-01 -1.63285732e+00 2.12648296e+00 -1.97891510e+00 -1.12061135e-01 -1.57441869e-01 9.42627415e-02 3.58549446e-01 2.08685637e-01 1.95410535e-01 1.23199649e-01 5.80973983e-01 -1.62897721e-01 -6.38791144e-01 -8.85001346e-02 -1.87028021e-01 7.84844756e-02 1.49700537e-01 4.43903208e-01 9.31230962e-01 -9.73483860e-01 -3.73408705e-01 -4.71764088e-01 -2.06894174e-01 -6.14149630e-01 3.86688769e-01 6.43838495e-02 4.47606534e-01 -1.99696168e-01 7.51056671e-01 7.75776803e-01 -5.31323953e-03 8.53563026e-02 4.58564073e-01 -7.37574771e-02 1.03845716e+00 -7.26783812e-01 1.58399916e+00 -3.67783040e-01 5.70044696e-01 -3.51763010e-01 -5.94735265e-01 1.21462607e+00 3.82894486e-01 -3.09470385e-01 -8.37518036e-01 -8.87471344e-03 8.87047052e-01 2.31354371e-01 -8.20478737e-01 6.88993752e-01 5.34780174e-02 -2.98623770e-01 2.04347745e-01 2.78720468e-01 2.96258807e-01 2.64819473e-01 3.13315302e-01 1.36931062e+00 -3.64294536e-02 2.20356554e-01 -3.96826446e-01 6.33914948e-01 -1.55599639e-01 7.59490848e-01 7.00520277e-01 -4.28677946e-01 8.24707270e-01 5.59941471e-01 -2.76730359e-01 -8.71322811e-01 -4.51623231e-01 -3.69115233e-01 7.01867998e-01 -3.62755567e-01 -7.28676856e-01 -8.29973638e-01 -1.08517921e+00 -2.28486091e-01 8.06235254e-01 -2.44679168e-01 -3.33577186e-01 -7.84302175e-01 -6.72490716e-01 9.38855052e-01 3.91785234e-01 6.48252606e-01 -1.30472302e+00 1.38683379e-01 3.59122306e-01 -5.55351853e-01 -1.02948785e+00 -6.22280478e-01 2.91474387e-02 -7.91406751e-01 -1.19030333e+00 -6.10903740e-01 -1.19592702e+00 8.29699337e-01 -4.78090078e-01 1.31233013e+00 8.36118877e-01 -2.11206689e-01 -3.30627710e-01 -1.03377438e+00 -5.97837090e-01 -6.22675478e-01 1.00159585e-01 -2.60154642e-02 -6.57715082e-01 4.85710740e-01 8.87460783e-02 -9.90559086e-02 -1.14841409e-01 6.88202605e-02 -1.46047726e-01 6.54591247e-02 1.07235324e+00 2.16024756e-01 -3.08981568e-01 7.99585700e-01 -1.19525528e+00 9.25314426e-01 -3.45653832e-01 -1.41869485e-01 6.53290451e-01 -8.09335053e-01 -1.48390248e-01 5.79298139e-01 3.31302434e-01 -8.92082214e-01 -5.56040764e-01 -7.77379692e-01 4.65754896e-01 8.67982581e-02 6.78830028e-01 -1.79448262e-01 1.21800587e-01 5.81816375e-01 -8.90602395e-02 -4.79489148e-01 -7.37640023e-01 -2.67614037e-01 1.21063125e+00 3.93102050e-01 -4.79214340e-01 -2.75090694e-01 -8.15820515e-01 -5.38914621e-01 -3.61016750e-01 -9.53179181e-01 -2.15553626e-01 -4.59945470e-01 2.60793255e-03 5.57402611e-01 -9.81135249e-01 -5.81588864e-01 9.89262104e-01 -1.78530908e+00 -8.58685896e-02 2.49674499e-01 4.90100026e-01 -6.33001253e-02 4.65300083e-01 -6.86327398e-01 -8.86818349e-01 -8.18994582e-01 -7.06233978e-01 7.82318771e-01 1.41187981e-01 -4.46554214e-01 -7.96439826e-01 -2.82530747e-02 2.25663409e-01 2.32678607e-01 -1.46598980e-01 9.48924005e-01 -6.17350519e-01 1.31288111e-01 -1.52936131e-01 -2.95403212e-01 6.23616517e-01 -1.81020826e-01 -1.19386926e-01 -6.89583063e-01 -1.23745374e-01 -1.94717601e-01 -3.71768564e-01 9.67147052e-01 1.46907359e-01 1.52670050e+00 -1.83930561e-01 -1.91435352e-01 3.62926573e-01 1.19054174e+00 3.38709325e-01 8.45277190e-01 8.58525932e-02 6.72474384e-01 3.97670656e-01 9.10701096e-01 4.10962582e-01 5.81648529e-01 6.83864772e-01 -9.45306644e-02 5.13268709e-01 -2.85295874e-01 -5.29007614e-01 4.23740417e-01 1.27676105e+00 -6.92985877e-02 -7.81284869e-01 -1.21616518e+00 5.70135295e-01 -1.74342120e+00 -4.32721794e-01 -9.60847557e-01 2.05172014e+00 1.07500875e+00 1.04644872e-01 -3.13037544e-01 1.52131647e-01 1.05272269e+00 -6.56654477e-01 9.63835120e-02 -9.40194845e-01 -3.83452982e-01 5.75791061e-01 1.25485688e-01 7.54052579e-01 -9.70059574e-01 1.27899539e+00 6.23677397e+00 7.77094901e-01 -6.25622690e-01 6.20782554e-01 9.08363104e-01 2.43836254e-01 -1.54332802e-01 -1.29020870e-01 -1.38999319e+00 1.13410294e+00 1.26813900e+00 -1.57338113e-01 3.83228473e-02 3.47213537e-01 1.36015341e-01 -1.92045704e-01 -7.29942679e-01 9.11506295e-01 2.69950986e-01 -1.02929127e+00 -2.70028234e-01 -3.30076516e-01 7.49729395e-01 -7.52454475e-02 -4.16703910e-01 6.64986789e-01 2.79138416e-01 -1.34990478e+00 5.53278625e-01 9.30861056e-01 9.88031447e-01 -7.86456287e-01 1.33644331e+00 5.63309789e-01 -4.71683592e-01 -5.13080042e-03 -6.08422101e-01 -3.98778647e-01 2.72652656e-02 1.01228082e+00 -5.94390869e-01 4.66665030e-01 8.93398643e-01 8.07731867e-01 -5.59893608e-01 1.12851357e+00 -8.49953711e-01 8.95246804e-01 -1.13992013e-01 -5.67232013e-01 -3.33018988e-01 3.24094594e-01 3.35905313e-01 1.45132935e+00 5.64560890e-01 2.23396301e-01 -2.02911317e-01 5.17823517e-01 -6.32788837e-01 3.53151351e-01 -1.31807014e-01 7.91365057e-02 6.65741146e-01 7.90542662e-01 7.37650599e-03 -2.10753992e-01 9.18837264e-03 1.38621700e+00 8.85132492e-01 -2.74834573e-01 -6.17414415e-01 -9.82223392e-01 1.25155091e-01 -3.67749035e-01 -2.71528326e-02 8.26993734e-02 -6.80329323e-01 -1.29259801e+00 4.33242738e-01 -8.59691679e-01 3.38708788e-01 -6.07135117e-01 -1.19831181e+00 8.11860442e-01 -9.25113261e-01 -8.75047147e-01 1.35869294e-01 -8.86236429e-01 -6.28774583e-01 1.43954754e+00 -1.10911417e+00 -8.95395577e-01 -2.82800406e-01 1.63248777e-02 5.19173920e-01 -5.20342767e-01 1.04991806e+00 8.71282935e-01 -9.54347432e-01 1.59702373e+00 8.16010460e-02 3.17156464e-01 9.95715380e-01 -1.38166499e+00 5.68570316e-01 1.09561813e+00 -2.31676966e-01 4.74312901e-01 3.12782556e-01 -9.76574540e-01 -8.02876353e-01 -1.29514015e+00 2.40852165e+00 -7.04768956e-01 2.35980853e-01 -1.54650494e-01 -8.47572923e-01 4.10321176e-01 -8.23729038e-02 7.16331229e-02 2.75710523e-01 3.81838858e-01 2.40026295e-01 1.82603776e-01 -1.31206000e+00 -1.75594077e-01 1.23689091e+00 -4.52770621e-01 -3.13481003e-01 6.23157799e-01 9.15475070e-01 -9.26735401e-01 -8.81731272e-01 3.62681955e-01 2.14590818e-01 -4.04126376e-01 6.62639961e-02 -1.05345488e+00 9.80182588e-01 -1.18021078e-01 -1.41837239e-01 -1.45006335e+00 -3.65832925e-01 -2.90416151e-01 -1.49405763e-01 1.53730798e+00 9.63180423e-01 -4.36552316e-01 4.09591526e-01 4.31033641e-01 -9.44719136e-01 -9.15490866e-01 -1.02104688e+00 -6.04904830e-01 3.81869763e-01 -5.04783869e-01 3.66627723e-01 9.26834524e-01 2.26355389e-01 6.20784909e-02 -3.75787079e-01 -2.48154602e-03 -7.65362456e-02 -5.63988626e-01 2.19094366e-01 -1.01663375e+00 -1.35227799e-01 -2.62338698e-01 -4.41582292e-01 -9.39508379e-01 6.58792108e-02 -1.31699061e+00 1.90950707e-01 -1.35671103e+00 2.28029743e-01 -7.42881656e-01 -2.64995396e-01 5.85445702e-01 -8.53547812e-01 8.89896974e-02 -1.93721373e-02 3.94253023e-02 -6.16932273e-01 4.47473556e-01 9.19010162e-01 -1.79610047e-02 8.81606862e-02 7.96147063e-03 -9.99226809e-01 4.13393795e-01 9.85763013e-01 -7.50534654e-01 4.59291041e-01 -9.29743826e-01 6.25113726e-01 -1.64998963e-01 -8.90520141e-02 -7.37618923e-01 1.78610355e-01 3.82438093e-01 2.74828881e-01 -5.76067567e-01 -6.35454535e-01 -2.95914933e-02 -4.06650037e-01 7.88197339e-01 -3.96332502e-01 3.71514231e-01 7.41182119e-02 -3.57679557e-03 -3.47805977e-01 -1.03039789e+00 5.50047755e-01 -1.65587470e-01 -5.96516192e-01 8.79299864e-02 -8.27400386e-02 5.16673744e-01 5.43111742e-01 2.34910399e-01 -5.23341119e-01 1.36759980e-02 -1.00652766e+00 4.46615189e-01 -7.52367377e-02 4.26548064e-01 6.95947587e-01 -1.18481874e+00 -1.34091103e+00 8.25396404e-02 3.71729940e-01 -1.33921117e-01 1.14716813e-01 8.66057515e-01 -8.47346902e-01 5.06379724e-01 1.25529408e-01 -2.51372486e-01 -1.44517255e+00 -3.06921899e-01 3.96605849e-01 -5.22717535e-01 -3.26857656e-01 1.62963474e+00 -6.82957947e-01 -8.58889639e-01 3.12938988e-01 -2.19178021e-01 -2.64879435e-01 -3.62500459e-01 7.58593380e-01 7.17925906e-01 9.04272735e-01 -1.23205014e-01 -5.12607336e-01 2.41294086e-01 -2.60072947e-01 1.93715215e-01 1.06353664e+00 -6.24312423e-02 -6.23479784e-01 4.12022352e-01 9.70738530e-01 1.11553602e-01 -1.75413191e-01 6.76847622e-02 2.11649999e-01 -3.92927468e-01 5.63410595e-02 -1.53139400e+00 -5.91505229e-01 9.77809429e-01 7.09480286e-01 -2.06951216e-01 9.33921993e-01 -2.00827748e-01 8.35338056e-01 3.53311539e-01 5.75457990e-01 -1.40293920e+00 -3.01610827e-01 1.42317080e+00 1.13690162e+00 -1.58442557e+00 -3.38576138e-01 -5.10576367e-01 -5.07775664e-01 1.08820176e+00 9.20500219e-01 -1.20428815e-01 5.60297906e-01 -5.37490137e-02 -2.03304797e-01 6.92458376e-02 -8.79910409e-01 3.91153097e-01 4.35665756e-01 4.09669071e-01 1.33279634e+00 4.47410017e-01 -1.42997897e+00 1.16864598e+00 -5.44043183e-01 7.71259815e-02 4.33576494e-01 6.87583327e-01 -5.58772027e-01 -1.33467436e+00 1.85827851e-01 7.64517307e-01 -7.62216926e-01 -4.39465702e-01 -3.98333788e-01 1.87336132e-01 3.56724411e-01 1.19559634e+00 1.03551984e-01 -6.03317499e-01 5.37745833e-01 2.16025189e-01 6.89296007e-01 -9.03305590e-01 -9.24847364e-01 -6.25661790e-01 5.83347738e-01 -3.45743358e-01 2.71526635e-01 -5.33356607e-01 -1.51014304e+00 -5.39901078e-01 -6.50119781e-01 3.56990218e-01 6.15536511e-01 9.96149898e-01 4.99494553e-01 6.91432476e-01 4.08920974e-01 4.25196975e-01 -4.41784561e-01 -1.66548002e+00 -4.03530508e-01 3.02969933e-01 2.79281214e-02 -2.35799089e-01 -2.35910982e-01 -3.25972050e-01]	[11.054112434387207, 10.797268867492676]
74509302-ec77-484b-9dee-8cf21a946571	characterizing-out-of-distribution-error-via	2305.15640	null	https://arxiv.org/abs/2305.15640v2	https://arxiv.org/pdf/2305.15640v2.pdf	Characterizing Out-of-Distribution Error via Optimal Transport	Out-of-distribution (OOD) data poses serious challenges in deployed machine learning models, so methods of predicting a model's performance on OOD data without labels are important for machine learning safety. While a number of methods have been proposed by prior work, they often underestimate the actual error, sometimes by a large margin, which greatly impacts their applicability to real tasks. In this work, we identify pseudo-label shift, or the difference between the predicted and true OOD label distributions, as a key indicator to this underestimation. Based on this observation, we introduce a novel method for estimating model performance by leveraging optimal transport theory, Confidence Optimal Transport (COT), and show that it provably provides more robust error estimates in the presence of pseudo-label shift. Additionally, we introduce an empirically-motivated variant of COT, Confidence Optimal Transport with Thresholding (COTT), which applies thresholding to the individual transport costs and further improves the accuracy of COT's error estimates. We evaluate COT and COTT on a variety of standard benchmarks that induce various types of distribution shift -- synthetic, novel subpopulation, and natural -- and show that our approaches significantly outperform existing state-of-the-art methods with an up to 3x lower prediction error.	['Katia Sycara', 'Joseph Campbell', 'Simon Stepputtis', 'Soheil Kolouri', 'Zhenlin Wang', 'Ketong Chen', 'Andrew Shen', 'Runtian Zhai', 'Yilong Qin', 'Yuzhe Lu']	2023-05-25	null	null	null	null	['pseudo-label']	['miscellaneous']	[ 8.29634964e-02 -5.74557632e-02 -4.80611831e-01 -5.58844924e-01 -1.01793873e+00 -4.98183101e-01 5.61642289e-01 4.41317379e-01 -1.86260983e-01 7.35208988e-01 -2.34333754e-01 -4.52895582e-01 -1.06870987e-01 -4.85592782e-01 -8.28140795e-01 -5.90184748e-01 -8.28547254e-02 6.11576080e-01 5.14885783e-01 2.82975316e-01 3.49619806e-01 2.60548741e-01 -1.52741361e+00 1.39210582e-01 1.14601123e+00 1.41704345e+00 -2.28463233e-01 4.25562650e-01 -1.90620601e-01 8.09134066e-01 -1.07760632e+00 -3.53874952e-01 3.78669471e-01 -2.35578164e-01 -5.09908974e-01 -6.05821535e-02 5.20425081e-01 -3.00084502e-01 -1.03854761e-03 8.79516482e-01 3.72251987e-01 -1.85776740e-01 1.28327429e+00 -1.70258665e+00 -5.42293966e-01 3.86866391e-01 -8.24921370e-01 2.20993966e-01 -7.40842074e-02 -1.39785595e-02 7.97194302e-01 -5.90426505e-01 3.17381144e-01 1.29624069e+00 1.00269389e+00 3.33571672e-01 -1.59295440e+00 -7.10605025e-01 -1.08052101e-02 -1.75397456e-01 -1.40611517e+00 -1.28772795e-01 3.73023897e-01 -5.75790703e-01 8.64604712e-01 1.87521696e-01 1.73502371e-01 1.01618993e+00 5.19879520e-01 9.10513818e-01 1.42664230e+00 -5.19023657e-01 3.31768781e-01 3.89353096e-01 2.89018333e-01 4.27024692e-01 3.28288883e-01 1.16998799e-01 -4.55010682e-01 -4.31578755e-01 2.33804986e-01 -1.22754321e-01 -1.13479637e-01 -4.26590085e-01 -1.00981820e+00 6.74955606e-01 2.19306439e-01 -2.30357707e-01 -2.42184401e-02 3.68140846e-01 3.82346779e-01 3.76745403e-01 1.04646862e+00 2.68446565e-01 -7.37713516e-01 -3.60324502e-01 -7.94282794e-01 3.90518457e-01 8.97602677e-01 1.11546850e+00 6.88040555e-01 -2.67109841e-01 -3.24423581e-01 1.05203044e+00 2.72918910e-01 6.15820348e-01 3.94001722e-01 -9.97295439e-01 4.59532171e-01 5.06063282e-01 3.11002284e-01 -8.72297943e-01 -2.04945385e-01 -4.21401173e-01 -6.01472616e-01 4.07744534e-02 7.94302046e-01 6.30213320e-03 -1.03475821e+00 1.72654235e+00 5.14527082e-01 6.56790063e-02 -7.17557445e-02 5.64197183e-01 1.14840880e-01 5.20708382e-01 1.01873241e-01 -1.81345984e-01 9.61030543e-01 -9.47034597e-01 -6.58513248e-01 -1.31380007e-01 1.06486583e+00 -6.47251129e-01 1.35814106e+00 4.67094332e-01 -6.17170811e-01 -3.12804103e-01 -9.14167821e-01 3.08357507e-01 -4.35737103e-01 -1.30372047e-01 4.89160866e-01 8.74873161e-01 -6.71031296e-01 8.00218403e-01 -7.02357352e-01 -2.83155024e-01 5.57364643e-01 9.60415676e-02 4.15870436e-02 -1.96528360e-01 -9.60676253e-01 7.43891954e-01 7.59180412e-02 -1.50601983e-01 -8.14690590e-01 -1.00597644e+00 -5.70812464e-01 -1.59330472e-01 4.31094706e-01 -1.05807140e-01 1.55369055e+00 -5.66264331e-01 -1.24012887e+00 6.73884153e-01 -1.85519531e-02 -4.94302720e-01 9.60550845e-01 -3.41336638e-01 -2.06249774e-01 -4.33340877e-01 2.86116283e-02 6.19844258e-01 9.19428229e-01 -1.43578517e+00 -7.91170716e-01 -3.80149364e-01 -2.10805759e-01 -7.34130144e-02 -4.87371236e-01 -2.86729127e-01 -4.16876167e-01 -6.15533590e-01 6.18118607e-02 -1.09639287e+00 1.10398404e-01 5.56779839e-02 -7.73679256e-01 -5.14820397e-01 8.64584625e-01 -1.47545651e-01 1.48029113e+00 -2.09470820e+00 -4.48571414e-01 1.97107255e-01 5.14109194e-01 -4.90621217e-02 1.11113526e-01 2.26404741e-01 4.18884575e-01 2.95641154e-01 -3.65959078e-01 -4.72582787e-01 3.24320465e-01 2.38336474e-01 -2.97349840e-01 4.39466864e-01 1.54570073e-01 3.70793074e-01 -9.33338881e-01 -4.87002999e-01 -3.85078266e-02 2.69749194e-01 -4.16395903e-01 2.11351126e-01 -4.06029671e-01 1.27169445e-01 -2.62154222e-01 7.91392744e-01 8.00689638e-01 -3.28466624e-01 5.23029640e-02 -1.40511632e-01 1.45868376e-01 2.22085401e-01 -1.07961798e+00 9.49859858e-01 -3.92463267e-01 7.05281198e-01 -5.98598003e-01 -7.42008686e-01 1.01816094e+00 -1.18323669e-01 3.60369205e-01 -5.81286728e-01 6.37095720e-02 4.66196448e-01 -1.05684228e-01 -2.14442506e-01 4.50957179e-01 4.50941138e-02 -1.48069069e-01 5.09317756e-01 -3.89864385e-01 -8.51875022e-02 1.06232196e-01 -9.30339172e-02 1.21870255e+00 4.64767516e-02 5.94814420e-02 -5.11109710e-01 -7.11888000e-02 4.36632261e-02 6.10202849e-01 9.86807048e-01 -4.81246263e-01 4.87149715e-01 8.87870669e-01 -3.32587689e-01 -1.06471062e+00 -1.14606512e+00 -5.56306183e-01 1.00824821e+00 3.33994061e-01 -1.34502575e-01 -9.11661386e-01 -1.33738470e+00 6.26909554e-01 8.77891660e-01 -6.92936957e-01 -2.13553220e-01 -1.84394628e-01 -1.09605396e+00 7.58385718e-01 6.12307787e-01 3.62624466e-01 -5.28149068e-01 -4.05376732e-01 5.16751818e-02 9.38670039e-02 -1.24221385e+00 -5.27127504e-01 4.29634333e-01 -8.58817995e-01 -9.63966012e-01 -7.93750107e-01 -3.71058851e-01 5.91346085e-01 1.31576613e-01 1.15324616e+00 5.19086532e-02 -5.24305031e-02 2.33339909e-02 -2.18447834e-01 -6.84936464e-01 -6.76154554e-01 3.72003764e-01 6.66512400e-02 -1.54053599e-01 5.56565523e-01 -1.23849936e-01 -4.42985624e-01 7.24839687e-01 -7.55052030e-01 -9.97099802e-02 5.38540781e-01 8.34907889e-01 6.90296650e-01 2.10013539e-01 7.25436509e-01 -1.34113312e+00 7.35695422e-01 -6.53167963e-01 -6.63555443e-01 1.51274145e-01 -1.33904314e+00 3.59404415e-01 6.15142465e-01 -7.22845316e-01 -9.83113408e-01 -3.98799628e-01 1.74058795e-01 -5.49673855e-01 -1.87268302e-01 2.11710617e-01 -4.77952473e-02 1.65276825e-01 7.01346219e-01 -1.24532111e-01 -9.44169313e-02 -6.13645971e-01 -4.49226275e-02 1.12218177e+00 1.80961609e-01 -7.78901041e-01 5.36846697e-01 3.35459143e-01 -1.75258573e-02 -5.21411180e-01 -1.32894158e+00 -3.22959989e-01 -4.78176594e-01 -4.71876524e-02 4.68568295e-01 -6.44990087e-01 -3.66234332e-01 7.36525357e-01 -8.74660969e-01 -8.89012337e-01 -1.11836962e-01 4.25349802e-01 -3.76911432e-01 1.82343870e-01 -5.52437127e-01 -8.99587929e-01 -2.93538012e-02 -1.25610793e+00 1.34651589e+00 -5.32777272e-02 -1.38594896e-01 -1.18408310e+00 -1.17564261e-01 8.80016387e-02 3.65757018e-01 4.25833493e-01 1.19872952e+00 -7.74070442e-01 -2.38447785e-01 -2.85657197e-01 -5.55938184e-01 5.66964328e-01 1.09865353e-01 1.60512447e-01 -9.88579273e-01 -3.28395277e-01 -4.27055597e-01 -3.86045635e-01 7.02926755e-01 4.14706588e-01 1.29112864e+00 -3.63423601e-02 -6.69498861e-01 2.77156651e-01 1.31535852e+00 -4.71148826e-03 5.09868205e-01 5.32573402e-01 5.07633269e-01 4.64313149e-01 1.03661537e+00 5.48768401e-01 4.43913549e-01 7.19162703e-01 4.05996531e-01 -3.13063003e-02 -1.80398792e-01 -2.69102752e-01 2.30164975e-01 5.83735883e-01 3.63413244e-01 -6.43192172e-01 -1.05121517e+00 4.46491271e-01 -1.65862036e+00 -3.38432878e-01 -3.12068611e-01 2.55766273e+00 9.52482104e-01 5.83743334e-01 1.34599730e-01 3.83523852e-01 7.27752686e-01 -8.68878365e-02 -8.42688501e-01 -3.80632132e-01 2.53365308e-01 -2.65401810e-01 8.63658249e-01 2.16704220e-01 -9.40060735e-01 8.56863558e-01 6.92762232e+00 1.11785638e+00 -8.71821105e-01 9.08717439e-02 1.03907073e+00 2.81138241e-01 -1.88579604e-01 -1.65398225e-01 -1.14136481e+00 7.59286106e-01 9.17808115e-01 2.20720246e-02 1.39602244e-01 1.00141895e+00 1.02344781e-01 -2.20881820e-01 -1.32321763e+00 7.08474398e-01 -1.10738926e-01 -7.53786564e-01 -4.38824743e-02 3.70069921e-01 9.77935791e-01 4.94509973e-02 1.70375958e-01 4.95387286e-01 3.98580730e-01 -7.75854707e-01 9.04953301e-01 3.23130280e-01 8.64390016e-01 -6.95412338e-01 9.62547243e-01 5.54210484e-01 -9.83808875e-01 -4.43810709e-02 -5.06710947e-01 9.10959989e-02 -1.81296825e-01 1.16545129e+00 -9.77006853e-01 1.94109961e-01 8.74118567e-01 5.43530107e-01 -7.03545511e-01 9.44024026e-01 7.07046827e-03 9.13599432e-01 -5.78138292e-01 -1.35043517e-01 5.78849651e-02 2.09539115e-01 2.65709192e-01 1.24449921e+00 4.08714682e-01 -5.03164232e-01 2.58976296e-02 8.16129327e-01 -3.86601090e-01 -9.89620090e-02 -4.00072455e-01 1.19449601e-01 1.02569354e+00 8.28921914e-01 -6.94633305e-01 -3.06864053e-01 -3.11820507e-01 6.84622526e-01 3.44990134e-01 2.41469249e-01 -1.16895032e+00 -4.56449568e-01 6.08790994e-01 1.70451388e-01 1.15690641e-01 -5.34668146e-03 -2.88717836e-01 -7.75035977e-01 1.46543058e-02 -6.95506394e-01 3.11242908e-01 -4.43135649e-01 -1.56827521e+00 4.21083212e-01 1.13142826e-01 -1.35342824e+00 -4.67701182e-02 -5.39631784e-01 -1.49897248e-01 4.14183646e-01 -1.81451702e+00 -6.64633393e-01 -5.66786349e-01 -2.38602608e-02 6.03156447e-01 9.79840159e-02 4.79994595e-01 4.07974899e-01 -6.55042350e-01 9.61607277e-01 6.01729095e-01 -1.58466980e-01 1.08393919e+00 -1.48582768e+00 4.41002220e-01 2.73128211e-01 -1.32643804e-01 7.18879839e-03 8.67165387e-01 -5.18218040e-01 -1.08193517e+00 -1.44744837e+00 7.17408240e-01 -7.08336055e-01 5.14658034e-01 -3.58506203e-01 -9.01342034e-01 5.49152315e-01 -3.32957745e-01 2.55756915e-01 4.43944424e-01 6.42275661e-02 -4.65560317e-01 -3.20864558e-01 -1.33713448e+00 3.70979428e-01 9.95862544e-01 -1.34413585e-01 -3.23485196e-01 4.82871860e-01 7.94474661e-01 -5.97410560e-01 -1.18225253e+00 5.88859022e-01 7.04477012e-01 -1.18596220e+00 6.77806437e-01 -2.90903449e-01 3.60307336e-01 -6.12304248e-02 -4.00457144e-01 -1.32331979e+00 1.59491420e-01 -2.43458316e-01 -3.08271468e-01 1.43015254e+00 6.64760411e-01 -7.33656466e-01 8.38398993e-01 5.60320795e-01 -4.18888181e-02 -1.13269663e+00 -7.61051416e-01 -1.35461938e+00 1.86609209e-01 -7.75349498e-01 7.83461392e-01 9.92323041e-01 -3.57288092e-01 1.75336953e-02 -3.33061785e-01 1.99204341e-01 9.22279418e-01 -2.29713932e-01 9.41762865e-01 -1.36517322e+00 -1.16292283e-01 -3.61714810e-01 -3.36612582e-01 -1.39827049e+00 1.46052793e-01 -6.18691087e-01 3.07306379e-01 -1.16166031e+00 9.61306468e-02 -9.96059835e-01 -3.25839520e-01 3.98059428e-01 -1.95732385e-01 4.10867274e-01 -1.34686381e-01 5.42294621e-01 -7.70602763e-01 5.92125535e-01 1.00738859e+00 -3.82041596e-02 -2.59153008e-01 1.44079626e-01 -4.54995126e-01 7.52155423e-01 6.70290828e-01 -1.04915214e+00 -3.61459970e-01 -4.95819241e-01 -2.60591805e-02 -3.73948932e-01 1.36892781e-01 -1.04551637e+00 -2.40260720e-01 -9.95460972e-02 2.20391765e-01 -4.77577895e-01 3.46803805e-03 -7.35828042e-01 -3.30900788e-01 4.24585670e-01 -6.08074725e-01 -2.49353591e-02 2.25356981e-01 9.07227397e-01 2.59184111e-02 -1.56159103e-01 7.46075451e-01 4.27633613e-01 -3.05143416e-01 2.54567951e-01 -1.63306594e-01 5.76243579e-01 1.09369493e+00 -1.05383426e-01 -6.10884488e-01 -1.09533019e-01 -9.15027559e-02 2.78710246e-01 4.76383537e-01 3.09780896e-01 2.26883307e-01 -1.30015099e+00 -4.66133952e-01 5.00609092e-02 5.13864815e-01 -3.23963985e-02 -1.59460962e-01 1.07433796e+00 -4.66526628e-01 2.65988171e-01 5.33172011e-01 -1.13180888e+00 -9.60745096e-01 2.73038834e-01 3.54087502e-01 -3.97589952e-01 -4.10125136e-01 6.48303449e-01 1.92748576e-01 -6.72075093e-01 5.42791665e-01 -6.56755388e-01 2.72954732e-01 -2.57385135e-01 2.32963234e-01 5.61474323e-01 1.86387718e-01 -2.10808828e-01 -1.12570435e-01 4.15291131e-01 -1.89316228e-01 3.01067233e-01 1.05361772e+00 -2.74193615e-01 3.11455011e-01 8.65825117e-01 1.18097949e+00 -1.12726204e-01 -1.58767688e+00 -3.64512473e-01 3.99746776e-01 -8.32970142e-01 1.26552179e-01 -8.79287779e-01 -7.90777087e-01 8.84462655e-01 7.65706122e-01 7.28711724e-01 8.21660697e-01 4.90090176e-02 9.07021701e-01 3.89174104e-01 3.50576371e-01 -1.19448423e+00 2.27346137e-01 2.47986883e-01 3.96865010e-01 -1.53818643e+00 -4.07541096e-02 -4.17914897e-01 -6.03356123e-01 7.99555779e-01 7.57275760e-01 2.49558687e-01 7.65875161e-01 5.23484826e-01 2.06173345e-01 8.75804499e-02 -9.26524460e-01 1.65134892e-01 1.00201942e-01 6.61405742e-01 3.09038341e-01 -2.35802084e-02 1.17421057e-02 4.00834441e-01 -1.19267497e-02 -5.52838780e-02 3.71335059e-01 9.45645809e-01 -4.64020133e-01 -9.13048983e-01 -2.94739485e-01 9.02647197e-01 -3.98936242e-01 1.46866813e-02 -2.01787904e-01 1.03295553e+00 1.49218785e-02 8.35469544e-01 2.54491627e-01 -4.96588260e-01 4.80678171e-01 -2.03011762e-02 2.37500682e-01 -3.01955193e-01 -1.21786289e-01 1.22247018e-01 1.03651173e-01 -3.79075348e-01 -2.30421096e-01 -5.67278504e-01 -1.20280564e+00 -6.21695280e-01 -8.22178841e-01 5.23172282e-02 7.07818925e-01 9.98188555e-01 3.94176036e-01 5.26892543e-01 7.20291674e-01 -5.67882419e-01 -1.08602917e+00 -1.09904289e+00 -8.44545841e-01 5.54918468e-01 2.26168975e-01 -1.05108953e+00 -8.79860640e-01 -8.33031014e-02]	[9.010170936584473, 3.847087860107422]
92e50c3f-4fcc-460d-9763-d98b94c1c905	recurrent-neural-networks-to-correct	1608.03440	null	http://arxiv.org/abs/1608.03440v3	http://arxiv.org/pdf/1608.03440v3.pdf	Recurrent Neural Networks to Correct Satellite Image Classification Maps	While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fine object outlining is of paramount importance. Different iterative enhancement algorithms have been presented in the literature to progressively improve the coarse CNN outputs, seeking to sharpen object boundaries around real image edges. However, one must carefully design, choose and tune such algorithms. Instead, our goal is to directly learn the iterative process itself. For this, we formulate a generic iterative enhancement process inspired from partial differential equations, and observe that it can be expressed as a recurrent neural network (RNN). Consequently, we train such a network from manually labeled data for our enhancement task. In a series of experiments we show that our RNN effectively learns an iterative process that significantly improves the quality of satellite image classification maps.	['Pierre Alliez', 'Emmanuel Maggiori', 'Yuliya Tarabalka', 'Guillaume Charpiat']	2016-08-11	null	null	null	null	['satellite-image-classification', 'image-categorization']	['computer-vision', 'computer-vision']	[ 5.68050504e-01 1.68794498e-01 1.17105395e-01 -4.43018585e-01 -3.42742443e-01 -4.99924272e-01 5.29710591e-01 7.60144889e-02 -6.41249955e-01 3.65602046e-01 -3.72457206e-02 -3.10493916e-01 -3.03950280e-01 -8.63241017e-01 -5.85948050e-01 -7.16632545e-01 2.74582896e-02 6.50225282e-02 4.44511920e-02 -2.15371117e-01 1.59267336e-01 7.31628418e-01 -1.37416327e+00 5.60154952e-02 8.24410677e-01 1.09944105e+00 2.13839665e-01 6.15787029e-01 -1.23614214e-01 1.01592755e+00 -3.47238809e-01 -2.12898567e-01 2.98624098e-01 -4.74550724e-01 -1.20742905e+00 7.21110582e-01 1.88826323e-01 -2.16796622e-01 -2.88559824e-01 1.34454763e+00 1.30329400e-01 2.24534273e-01 7.06439555e-01 -8.83511901e-01 -7.35674143e-01 5.73908210e-01 -5.33564329e-01 2.34656051e-01 -4.32157248e-01 -1.38293967e-01 1.01749182e+00 -8.01041603e-01 4.12254006e-01 6.47286952e-01 9.22105610e-01 3.41201127e-01 -1.25550699e+00 -1.25476733e-01 3.24529499e-01 5.31515107e-03 -1.57449424e+00 -1.81982219e-01 8.70238543e-01 -4.64444131e-01 3.01516742e-01 1.75299689e-01 5.69127977e-01 6.62503362e-01 -2.50678003e-01 8.25513244e-01 9.59178984e-01 -3.91921848e-01 2.80166805e-01 2.05613956e-01 5.82879782e-02 4.55246955e-01 -5.46482317e-02 4.58091944e-02 9.63662006e-03 3.19259346e-01 1.06514037e+00 1.44736752e-01 -5.55018008e-01 -3.90810430e-01 -8.59530747e-01 7.75683284e-01 1.04770148e+00 6.49246693e-01 -5.14402509e-01 1.46582380e-01 2.20907882e-01 1.63715422e-01 6.04882419e-01 6.80334032e-01 -2.21430615e-01 3.03095460e-01 -1.19255233e+00 -3.73647250e-02 4.15394634e-01 4.64163393e-01 8.60083997e-01 -4.13262844e-02 6.15793094e-02 7.88701773e-01 -8.29333439e-02 -8.79725218e-02 3.17029148e-01 -1.01367950e+00 -1.74704008e-02 8.38000417e-01 1.04321346e-01 -1.02368653e+00 -4.84694988e-01 -9.79494631e-01 -1.37415564e+00 4.14866000e-01 3.98263782e-01 -1.20483525e-01 -9.61646557e-01 1.63799930e+00 1.95444256e-01 1.36083439e-01 1.20770469e-01 1.13896894e+00 4.37512100e-01 6.90904737e-01 2.32098445e-01 2.12066799e-01 1.07056391e+00 -8.19054067e-01 -5.15128493e-01 -3.69195551e-01 5.57971478e-01 -3.61455262e-01 8.26993585e-01 2.92623013e-01 -9.30473506e-01 -6.32869184e-01 -9.83172059e-01 -7.35273063e-02 -5.40797889e-01 4.00685459e-01 5.32676578e-01 2.42719322e-01 -1.26794410e+00 9.08741593e-01 -7.76126683e-01 -3.02360624e-01 4.98881996e-01 3.49267095e-01 -2.66715556e-01 2.44782537e-01 -1.14822268e+00 9.72465217e-01 4.80168968e-01 7.25214541e-01 -6.79533243e-01 -5.22756636e-01 -7.50633359e-01 3.16647917e-01 2.83109546e-01 -5.13376176e-01 1.22803533e+00 -1.52201521e+00 -1.26401722e+00 1.06936669e+00 2.23478809e-01 -6.73903763e-01 5.35791934e-01 -1.72944114e-01 -4.31681909e-02 1.39999673e-01 -2.59507865e-01 8.62696409e-01 1.01358163e+00 -1.42102051e+00 -8.46268654e-01 -2.41445273e-01 3.28086108e-01 1.95520788e-01 -3.72636586e-01 -3.96576561e-02 -1.64622054e-01 -8.70773911e-01 2.33112395e-01 -6.34112000e-01 -6.10522866e-01 3.11493784e-01 -1.76791653e-01 -4.95645478e-02 7.23048151e-01 -6.13473952e-01 1.01458454e+00 -2.14323759e+00 3.63830179e-01 2.54861176e-01 2.57479429e-01 3.19886327e-01 -1.15245640e-01 -3.07315495e-02 -2.32075840e-01 2.25985155e-01 -8.06935966e-01 -2.21798524e-01 -1.46416411e-01 1.99452519e-01 -3.51958573e-01 4.64965791e-01 6.03676021e-01 1.08812380e+00 -7.73239493e-01 -2.15970516e-01 1.96216568e-01 8.27939630e-01 -3.76220316e-01 1.80036530e-01 -9.18966904e-02 4.41709608e-01 -3.45696807e-01 3.21410984e-01 5.70195436e-01 -5.91775239e-01 3.29237878e-02 -3.84453386e-01 -3.57629508e-01 -8.76968727e-02 -1.15129864e+00 1.44408166e+00 -3.83997530e-01 8.83794725e-01 3.06353062e-01 -1.50503767e+00 8.91088665e-01 1.73295945e-01 6.33786738e-01 -4.96187568e-01 3.68379533e-01 5.15784584e-02 -2.28517830e-01 -2.03962505e-01 6.95521057e-01 -7.11141750e-02 2.69602686e-01 4.13165420e-01 -5.06832413e-02 -7.27132112e-02 -6.40267953e-02 -1.37486801e-01 7.82117248e-01 1.34443581e-01 2.98775584e-01 -3.95761222e-01 6.41651511e-01 2.01515853e-01 2.71198183e-01 5.61414838e-01 -1.66442946e-01 8.14938903e-01 1.27011105e-01 -6.67603672e-01 -1.13688672e+00 -6.68281734e-01 -3.48594129e-01 9.56436574e-01 3.17239106e-01 6.92022592e-02 -9.71274555e-01 -6.22649550e-01 -3.26686621e-01 1.96067303e-01 -7.14864850e-01 -1.71916530e-01 -6.09486520e-01 -8.26772988e-01 3.99590105e-01 6.35305107e-01 9.80144918e-01 -1.10656059e+00 -9.11675215e-01 4.60918546e-01 -1.68091834e-01 -1.05236864e+00 -3.19393367e-01 5.49578726e-01 -7.96299219e-01 -9.92017746e-01 -1.02420235e+00 -9.46617961e-01 1.01023209e+00 2.38049999e-01 1.07457328e+00 2.88518935e-01 -2.89100498e-01 2.52912432e-01 -3.26920062e-01 6.34100884e-02 -2.65320271e-01 4.12500560e-01 -3.44502777e-01 2.62266725e-01 1.72179773e-01 -5.23749411e-01 -6.41859293e-01 2.54234701e-01 -1.37061274e+00 1.96058050e-01 7.96202183e-01 8.48928750e-01 4.51020837e-01 4.46813583e-01 2.60215729e-01 -7.00508714e-01 4.32518810e-01 -7.62151778e-02 -6.53854132e-01 4.87389147e-01 -4.24131334e-01 3.56217086e-01 4.77109343e-01 -2.90244460e-01 -1.01143205e+00 3.38966161e-01 -4.87560630e-01 -6.28971681e-02 -4.59704131e-01 7.30418801e-01 1.69347659e-01 -4.79874104e-01 6.29888833e-01 2.88648874e-01 -1.67722374e-01 -4.10651267e-01 3.63599718e-01 7.66963720e-01 8.69299889e-01 -2.77424723e-01 7.71627784e-01 5.73911130e-01 -7.36214668e-02 -8.00083995e-01 -1.02032220e+00 -3.99940461e-01 -8.74561667e-01 -4.07826632e-01 8.98748100e-01 -6.21319652e-01 -6.37682736e-01 4.54552591e-01 -9.71878290e-01 -6.87782347e-01 -4.56014544e-01 8.75611678e-02 -4.56675887e-01 1.77792192e-01 -5.96082449e-01 -6.47258580e-01 -2.12771118e-01 -1.05061758e+00 9.53353226e-01 3.90235662e-01 -7.23360851e-03 -1.19189966e+00 -1.34912312e-01 -2.32863024e-01 6.03989244e-01 2.58033991e-01 6.84659600e-01 -1.14100039e-01 -4.74713653e-01 -4.34566215e-02 -5.52110851e-01 5.99056244e-01 1.76443562e-01 -2.01733951e-02 -1.01720560e+00 -2.65960693e-02 1.56760290e-01 -1.80232003e-01 9.79350030e-01 4.87486660e-01 1.47213185e+00 -2.76276410e-01 -1.49210095e-01 7.61468709e-01 1.59335339e+00 -2.37030741e-02 5.46034038e-01 4.66668308e-01 4.61079299e-01 8.94083261e-01 1.79738387e-01 1.68525472e-01 1.11730963e-01 4.84745055e-01 5.46280324e-01 -6.22988582e-01 -9.46552027e-03 4.29875515e-02 3.19639556e-02 3.15939695e-01 -1.85271367e-01 2.09382195e-02 -9.99176145e-01 6.41400933e-01 -1.77007401e+00 -7.54420996e-01 1.34376824e-01 1.88412344e+00 7.36212969e-01 -7.11001130e-03 -1.19780257e-01 4.99274075e-01 8.09157610e-01 1.87208831e-01 -4.19425339e-01 -2.51261541e-03 -2.23178580e-01 1.42374560e-01 6.44853473e-01 4.97757256e-01 -1.48926103e+00 9.15068328e-01 6.06038094e+00 4.82690901e-01 -1.45145726e+00 -2.86217690e-01 1.02686381e+00 5.89652061e-01 -4.09979634e-02 -3.02270532e-01 -5.02732396e-01 4.45420220e-02 3.83903265e-01 1.60242110e-01 3.84150118e-01 8.62423122e-01 1.49993569e-01 3.50225829e-02 -9.05680358e-01 9.77965653e-01 -1.69522882e-01 -1.31264305e+00 3.09733506e-02 -1.29638821e-01 8.25340867e-01 -1.60190076e-01 3.05521011e-01 1.23127818e-01 2.95888633e-01 -1.18226528e+00 7.26103306e-01 4.52296406e-01 4.62979704e-01 -7.07370102e-01 6.75684273e-01 3.34030658e-01 -1.26637721e+00 -1.03371508e-01 -4.11076128e-01 -1.74210817e-02 2.01198637e-01 6.73499227e-01 -3.02926034e-01 3.68871391e-01 6.81457043e-01 7.95521796e-01 -6.20710909e-01 1.19464588e+00 -2.77591825e-01 3.55106086e-01 -2.25243628e-01 2.19345883e-01 6.84044302e-01 -4.19716179e-01 2.30618194e-01 1.09795976e+00 2.62281507e-01 4.24832195e-01 -6.51651472e-02 1.07005703e+00 -2.84399897e-01 -1.18274741e-01 -4.39472824e-01 -1.17919661e-01 -1.52751744e-01 1.54815793e+00 -1.15187669e+00 -2.37192079e-01 -2.08244726e-01 1.20947897e+00 5.23055077e-01 6.32595360e-01 -7.51784027e-01 -3.74057740e-01 7.34075487e-01 -8.10725242e-02 3.39339137e-01 -3.07253718e-01 -3.88763785e-01 -1.06009948e+00 -1.83415025e-01 -6.65382624e-01 1.74259543e-01 -8.07360291e-01 -1.07735193e+00 9.91135895e-01 -3.83244127e-01 -1.02771401e+00 6.79332472e-04 -7.85187781e-01 -4.28187668e-01 5.90574622e-01 -1.71438193e+00 -9.30788100e-01 -6.84207261e-01 3.10355753e-01 4.66160208e-01 5.35461128e-01 5.76417685e-01 4.09483522e-01 -4.79924679e-01 8.40192512e-02 1.01916213e-02 3.31669837e-01 2.40418732e-01 -1.34719658e+00 3.03384006e-01 1.07750165e+00 2.51246303e-01 2.89185524e-01 6.56675339e-01 -1.77202448e-01 -7.26547301e-01 -1.38120008e+00 8.81442249e-01 4.28536758e-02 5.35023749e-01 -1.64416313e-01 -1.15447998e+00 6.05577469e-01 2.10374266e-01 1.18877374e-01 -3.10641192e-02 -2.02912390e-01 6.89898580e-02 6.31074887e-03 -8.52831900e-01 5.60808659e-01 9.48976576e-01 -6.45182669e-01 -3.80349904e-01 1.96156114e-01 2.03541309e-01 -3.38397682e-01 -7.06228673e-01 6.55278623e-01 1.91756457e-01 -8.53699148e-01 9.85463679e-01 -5.10410130e-01 4.98021334e-01 -4.73238677e-01 1.87039539e-01 -1.38494134e+00 -3.89307261e-01 -3.54719371e-01 2.58928388e-01 9.95954931e-01 3.62326056e-01 -3.32110941e-01 8.49964857e-01 5.24249494e-01 -1.19449310e-01 -6.80121422e-01 -3.32236260e-01 -5.33332646e-01 -6.07943423e-02 -3.74748558e-01 4.24412489e-01 8.78062189e-01 -2.70271659e-01 1.45486951e-01 -3.07200640e-01 3.85023296e-01 5.29388249e-01 1.85240969e-01 3.47935170e-01 -1.24992681e+00 -7.19989613e-02 -8.09405267e-01 -3.21863919e-01 -1.48115659e+00 6.29998595e-02 -7.73586631e-01 4.27305758e-01 -1.55994201e+00 8.86158943e-02 -5.11166632e-01 -2.18386173e-01 4.57834810e-01 -2.42532939e-01 5.96957505e-01 -2.09985636e-02 1.26509443e-01 -4.72069800e-01 5.30769229e-01 1.08917558e+00 -4.11734134e-01 -1.23037711e-01 1.21271864e-01 -6.33097589e-01 7.08930910e-01 8.47908795e-01 -2.67458230e-01 -1.50179133e-01 -6.83557570e-01 4.41695869e-01 -4.27513152e-01 7.42603600e-01 -1.10570824e+00 4.93021369e-01 1.37266129e-01 3.79114240e-01 -3.39480996e-01 -7.80704394e-02 -1.01434684e+00 1.05144657e-01 4.23515856e-01 -6.59699976e-01 -1.31359771e-01 1.69972703e-02 2.29549572e-01 -5.78501821e-01 -5.52475095e-01 9.76063430e-01 -1.48517892e-01 -1.00215471e+00 4.35429722e-01 -5.64698637e-01 -1.75136834e-01 8.24043453e-01 -2.29398862e-01 9.36864242e-02 -4.02153730e-01 -1.03854585e+00 3.06849405e-02 3.71274978e-01 8.76336247e-02 4.62136954e-01 -1.09297442e+00 -4.47037399e-01 5.69873527e-02 -5.54638728e-02 2.98461407e-01 1.33517131e-01 8.24802577e-01 -6.45954669e-01 3.16240370e-01 -1.66714966e-01 -6.45538270e-01 -8.94305468e-01 4.50692713e-01 8.63711655e-01 -2.31130242e-01 -7.14937687e-01 8.93128932e-01 3.78914207e-01 -2.90751159e-01 4.27287430e-01 -6.20344996e-01 -4.22533482e-01 -1.06872339e-02 4.32117373e-01 1.27170727e-01 2.80606057e-02 -6.44309938e-01 1.95613354e-02 6.95739985e-01 2.53373682e-01 4.93843630e-02 1.53656030e+00 -4.03406709e-01 -1.24701187e-01 4.86848019e-02 1.14034677e+00 -6.87664151e-01 -1.63481486e+00 -3.84478480e-01 3.30103040e-01 1.35971988e-02 4.21117783e-01 -3.79676372e-01 -1.29182470e+00 9.61130381e-01 6.12655282e-01 5.69648981e-01 1.45430577e+00 -1.40973926e-01 5.15389025e-01 3.86655897e-01 1.13630734e-01 -9.58418012e-01 -1.73279736e-02 6.06976569e-01 7.23240137e-01 -1.31800628e+00 -3.52685660e-01 -2.84505755e-01 -4.93075401e-01 1.27184069e+00 3.34702045e-01 -2.60436118e-01 6.69689000e-01 3.38382244e-01 9.93337408e-02 -2.70961136e-01 -5.68973050e-02 -6.35009468e-01 3.37810218e-01 3.55110824e-01 3.66077274e-01 -2.81909376e-01 5.76118715e-02 2.77577788e-01 4.51983586e-02 -1.57619826e-02 2.11387455e-01 7.98751593e-01 -5.79237342e-01 -8.24984193e-01 -2.46070683e-01 1.16472825e-01 -4.16935861e-01 -1.82641651e-02 -4.85800564e-01 7.59743333e-01 1.07247718e-01 5.58132708e-01 1.92744523e-01 -7.36667886e-02 1.39204487e-01 -5.57145029e-02 3.31005216e-01 -2.78414130e-01 -6.63271785e-01 -2.38823265e-01 -4.12303686e-01 -3.28536749e-01 -7.77210116e-01 -3.30708027e-01 -1.17322993e+00 6.60895854e-02 -3.72565269e-01 2.85436422e-01 7.05551863e-01 1.05174029e+00 -4.24029529e-02 7.44455040e-01 6.86145425e-01 -9.49883461e-01 -4.35950994e-01 -7.22554982e-01 -5.42158425e-01 3.64322394e-01 4.42420125e-01 -4.85542417e-01 -4.12873566e-01 4.25340086e-01]	[9.635834693908691, 0.5762585997581482]
231c48db-d989-4f4f-bafc-89cbd784acdb	htnet-human-topology-aware-network-for-3d	2302.09790	null	https://arxiv.org/abs/2302.09790v1	https://arxiv.org/pdf/2302.09790v1.pdf	HTNet: Human Topology Aware Network for 3D Human Pose Estimation	3D human pose estimation errors would propagate along the human body topology and accumulate at the end joints of limbs. Inspired by the backtracking mechanism in automatic control systems, we design an Intra-Part Constraint module that utilizes the parent nodes as the reference to build topological constraints for end joints at the part level. Further considering the hierarchy of the human topology, joint-level and body-level dependencies are captured via graph convolutional networks and self-attentions, respectively. Based on these designs, we propose a novel Human Topology aware Network (HTNet), which adopts a channel-split progressive strategy to sequentially learn the structural priors of the human topology from multiple semantic levels: joint, part, and body. Extensive experiments show that the proposed method improves the estimation accuracy by 18.7% on the end joints of limbs and achieves state-of-the-art results on Human3.6M and MPI-INF-3DHP datasets. Code is available at https://github.com/vefalun/HTNet.	['Miaoju Ban', 'Jianbing Wu', 'Wenhao Li', 'Runwei Ding', 'Hong Liu', 'Jialun Cai']	2023-02-20	null	null	null	null	['3d-human-pose-estimation']	['computer-vision']	[-3.84950370e-01 4.58520323e-01 -3.09748828e-01 -2.40529776e-01 1.01856053e-01 -4.01077271e-02 2.26662338e-01 -4.36894506e-01 -1.82239369e-01 4.90685135e-01 3.99121821e-01 4.30244297e-01 8.45866799e-02 -6.01507187e-01 -8.47568214e-01 -1.47702590e-01 -3.03782016e-01 8.07880223e-01 6.22530699e-01 -3.63061905e-01 -1.74705535e-01 3.11681002e-01 -1.01054561e+00 -1.12934172e-01 6.06022894e-01 7.86179066e-01 -3.91235612e-02 5.18544376e-01 3.14410895e-01 7.88405716e-01 -3.56552631e-01 -5.86762309e-01 2.70552576e-01 -3.31486404e-01 -8.81506264e-01 3.72314334e-01 3.84655267e-01 -4.07473534e-01 -8.09157968e-01 8.04760814e-01 7.14616120e-01 5.30902185e-02 3.14802766e-01 -1.28224444e+00 -1.77301958e-01 5.00809610e-01 -8.57149363e-01 -2.43849799e-01 4.03547734e-01 4.07334507e-01 7.73326933e-01 -6.61160409e-01 1.01025188e+00 1.46904016e+00 9.86351252e-01 5.79439521e-01 -9.04046953e-01 -6.15168691e-01 3.69693339e-01 3.44951928e-01 -1.43357754e+00 -1.37732521e-01 1.07642066e+00 -4.87721950e-01 6.48140490e-01 -1.54234052e-01 1.14577913e+00 1.13123822e+00 4.91905242e-01 8.27714503e-01 5.87714970e-01 -6.15352839e-02 -2.28525057e-01 -8.45698595e-01 -1.84171796e-01 1.29833484e+00 1.91142768e-01 2.54135542e-02 -8.48843396e-01 1.36064410e-01 1.34024394e+00 -3.12921435e-01 -1.05560169e-01 -7.72013903e-01 -1.32031059e+00 4.93941247e-01 8.41138661e-01 -1.99360132e-01 -3.61468464e-01 7.82153428e-01 5.25236070e-01 -2.35313565e-01 2.38778636e-01 -1.94863468e-01 -6.57771885e-01 7.48391375e-02 -7.26040304e-01 4.30981725e-01 7.09741831e-01 1.34698164e+00 3.55071157e-01 -1.76903173e-01 -2.21843988e-01 7.17921555e-01 6.91565752e-01 3.66170555e-01 -7.07828104e-02 -1.23704875e+00 5.57800889e-01 6.91263437e-01 -1.55495346e-01 -9.89839137e-01 -9.05298293e-01 -7.65562057e-01 -1.05389392e+00 -2.83164959e-02 4.57272798e-01 -2.04640701e-01 -1.29766345e+00 1.80896747e+00 8.85051191e-01 3.05696782e-02 -7.95607269e-01 1.47396922e+00 6.47905231e-01 1.52536795e-01 2.78806865e-01 3.90772969e-01 1.60076690e+00 -1.42024291e+00 -5.13811588e-01 -1.51047736e-01 3.02276433e-01 -4.87453520e-01 7.98734844e-01 2.26504028e-01 -1.20154011e+00 -8.59340549e-01 -1.01026964e+00 -4.48575288e-01 1.78657427e-01 2.62331456e-01 4.83428955e-01 6.12319224e-02 -6.53994799e-01 6.30707383e-01 -1.27642608e+00 -3.84518087e-01 2.86423564e-01 3.21785092e-01 -3.57040972e-01 1.11534223e-02 -1.26958001e+00 8.74828517e-01 1.34884417e-01 6.60356700e-01 -8.49495828e-01 -5.76537132e-01 -8.95667255e-01 -3.08429301e-01 4.21418130e-01 -1.49448717e+00 1.06415224e+00 -4.50298458e-01 -1.80246162e+00 8.68796170e-01 2.61712790e-01 -2.11728141e-01 1.12506974e+00 -6.63659990e-01 4.02508900e-02 3.48074853e-01 6.97228462e-02 9.38741863e-01 6.80504382e-01 -9.90251720e-01 -2.71633983e-01 -5.06032526e-01 -1.75227046e-01 4.79437023e-01 3.84382844e-01 -3.03954512e-01 -1.34573019e+00 -7.56295562e-01 2.95761436e-01 -1.23983550e+00 -3.78562480e-01 6.49210572e-01 -9.50017333e-01 -2.56397277e-01 4.53953087e-01 -1.02665257e+00 1.26281452e+00 -1.63553178e+00 8.13400567e-01 4.63325143e-01 4.06809211e-01 -1.24368705e-01 2.48077139e-02 2.12241262e-01 3.76800537e-01 -3.44989359e-01 -3.12638700e-01 -3.39907974e-01 2.09485739e-01 3.72512072e-01 5.42902946e-01 7.64380097e-01 -7.01190606e-02 1.10528338e+00 -6.64005399e-01 -9.69743073e-01 4.13531482e-01 7.56981611e-01 -6.94561541e-01 1.26049757e-01 -2.73758411e-01 7.75794268e-01 -5.88810623e-01 7.05996394e-01 4.92600501e-01 -4.03402925e-01 4.40080971e-01 -4.65741992e-01 1.50994956e-01 8.48778784e-02 -1.12824476e+00 2.44894099e+00 -4.60232422e-03 -3.82828675e-02 3.43503833e-01 -6.25962913e-01 5.67066669e-01 2.15693504e-01 7.12678373e-01 -4.33318764e-01 2.92905033e-01 -1.15470722e-01 1.06885687e-01 -3.51031721e-01 4.31200676e-03 3.15655887e-01 -1.88504443e-01 -2.18591511e-01 2.34665915e-01 1.26067191e-01 1.43998832e-01 1.69812236e-02 1.02227640e+00 9.76898789e-01 9.96474773e-02 -3.38563323e-01 5.17946124e-01 -3.94616239e-02 9.88934278e-01 7.61048943e-02 -4.35683697e-01 6.64940357e-01 5.27342439e-01 -6.10630989e-01 -1.09126246e+00 -1.45452797e+00 1.03632070e-01 1.12911606e+00 4.62406397e-01 -5.46996772e-01 -8.73015046e-01 -4.97625500e-01 3.51532280e-01 -5.64129353e-02 -6.27061963e-01 -6.91660941e-02 -1.11582363e+00 -2.31314063e-01 4.80610967e-01 8.59704137e-01 8.10916245e-01 -8.99613082e-01 -8.31982493e-01 4.16090697e-01 -4.33828026e-01 -1.14651430e+00 -7.15971947e-01 -2.52709955e-01 -8.56425226e-01 -1.32232594e+00 -9.20743227e-01 -7.02751219e-01 5.98587155e-01 -6.63800418e-01 1.25610209e+00 3.94593358e-01 -4.63797033e-01 9.68254879e-02 -1.82162791e-01 2.51981556e-01 1.21835992e-01 3.94304395e-01 -4.21644710e-02 -3.81565690e-01 -3.16029698e-01 -7.14214504e-01 -1.10307431e+00 7.23990262e-01 -2.07629934e-01 4.69178557e-01 6.50581062e-01 6.16232634e-01 7.99958706e-01 -2.74411708e-01 2.70482600e-02 -5.80809295e-01 -8.11971128e-02 -2.45728657e-01 -4.69841540e-01 1.14557981e-01 -1.14566840e-01 -4.58948500e-02 3.60384047e-01 -3.50972772e-01 -1.03119814e+00 5.33320308e-01 -2.20747784e-01 -4.90363836e-01 -8.77531543e-02 1.52930632e-01 -3.54036003e-01 -3.79850976e-02 2.55979300e-01 -1.31662220e-01 4.61212359e-02 -7.26300299e-01 5.56441963e-01 -2.87817661e-02 8.66481662e-01 -9.60093319e-01 7.73513317e-01 4.72090214e-01 4.04926598e-01 -5.81430614e-01 -7.12793410e-01 -3.04282308e-01 -1.13121569e+00 -6.34727299e-01 1.19464231e+00 -1.00694108e+00 -8.47436905e-01 7.58776903e-01 -1.19936299e+00 -6.48240387e-01 -4.49324995e-02 4.65526134e-01 -7.91810691e-01 5.52298725e-01 -1.11090529e+00 -2.48029381e-01 -4.66721892e-01 -9.32353795e-01 1.27691114e+00 3.32809687e-02 -4.76755649e-01 -7.79415607e-01 -1.38174975e-02 4.50360328e-01 -7.44940937e-02 6.43332601e-01 6.39532447e-01 1.05173334e-01 -6.56222522e-01 9.41446573e-02 2.41250079e-03 -7.46616647e-02 -2.74375468e-01 -6.44414723e-02 -2.19480559e-01 -2.19260767e-01 -6.71356797e-01 -2.37988770e-01 5.78722537e-01 6.11122727e-01 9.99253273e-01 -9.93628129e-02 -4.15500522e-01 9.11862791e-01 1.01407468e+00 -6.51114702e-01 7.13024676e-01 1.10867761e-01 1.19299066e+00 7.48833835e-01 4.70210552e-01 6.57687068e-01 7.68553674e-01 9.15677130e-01 4.30000931e-01 -5.35773039e-02 -7.59937942e-01 -7.35678554e-01 1.13078147e-01 1.01190817e+00 -4.45560336e-01 -3.93073745e-02 -9.81345952e-01 4.37571019e-01 -1.94430017e+00 -5.33317983e-01 -2.98544019e-01 1.79818463e+00 8.72073829e-01 3.19414765e-01 4.35927629e-01 -3.29091728e-01 9.33355510e-01 1.13763072e-01 -7.57848084e-01 2.35599577e-01 2.95573235e-01 -2.27352977e-02 5.18838227e-01 4.19743717e-01 -1.14649498e+00 1.12551689e+00 5.46791363e+00 5.34790099e-01 -6.41700029e-01 3.22477743e-02 1.60394862e-01 -1.28916711e-01 2.15214804e-01 -1.34693801e-01 -6.91110194e-01 5.58454633e-01 2.56254584e-01 3.87823969e-01 1.95868075e-01 6.46164715e-01 2.12613225e-01 4.49620299e-02 -9.53258634e-01 6.86433017e-01 -3.28695744e-01 -8.37628543e-01 -9.35009271e-02 3.72460112e-02 6.12732708e-01 1.63056165e-01 -3.22190076e-01 -2.20731962e-02 2.75319010e-01 -6.80904269e-01 1.12723720e+00 7.83813775e-01 7.02043712e-01 -7.52712131e-01 4.31889057e-01 3.15595120e-01 -1.76923597e+00 3.06062937e-01 -2.19584286e-01 -1.12339906e-01 4.80554134e-01 5.03385723e-01 -2.04639196e-01 6.18356049e-01 8.68522048e-01 7.65231907e-01 -4.12193060e-01 1.02534628e+00 -7.93431461e-01 4.34263319e-01 -6.17272615e-01 3.34098577e-01 -2.64967859e-01 2.90288087e-02 5.08842468e-01 9.39256430e-01 -1.84205696e-01 1.04810238e-01 4.73418653e-01 8.50276291e-01 -1.62087843e-01 -1.90810934e-01 3.37536409e-02 4.53787059e-01 3.80609572e-01 1.18225527e+00 -7.17055500e-01 -2.09491536e-01 -1.85436264e-01 1.26913118e+00 3.88929904e-01 2.73712963e-01 -1.20580852e+00 -2.96758205e-01 6.72722459e-01 4.15525943e-01 2.52601743e-01 -6.10760152e-01 -2.44996190e-01 -1.12756538e+00 3.51061791e-01 -5.58271945e-01 4.76864100e-01 -7.23424673e-01 -1.22063625e+00 1.51948899e-01 8.48363340e-02 -9.87833202e-01 3.48687842e-02 -3.43847930e-01 -3.19058597e-01 5.41711330e-01 -1.01135790e+00 -1.56886101e+00 -3.99540722e-01 6.49499714e-01 4.50665861e-01 5.40194690e-01 3.53181779e-01 4.09004539e-01 -5.97843587e-01 5.55309176e-01 -6.95948660e-01 6.49456382e-01 5.10774672e-01 -9.95657563e-01 7.23174751e-01 6.68125749e-01 -2.88124382e-01 5.16196430e-01 4.18075919e-01 -1.11104119e+00 -1.34466469e+00 -1.02252269e+00 6.86856389e-01 -3.50632787e-01 4.72859383e-01 -3.95241499e-01 -5.50648987e-01 8.33637416e-01 -5.02188429e-02 2.12665334e-01 1.47312567e-01 1.05294198e-01 -3.00123483e-01 5.99425621e-02 -9.49718595e-01 5.75347245e-01 1.82754529e+00 -6.90517053e-02 -6.72049701e-01 2.99223065e-01 7.26287842e-01 -1.08141279e+00 -1.26502347e+00 7.06712842e-01 9.65252340e-01 -7.09926009e-01 1.19722486e+00 -4.17906344e-01 4.70601171e-01 -6.17873073e-01 1.30485207e-01 -9.13539350e-01 -6.91795230e-01 -5.32699347e-01 -5.94232321e-01 7.96597898e-01 1.19706973e-01 -5.19412123e-02 1.21110725e+00 3.75867933e-01 -3.27616572e-01 -9.92844582e-01 -1.13873172e+00 -7.20555365e-01 -8.51399153e-02 -1.48646876e-01 3.14306110e-01 6.18913531e-01 -1.89463288e-01 2.91197985e-01 -7.36073732e-01 2.73885131e-01 1.13774562e+00 -8.27432573e-02 9.48443651e-01 -1.12008882e+00 -3.71788710e-01 -2.48598725e-01 -6.65451705e-01 -1.51412570e+00 6.19549192e-02 -6.70635939e-01 2.08030447e-01 -1.68838072e+00 -3.31090875e-02 -1.85693935e-01 -1.05204768e-01 5.29770315e-01 7.57401511e-02 2.74483740e-01 3.00576061e-01 1.81381077e-01 -8.14512551e-01 6.52357340e-01 1.79642057e+00 2.86518112e-02 2.61421837e-02 -3.05577088e-02 2.31649037e-02 1.03656220e+00 7.17905760e-01 -2.86480457e-01 -2.35846207e-01 -6.73535466e-01 3.89709068e-03 2.28877679e-01 6.93250299e-01 -1.43137336e+00 3.48639041e-01 6.92349719e-03 7.91092575e-01 -8.81463349e-01 3.16446990e-01 -7.63282239e-01 4.33867842e-01 1.00786853e+00 -2.49867097e-01 8.36790875e-02 -1.29222676e-01 6.40264332e-01 2.29119003e-01 5.75701535e-01 8.52647483e-01 -2.63124555e-01 -7.97599912e-01 6.48802280e-01 4.82818522e-02 2.36825049e-01 7.94463098e-01 -1.21943444e-01 2.81873848e-02 -3.30388844e-02 -1.03458226e+00 8.69570673e-01 5.22391498e-01 4.75799501e-01 5.36107421e-01 -1.40361047e+00 -6.61661088e-01 -3.64876427e-02 -5.26498556e-02 4.47679281e-01 4.33226794e-01 1.09692550e+00 -9.74741399e-01 1.63668036e-01 -4.30004388e-01 -8.41933727e-01 -9.67612028e-01 1.91517606e-01 5.59252024e-01 -2.88036942e-01 -9.68597531e-01 9.82537150e-01 -3.42581049e-03 -5.96688569e-01 4.29886878e-01 -3.63798827e-01 2.00707734e-01 -4.95567471e-01 -1.18862912e-01 7.78187335e-01 -4.30866212e-01 -9.13373470e-01 -6.16565228e-01 1.10410511e+00 4.02831078e-01 8.02856833e-02 1.08488083e+00 -2.91027009e-01 -9.11415443e-02 -3.39348689e-02 1.10493886e+00 -2.05047935e-01 -1.69598246e+00 -1.11458041e-01 -1.90268174e-01 -1.54908955e-01 -3.61670405e-01 -9.09229636e-01 -1.28377414e+00 7.86609530e-01 3.84495884e-01 -6.34313941e-01 9.15523589e-01 1.55507416e-01 1.22878492e+00 2.05409825e-02 7.26056039e-01 -1.37250113e+00 6.66144565e-02 4.97232080e-01 1.07983208e+00 -6.54034734e-01 3.77476782e-01 -8.91205549e-01 -3.77323359e-01 8.94077837e-01 1.06375408e+00 -3.39150727e-01 7.69575775e-01 1.55313462e-01 -6.06107004e-02 -4.21553612e-01 -4.85104889e-01 -1.97523758e-01 5.58874249e-01 6.18618667e-01 5.27425051e-01 1.36852577e-01 -5.25907457e-01 4.26110297e-01 -2.18434036e-01 1.36783600e-01 -1.69051811e-01 9.96616483e-01 -3.70482326e-01 -1.06589675e+00 -3.27577949e-01 1.01046443e-01 -2.57508337e-01 3.96538973e-01 -4.29474503e-01 1.09471416e+00 4.49547440e-01 4.81495976e-01 -1.85018778e-01 -5.09290099e-01 6.56309009e-01 -2.45024692e-02 9.04740036e-01 -4.32801694e-01 -4.09096479e-01 2.95182675e-01 2.68523335e-01 -1.16352606e+00 -4.37784702e-01 -4.29525256e-01 -1.77182686e+00 -4.77013946e-01 -2.66353264e-02 -1.66848361e-01 3.89757216e-01 6.97279394e-01 5.26648998e-01 6.84937179e-01 2.99896132e-02 -1.16519427e+00 -3.29453230e-01 -1.02956092e+00 -5.17414272e-01 5.23792386e-01 -1.07777119e-01 -1.11300182e+00 9.09765735e-02 1.62799045e-01]	[7.099092960357666, -0.6394210457801819]
f6e04f33-5ce3-45de-8720-aa2432cb38fc	efficient-informed-proposals-for-discrete	2302.13929	null	https://arxiv.org/abs/2302.13929v1	https://arxiv.org/pdf/2302.13929v1.pdf	Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation	Gradients have been exploited in proposal distributions to accelerate the convergence of Markov chain Monte Carlo algorithms on discrete distributions. However, these methods require a natural differentiable extension of the target discrete distribution, which often does not exist or does not provide effective gradient guidance. In this paper, we develop a gradient-like proposal for any discrete distribution without this strong requirement. Built upon a locally-balanced proposal, our method efficiently approximates the discrete likelihood ratio via Newton's series expansion to enable a large and efficient exploration in discrete spaces. We show that our method can also be viewed as a multilinear extension, thus inheriting its desired properties. We prove that our method has a guaranteed convergence rate with or without the Metropolis-Hastings step. Furthermore, our method outperforms a number of popular alternatives in several different experiments, including the facility location problem, extractive text summarization, and image retrieval.	['Ruqi Zhang', 'Dongkuan Xu', 'Bowen Lei', 'Dongyao Zhu', 'Yue Xiang']	2023-02-27	null	null	null	null	['efficient-exploration', 'extractive-document-summarization']	['methodology', 'natural-language-processing']	[ 5.76860718e-02 -1.64586172e-01 -3.13402772e-01 -2.42790967e-01 -1.18828642e+00 -7.29849815e-01 7.93713689e-01 2.84345061e-01 -5.94986320e-01 1.15331328e+00 1.95983276e-01 -4.45896804e-01 -2.19871715e-01 -7.41670430e-01 -6.87629282e-01 -9.39282656e-01 2.27398410e-01 1.13709533e+00 -3.90664861e-02 1.42503604e-01 5.13870478e-01 5.98111987e-01 -9.34690595e-01 -4.51179117e-01 1.18493342e+00 5.64575851e-01 1.82652399e-01 8.19477975e-01 -2.30473146e-01 3.13561410e-01 -4.17434663e-01 -1.28539056e-01 2.53613085e-01 -5.38323700e-01 -5.92657089e-01 1.60637259e-01 2.98920780e-01 -5.45671701e-01 -1.06330693e-01 1.19478464e+00 5.84878981e-01 3.23135495e-01 1.15811408e+00 -9.87819195e-01 -3.12490106e-01 4.71677721e-01 -8.48543584e-01 -5.33403568e-02 3.60322326e-01 -7.44986534e-02 1.00412941e+00 -9.13604081e-01 5.94145179e-01 1.21748376e+00 4.26281750e-01 1.33159831e-01 -1.44979227e+00 -4.40227985e-01 1.32974699e-01 -3.90092999e-01 -1.40565598e+00 -1.43586442e-01 5.02233803e-01 -1.59174293e-01 5.30657351e-01 3.06539416e-01 7.74344563e-01 8.33251417e-01 9.91763994e-02 1.16939342e+00 1.11316681e+00 -5.89179933e-01 6.55367017e-01 1.00897603e-01 -5.89854904e-02 7.68572092e-01 5.45258462e-01 -2.40191340e-01 -2.85461038e-01 -8.49031091e-01 8.94625366e-01 1.48925275e-01 -1.76801056e-01 -7.24784791e-01 -1.25020695e+00 1.26589000e+00 6.34395629e-02 -2.62144022e-02 -3.94810766e-01 2.95969069e-01 1.20129876e-01 6.05269801e-03 5.17580271e-01 2.32475936e-01 -2.44641062e-02 -4.22500610e-01 -1.27380002e+00 5.98455191e-01 1.31722093e+00 9.35761094e-01 7.55856633e-01 -1.49373144e-01 -2.52588630e-01 4.14997131e-01 3.30736905e-01 9.64541316e-01 4.71964292e-02 -9.91780877e-01 4.90070969e-01 -9.99754146e-02 7.30981648e-01 -7.11745143e-01 -1.36574864e-01 -2.77405858e-01 -9.62826252e-01 -1.09604031e-01 6.96626186e-01 -3.38615596e-01 -7.03792036e-01 1.67827308e+00 4.86910820e-01 3.27420309e-02 -2.58480996e-01 7.09070802e-01 -3.20033908e-01 8.99322510e-01 -2.69639045e-01 -6.05076909e-01 7.82669067e-01 -9.20464456e-01 -6.22991383e-01 1.03495017e-01 5.57245970e-01 -7.42020190e-01 1.07165635e+00 5.87945580e-01 -1.26306653e+00 8.53670537e-02 -7.18611538e-01 1.75056025e-01 1.18032679e-01 1.29640326e-01 7.52633572e-01 7.78709710e-01 -1.08147883e+00 5.71374893e-01 -9.52759147e-01 -3.07182193e-01 2.92881876e-01 2.12221622e-01 1.53125256e-01 -1.28893510e-01 -7.55313873e-01 6.79258466e-01 3.19594175e-01 -1.32066710e-02 -9.48504388e-01 -3.29501957e-01 -4.88798529e-01 1.67485774e-01 4.66933697e-01 -9.44156408e-01 1.21825731e+00 -4.28194284e-01 -1.72242332e+00 3.89370620e-01 -2.23841786e-01 -4.56350327e-01 1.04688478e+00 -3.42916161e-01 2.61351168e-01 2.52797782e-01 1.13878839e-01 5.15701950e-01 1.06686592e+00 -9.64014471e-01 -5.15604377e-01 -2.34091565e-01 -7.63674229e-02 5.37528336e-01 -3.44405442e-01 -3.03207755e-01 -2.94092149e-01 -4.72959250e-01 4.23673242e-02 -1.08066094e+00 -7.03347147e-01 -1.61028638e-01 -4.46277887e-01 -2.48760968e-01 4.32014853e-01 -4.20839876e-01 1.12399697e+00 -1.90046430e+00 3.30629975e-01 6.55220091e-01 1.42547593e-01 -1.09775960e-01 8.44582245e-02 7.48739302e-01 5.75046360e-01 1.58987105e-01 -4.80687708e-01 -5.10876894e-01 4.08672959e-01 1.74156725e-01 -4.90407705e-01 9.83439207e-01 -1.41988188e-01 6.26076639e-01 -1.11507809e+00 -6.15700006e-01 7.25757405e-02 2.08086789e-01 -9.45923209e-01 -1.48927525e-01 -3.53530645e-01 2.85704046e-01 -7.88928151e-01 4.16354477e-01 7.56253898e-01 -3.07044655e-01 3.89868200e-01 3.65652531e-01 -8.89198035e-02 3.14543359e-02 -1.52593863e+00 1.82219577e+00 -3.14532965e-01 3.91451776e-01 2.68126070e-01 -9.09100354e-01 6.02059901e-01 -1.94169991e-02 3.01752061e-01 3.38357780e-03 -2.23708693e-02 5.04838586e-01 -5.06113946e-01 1.62598103e-01 9.55946624e-01 -3.28486085e-01 -1.92494020e-01 7.25864112e-01 -3.61805320e-01 -4.26228195e-01 2.47490659e-01 6.49814248e-01 8.94411922e-01 3.25866640e-02 3.72559369e-01 -5.11403322e-01 1.85826868e-01 -1.73595354e-01 3.08458984e-01 1.43651080e+00 8.03333670e-02 5.50068021e-01 6.55007541e-01 1.41048655e-02 -1.22613120e+00 -1.45614421e+00 -1.96448132e-01 7.80111969e-01 1.46430984e-01 -3.80870581e-01 -8.23872685e-01 -6.96959615e-01 9.90453362e-02 7.92798936e-01 -2.64595449e-01 1.60257593e-01 -4.61540431e-01 -9.77595985e-01 3.31971467e-01 3.54888737e-01 2.68750608e-01 -5.21371245e-01 -5.02273500e-01 3.11384529e-01 -2.15871453e-01 -6.05880499e-01 -7.48299181e-01 1.63346633e-01 -1.16065764e+00 -7.28194773e-01 -1.09677923e+00 -3.96737128e-01 8.71995449e-01 1.07723825e-01 7.75921464e-01 -4.44323450e-01 -9.56302732e-02 5.17493367e-01 -4.41114884e-03 -6.17488846e-02 -3.04449469e-01 3.29727411e-01 2.45608434e-01 -2.20041335e-01 3.56240720e-02 -4.24342662e-01 -6.52592778e-01 5.40534072e-02 -1.06238675e+00 -3.61647159e-02 7.62902021e-01 1.08142209e+00 5.24637461e-01 9.91111621e-03 3.80608201e-01 -8.18394303e-01 1.00611413e+00 -4.50605780e-01 -1.00737596e+00 1.30331159e-01 -6.28021479e-01 5.66504657e-01 4.34443802e-01 -4.99926746e-01 -1.12676990e+00 4.66665626e-02 9.42285433e-02 -1.46448791e-01 6.41256720e-02 7.22685754e-01 6.63299114e-02 7.50754029e-02 4.83907938e-01 3.51667643e-01 1.28643634e-02 -5.19978285e-01 7.44065762e-01 5.91240883e-01 3.54437262e-01 -9.39436436e-01 7.16705501e-01 8.12554657e-01 1.22605860e-01 -7.91233003e-01 -7.31267810e-01 -5.45571268e-01 -3.45664799e-01 1.67475253e-01 4.90146279e-01 -6.51245117e-01 -6.72033012e-01 3.56193870e-01 -1.02099228e+00 -2.94012815e-01 -3.84196281e-01 7.55014420e-01 -8.30112994e-01 7.85429180e-01 -7.29443431e-01 -1.12537169e+00 -1.13826558e-01 -1.06650352e+00 1.13355649e+00 1.83277532e-01 -8.23973715e-02 -1.06996727e+00 3.22916269e-01 -2.43394114e-02 4.96306866e-01 1.09608717e-01 7.78292000e-01 -5.84845364e-01 -7.26744771e-01 -3.25215727e-01 -2.18985826e-01 4.26164344e-02 -1.13874115e-01 3.98078561e-02 -2.42236003e-01 -6.61928058e-01 4.12198268e-02 -2.99473882e-01 9.89445031e-01 6.85799897e-01 9.39427912e-01 -4.13389534e-01 -5.10229349e-01 4.16753471e-01 1.31685340e+00 -2.81320482e-01 4.49246705e-01 2.99215257e-01 4.76345032e-01 2.21429750e-01 7.19957650e-01 9.58390713e-01 1.69811636e-01 2.86967158e-01 1.56039238e-01 6.86963350e-02 5.91639280e-01 -3.69059056e-01 4.32764322e-01 7.40785539e-01 1.52048469e-01 -2.99476862e-01 -7.63652861e-01 5.89665651e-01 -2.07080460e+00 -8.24273229e-01 3.73429842e-02 2.32460141e+00 1.19480276e+00 3.51005122e-02 1.78187847e-01 -2.17174634e-01 7.14019835e-01 1.17546201e-01 -5.71833074e-01 -2.59619623e-01 -8.93574674e-03 1.64657727e-01 8.45369160e-01 7.04644799e-01 -9.45823133e-01 8.93751442e-01 7.09341717e+00 1.28608644e+00 -6.05819523e-01 9.65439975e-02 4.91267443e-01 -1.29057765e-01 -6.77690327e-01 2.42752209e-01 -1.05114162e+00 3.74321014e-01 7.31528521e-01 -2.48687580e-01 4.03549373e-01 8.55327427e-01 1.48242116e-01 -5.00410438e-01 -9.35998440e-01 8.49391818e-01 -7.06204921e-02 -1.28051841e+00 2.06137989e-02 4.59224224e-01 1.02948546e+00 -1.59540147e-01 1.77724183e-01 4.71268361e-03 7.56003261e-01 -8.46346974e-01 6.45921469e-01 4.91768152e-01 5.99916279e-01 -1.13896132e+00 3.94247472e-01 6.14864469e-01 -6.65395260e-01 8.32757354e-02 -4.18689966e-01 1.50342388e-02 6.62578762e-01 9.53639388e-01 -9.24841523e-01 3.81162167e-01 1.14658996e-01 2.02807486e-01 -9.42787752e-02 1.22247565e+00 -1.74097389e-01 7.66592383e-01 -9.08306777e-01 -3.89846116e-01 7.23070681e-01 -7.47962832e-01 8.64754200e-01 1.25473285e+00 5.10880709e-01 -9.04105529e-02 4.15065944e-01 7.56652176e-01 2.09023356e-02 1.87399074e-01 -4.07734454e-01 -2.95644373e-01 4.19876069e-01 1.04618502e+00 -9.85984743e-01 -5.18323720e-01 -2.55169664e-02 1.14094234e+00 2.48347133e-01 5.71159422e-01 -1.02213109e+00 -4.56411958e-01 3.26796263e-01 -2.27657557e-02 5.07213891e-01 -6.05080545e-01 7.18837827e-02 -1.32248390e+00 -8.33083019e-02 -7.04135656e-01 2.94096142e-01 -4.07715857e-01 -1.18079913e+00 1.27685025e-01 3.27676415e-01 -6.74098790e-01 -6.37554765e-01 -2.87336230e-01 -3.29059035e-01 7.64724314e-01 -1.40721083e+00 -7.33667493e-01 2.76598454e-01 5.97359955e-01 1.46318898e-01 1.18149057e-01 5.56377590e-01 3.02971750e-02 -2.46788368e-01 3.56374353e-01 9.28465605e-01 -3.85605186e-01 8.27154517e-01 -1.56288087e+00 1.14982702e-01 8.32902133e-01 1.31626561e-01 6.73747301e-01 9.99577701e-01 -8.23738635e-01 -1.52637982e+00 -6.94410801e-01 6.17098331e-01 -1.68830752e-01 7.61448860e-01 -1.98622212e-01 -5.00351608e-01 7.33683825e-01 1.82203129e-01 -5.00989079e-01 4.84455228e-01 1.86583772e-01 6.22156970e-02 1.80186868e-01 -1.14128280e+00 8.32979143e-01 6.72289431e-01 -2.74172306e-01 -3.67365241e-01 7.23419845e-01 3.65445554e-01 -4.17017728e-01 -4.63117898e-01 -4.07469235e-02 3.55642915e-01 -6.18473768e-01 8.21630955e-01 -5.30888677e-01 4.64302152e-02 -2.68981636e-01 -2.10369542e-01 -1.16562927e+00 -1.88174710e-01 -1.08429539e+00 -2.73513675e-01 1.03091514e+00 1.75033689e-01 -8.53205740e-01 8.43804896e-01 4.47727174e-01 2.32839167e-01 -6.46753848e-01 -9.13122237e-01 -8.60166490e-01 3.05067658e-01 -2.13892594e-01 3.53093565e-01 5.00954807e-01 -1.79879040e-01 6.70330748e-02 -5.62870502e-01 5.21885790e-02 1.11904502e+00 3.09634298e-01 8.60350728e-01 -9.47927833e-01 -4.39378440e-01 -3.99057686e-01 3.92904766e-02 -1.74675405e+00 2.42379904e-01 -8.03856552e-01 7.72308186e-02 -1.65563977e+00 4.91656095e-01 -5.36889732e-01 8.30771774e-03 2.83838604e-02 -9.28647369e-02 -9.68549699e-02 -3.36438492e-02 2.48382509e-01 -8.62861872e-01 8.28446388e-01 1.11958694e+00 2.40339190e-02 -2.85712808e-01 1.75436005e-01 -6.12866700e-01 8.20592701e-01 7.53967524e-01 -5.59418976e-01 -1.98746160e-01 -7.51580670e-02 5.12937129e-01 2.75826812e-01 1.65597692e-01 -5.51075459e-01 3.92790079e-01 -3.72003049e-01 1.45533219e-01 -1.00925386e+00 3.21639329e-01 -4.16703790e-01 1.04907118e-01 4.95395720e-01 -3.05045605e-01 -7.17771472e-03 -1.96697518e-01 1.04377675e+00 -3.61459628e-02 -5.79574227e-01 6.83690846e-01 -9.17151496e-02 -5.60144931e-02 1.82102442e-01 -7.02401459e-01 2.06761688e-01 7.13841081e-01 2.89102327e-02 9.96190310e-02 -6.87625885e-01 -6.16021276e-01 4.42171931e-01 8.91782522e-01 -3.59136730e-01 5.70694804e-01 -1.32460296e+00 -6.99516833e-01 -1.80562958e-01 -4.27013129e-01 5.00077568e-02 -6.22087605e-02 1.16842294e+00 -7.00563967e-01 3.97502571e-01 2.70418644e-01 -6.70207381e-01 -8.75039220e-01 2.85120606e-01 -6.63848817e-02 -7.05385625e-01 -5.23552239e-01 5.71088672e-01 1.02603063e-01 -3.47772151e-01 1.67037129e-01 -3.33371341e-01 4.77424234e-01 1.01208627e-01 3.58038664e-01 5.16332686e-01 -5.02410948e-01 -7.06222504e-02 -2.04684824e-01 2.49581531e-01 -2.85972297e-01 -8.40250015e-01 1.18312848e+00 -4.54490662e-01 -2.47746885e-01 4.75262314e-01 1.10090780e+00 3.77189219e-01 -1.39230692e+00 -2.09090695e-01 -7.30600208e-02 -6.71076596e-01 -7.76840374e-02 -3.72366279e-01 -5.55283010e-01 6.81738257e-01 9.29150805e-02 2.02143535e-01 7.11630523e-01 -1.10072613e-01 8.70799899e-01 6.74743295e-01 4.29398477e-01 -1.23459744e+00 3.37396339e-02 3.68808091e-01 4.80004162e-01 -1.07116950e+00 2.89008379e-01 3.02819023e-03 -5.84269166e-01 9.25257862e-01 -1.46039590e-01 -1.94041595e-01 4.35074627e-01 2.22968966e-01 -5.63966870e-01 1.32741243e-01 -5.28138697e-01 1.01911407e-02 -6.67674765e-02 2.49643952e-01 1.17429361e-01 1.80009961e-01 -6.46094322e-01 1.56984597e-01 -6.51316345e-02 -1.13281541e-01 7.27277696e-01 1.01490891e+00 -6.70456767e-01 -1.11291039e+00 -4.84873414e-01 4.90549862e-01 -4.11721170e-01 -3.14098179e-01 -1.66406557e-02 7.39616156e-01 -7.55656421e-01 6.70880139e-01 -1.17044404e-01 4.78513241e-01 -2.48597592e-01 -4.68489788e-02 7.50161111e-01 -3.64252567e-01 -8.78615677e-03 5.40451944e-01 -1.40853941e-01 -4.13792878e-01 -3.24033767e-01 -1.06452596e+00 -9.76590037e-01 -5.72975993e-01 -6.81910992e-01 6.57167792e-01 6.97266579e-01 7.91447997e-01 1.53134778e-01 -6.90208450e-02 5.30465245e-01 -8.58954072e-01 -1.24647677e+00 -6.76336288e-01 -9.61580098e-01 -1.37451306e-01 2.26322114e-01 -5.70181251e-01 -5.18419087e-01 -2.81798810e-01]	[6.897722244262695, 4.030930519104004]
fdda4a5e-10e5-498a-9e5a-7b58d1cd9db6	blindly-assess-image-quality-in-the-wild	null	null	http://openaccess.thecvf.com/content_CVPR_2020/html/Su_Blindly_Assess_Image_Quality_in_the_Wild_Guided_by_a_CVPR_2020_paper.html	http://openaccess.thecvf.com/content_CVPR_2020/papers/Su_Blindly_Assess_Image_Quality_in_the_Wild_Guided_by_a_CVPR_2020_paper.pdf	Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper Network	Blind image quality assessment (BIQA) for authentically distorted images has always been a challenging problem, since images captured in the wild include varies contents and diverse types of distortions. The vast majority of prior BIQA methods focus on how to predict synthetic image quality, but fail when applied to real-world distorted images. To deal with the challenge, we propose a self-adaptive hyper network architecture to blind assess image quality in the wild. We separate the IQA procedure into three stages including content understanding, perception rule learning and quality predicting. After extracting image semantics, perception rule is established adaptively by a hyper network, and then adopted by a quality prediction network. In our model, image quality can be estimated in a self-adaptive manner, thus generalizes well on diverse images captured in the wild. Experimental results verify that our approach not only outperforms the state-of-the-art methods on challenging authentic image databases but also achieves competing performances on synthetic image databases, though it is not explicitly designed for the synthetic task.	[' Yanning Zhang', ' Jinqiu Sun', ' Xin Ge', ' Cheng Zhang', ' Yu Zhu', ' Qingsen Yan', 'Shaolin Su']	2020-06-01	null	null	null	cvpr-2020-6	['blind-image-quality-assessment']	['computer-vision']	[ 4.92204577e-01 -3.54551762e-01 2.71859527e-01 -4.56404865e-01 -8.38297784e-01 -5.69360316e-01 4.77477074e-01 -1.75381035e-01 -4.11585838e-01 5.27278006e-01 1.27990216e-01 -8.62273350e-02 -1.24928243e-01 -7.28044331e-01 -7.92778373e-01 -5.97725689e-01 1.39979467e-01 2.87304729e-01 1.99820474e-01 -3.10957134e-01 4.18349922e-01 2.24992201e-01 -1.76378179e+00 2.80975491e-01 1.20798218e+00 1.34224224e+00 8.62067342e-02 8.95229876e-01 2.10872129e-01 9.65306401e-01 -7.67910421e-01 -7.66487241e-01 4.60940093e-01 -4.66717035e-01 -7.26954997e-01 3.96322846e-01 5.91863871e-01 -5.60990334e-01 -3.60290974e-01 1.46697748e+00 8.14834177e-01 -1.31943971e-01 5.90148926e-01 -1.43411338e+00 -1.04974711e+00 4.00844753e-01 -1.73321277e-01 1.66881099e-01 4.72704172e-01 7.98404872e-01 9.61611688e-01 -1.02511919e+00 3.02667975e-01 1.21305680e+00 3.79210979e-01 5.11507630e-01 -1.20881581e+00 -6.45397484e-01 -1.16843045e-01 8.02163839e-01 -1.22023880e+00 -6.21040225e-01 8.16320181e-01 -2.82591403e-01 3.80902469e-01 1.19989090e-01 5.77243567e-01 1.20150352e+00 7.61213824e-02 8.31664145e-01 1.56674695e+00 -1.08804733e-01 5.67215085e-01 -2.12895000e-04 -3.96952927e-01 2.42058545e-01 9.94997472e-02 2.71489710e-01 -7.08655059e-01 1.99978828e-01 4.76170748e-01 -3.09464276e-01 -7.21960545e-01 -6.88636303e-01 -1.50444245e+00 5.97000182e-01 6.31340384e-01 3.97706814e-02 -5.63753426e-01 -1.78103358e-01 2.22571522e-01 5.68359792e-01 5.17097786e-02 5.61786473e-01 -2.76544422e-01 -1.38966948e-01 -1.02264297e+00 3.67778361e-01 6.53387129e-01 7.21576273e-01 6.60971045e-01 1.83948696e-01 -4.20458913e-01 9.61913943e-01 1.04203962e-01 7.92125404e-01 5.26858807e-01 -1.17104733e+00 4.39944834e-01 4.15093780e-01 5.23815334e-01 -1.23779452e+00 -3.10169831e-02 -2.51228184e-01 -1.14983463e+00 6.03864729e-01 4.79559243e-01 2.48021275e-01 -9.38408613e-01 1.62569845e+00 1.42869338e-01 1.04273222e-01 2.52293736e-01 1.28165019e+00 7.86720634e-01 7.15780020e-01 -2.60940921e-02 -3.56039762e-01 1.17293942e+00 -8.00961256e-01 -7.31030583e-01 -3.02498877e-01 -3.40819061e-01 -6.61103308e-01 1.40250015e+00 8.82888377e-01 -1.32650805e+00 -9.90950406e-01 -1.27840543e+00 1.33683428e-01 -2.75670379e-01 -2.37879351e-01 -3.18107866e-02 8.31245244e-01 -1.38030028e+00 4.00545716e-01 -1.34857431e-01 -1.48958459e-01 5.84077835e-01 2.13036284e-01 -3.73666376e-01 -4.95113552e-01 -1.41932487e+00 7.84030497e-01 5.55113196e-01 4.98165451e-02 -1.24246299e+00 -5.78915834e-01 -8.51155102e-01 1.28942234e-02 4.60220844e-01 -9.25507784e-01 1.10913622e+00 -1.36390519e+00 -1.76032293e+00 7.93105960e-01 2.41579637e-01 -4.40238386e-01 7.09592044e-01 7.16214068e-04 -8.33474517e-01 3.79051328e-01 -4.66345474e-02 6.65761113e-01 1.37406778e+00 -1.98498189e+00 -6.52300298e-01 -4.07688707e-01 3.13064396e-01 3.29228401e-01 -3.77558142e-01 -1.13768004e-01 -6.72677994e-01 -6.73394799e-01 6.25045598e-02 -5.30262053e-01 -3.95196714e-02 3.05331022e-01 -9.97803584e-02 2.74862409e-01 4.58480895e-01 -7.30390906e-01 1.11674297e+00 -1.96143365e+00 6.43245652e-02 3.16070497e-01 2.78239131e-01 4.93501097e-01 -3.81369531e-01 5.71620576e-02 7.42985830e-02 -1.17323257e-01 -5.90623856e-01 -8.01804513e-02 1.54225945e-01 -5.52669400e-04 -2.64280558e-01 4.17343438e-01 1.98728979e-01 8.94611776e-01 -1.03753650e+00 -6.86777949e-01 2.36955434e-01 3.93940687e-01 -4.77738768e-01 7.15281129e-01 -2.09709197e-01 3.92423689e-01 1.86967105e-02 7.86489487e-01 1.00367129e+00 -3.62697512e-01 -1.45069240e-02 -5.71803451e-01 2.44090214e-01 -3.34335268e-01 -1.37310112e+00 1.80978918e+00 -4.01284039e-01 3.20743024e-01 5.65922447e-02 -7.79929698e-01 8.23238015e-01 2.46434778e-01 1.34339750e-01 -1.34659350e+00 -4.94596455e-03 1.86006367e-01 3.56802307e-02 -7.21443892e-01 5.01154244e-01 -1.11907357e-02 1.10476837e-01 2.86522776e-01 1.85652554e-01 -4.20794904e-01 2.13538900e-01 4.31959368e-02 9.34097946e-01 3.24685089e-02 2.18287453e-01 1.62061930e-01 9.65877950e-01 -2.33336791e-01 6.43308938e-01 8.98084402e-01 -6.45171881e-01 9.47943568e-01 2.10716844e-01 -3.51790786e-01 -1.35906577e+00 -1.45686972e+00 -4.44456469e-03 8.03939223e-01 7.50584126e-01 3.64946313e-02 -9.45561111e-01 -6.24589741e-01 -2.34622180e-01 5.08973062e-01 -6.06208444e-01 -3.03537697e-01 -2.65703738e-01 -6.65040553e-01 2.99762338e-01 1.20872237e-01 9.96346354e-01 -1.46944749e+00 -3.88946682e-01 1.30822361e-01 -4.69463736e-01 -1.32745898e+00 -4.08734351e-01 -4.52034354e-01 -3.52794111e-01 -1.04758275e+00 -9.23584104e-01 -5.42846203e-01 3.98179322e-01 2.92906970e-01 1.48209822e+00 -1.76745988e-02 -5.45301363e-02 4.34398830e-01 -4.00084853e-01 -1.34569719e-01 -7.02441096e-01 -5.06287217e-01 7.69571736e-02 6.90196872e-01 4.54023061e-03 -5.90524316e-01 -1.18684518e+00 5.66899717e-01 -1.31275725e+00 -2.02214018e-01 9.52942908e-01 1.05088115e+00 5.74762762e-01 3.61222208e-01 6.00014746e-01 -5.94437897e-01 6.58639908e-01 -2.07333788e-01 -5.37094057e-01 4.39586520e-01 -8.56321752e-01 -1.03643373e-01 8.12515676e-01 -3.97907019e-01 -1.22428703e+00 -2.00708866e-01 -4.98799160e-02 -3.56968462e-01 -3.54252547e-01 1.40694097e-01 -8.26312482e-01 -3.43741357e-01 8.33579838e-01 5.10055423e-01 5.53327873e-02 -8.38831440e-03 5.40702939e-01 6.81067348e-01 9.75813866e-01 -3.34028453e-01 1.12534153e+00 4.22614127e-01 -1.54936478e-01 -3.06110412e-01 -5.69546640e-01 -2.46328443e-01 -4.89920646e-01 -5.82121670e-01 7.82832444e-01 -1.00705481e+00 -9.27831709e-01 9.20434892e-01 -8.08434784e-01 -3.05694342e-01 -2.01513231e-01 1.41787782e-01 -9.58310008e-01 6.37288630e-01 -4.92468119e-01 -5.54071963e-01 -3.82761598e-01 -1.30356860e+00 8.17085803e-01 2.40417689e-01 1.98321551e-01 -6.13241255e-01 -5.69661409e-02 7.35757053e-01 5.92406511e-01 6.65695742e-02 8.36476564e-01 -9.01326984e-02 -7.03193128e-01 1.45410737e-02 -6.37983680e-01 6.75122499e-01 -4.11922261e-02 -3.05323184e-01 -1.07834101e+00 -2.85045564e-01 1.17004430e-02 -7.55488753e-01 6.79512262e-01 1.29574135e-01 1.45644796e+00 -3.78018796e-01 5.44874489e-01 7.34621525e-01 1.55477834e+00 4.05987799e-02 9.57241774e-01 4.39401209e-01 5.50749123e-01 4.91765320e-01 7.66912103e-01 3.26711506e-01 6.37802243e-01 6.32125556e-01 9.81592000e-01 -1.38556287e-01 -2.43124917e-01 -1.05181716e-01 4.36220616e-01 6.21535301e-01 1.45486251e-01 -5.22822142e-01 -8.73366594e-01 6.03809059e-01 -1.68669701e+00 -1.09913468e+00 2.93400675e-01 2.17753220e+00 1.11534464e+00 2.10008636e-01 1.71333149e-01 5.39678216e-01 5.57905197e-01 2.91711450e-01 -8.15896213e-01 -1.31947711e-01 -4.24894154e-01 -4.12450098e-02 3.03158402e-01 2.23493114e-01 -1.07481217e+00 7.57564127e-01 5.96934795e+00 8.71607959e-01 -9.27881300e-01 1.34979980e-02 8.65004778e-01 2.14525700e-01 -2.97792375e-01 -2.73383170e-01 8.59664753e-02 5.53474367e-01 8.25889945e-01 -3.49985505e-03 7.63828635e-01 5.05904913e-01 1.41874716e-01 -4.21617785e-03 -9.33957756e-01 1.41370535e+00 4.34616506e-01 -9.10485387e-01 4.36353147e-01 -2.00966343e-01 8.44886124e-01 -4.14944082e-01 5.93935549e-01 4.73567508e-02 3.11613113e-01 -1.15485716e+00 9.73844647e-01 7.44373739e-01 8.94187272e-01 -7.15922415e-01 7.55733132e-01 2.37100199e-01 -7.87874818e-01 -4.22138900e-01 -4.56642479e-01 3.10960203e-01 8.64995047e-02 5.30831814e-01 -4.81781185e-01 5.17280042e-01 9.92330432e-01 6.63521290e-01 -1.00585377e+00 1.34782481e+00 -1.49611652e-01 4.95048493e-01 4.22329426e-01 3.13389152e-01 -3.65423635e-02 -3.28859165e-02 3.62137437e-01 9.24503803e-01 3.98495644e-01 5.78375459e-02 -9.11930725e-02 8.84961665e-01 -1.80081859e-01 1.18725397e-01 -3.07994276e-01 2.76100039e-01 3.27645421e-01 1.04297256e+00 -3.19115102e-01 -3.61916512e-01 -2.22492889e-01 1.38680649e+00 4.82477471e-02 5.40480673e-01 -8.13409269e-01 -3.35707903e-01 5.66330194e-01 -1.28721952e-01 3.32003236e-01 2.14027703e-01 -2.64521629e-01 -1.25500321e+00 2.77987152e-01 -1.61686659e+00 2.65739888e-01 -1.34639311e+00 -1.57179892e+00 8.38427603e-01 -4.77332413e-01 -1.68096149e+00 -1.63897246e-01 -6.16930962e-01 -3.55888844e-01 7.09897101e-01 -1.88980627e+00 -1.13039100e+00 -8.13212931e-01 1.05290782e+00 5.64330816e-01 -2.06451163e-01 6.83230937e-01 2.82935351e-01 -2.80444205e-01 7.06273735e-01 8.56312644e-03 9.46056098e-02 1.02856588e+00 -1.43091178e+00 4.35636193e-01 1.12063587e+00 -3.57679129e-02 7.85663202e-02 7.65136719e-01 -2.81874835e-01 -1.46195006e+00 -1.11715686e+00 3.47911656e-01 -3.06493580e-01 4.59967852e-01 -1.34288937e-01 -1.08389652e+00 -1.97929204e-01 4.84339148e-01 2.41397098e-01 4.17598307e-01 -5.19871473e-01 -7.35367954e-01 -5.69034755e-01 -1.33254182e+00 5.53283870e-01 1.01400566e+00 -5.66338003e-01 -3.45283538e-01 4.64005545e-02 7.21076190e-01 -2.38423064e-01 -9.81538951e-01 5.82428634e-01 4.12771672e-01 -1.45860517e+00 1.26736200e+00 -1.88488171e-01 6.43026352e-01 -6.69962227e-01 -2.71916509e-01 -1.51294959e+00 -2.79855907e-01 -4.40929294e-01 -9.15883631e-02 1.25224578e+00 2.55178392e-01 -2.62479931e-01 5.03932893e-01 3.70954931e-01 1.76815510e-01 -3.05683136e-01 -7.17858374e-01 -6.50315464e-01 -2.17083439e-01 -4.69126225e-01 9.96648371e-01 7.32444882e-01 -4.77065980e-01 4.34549805e-03 -6.61889553e-01 4.66577381e-01 1.14037013e+00 1.43158242e-01 8.41457367e-01 -9.73095238e-01 -3.82290870e-01 -6.47317529e-01 -7.00416982e-01 -9.35370445e-01 -6.19938560e-02 -3.96611363e-01 3.60191017e-01 -1.35566080e+00 1.73917577e-01 -2.53422439e-01 -3.71977359e-01 -8.76040235e-02 -5.88160396e-01 6.46573007e-01 2.67673850e-01 3.07148933e-01 -1.05389845e+00 7.15294838e-01 1.46248293e+00 -5.65681875e-01 1.36249647e-01 -7.79883936e-02 -7.01752841e-01 3.78838599e-01 6.65310502e-01 -4.95204739e-02 -6.06299996e-01 -3.78021300e-01 4.03256178e-01 3.00658822e-01 6.01204872e-01 -1.50305617e+00 2.89721489e-01 -1.83865204e-01 6.27971828e-01 -2.66725093e-01 2.02560037e-01 -1.07568049e+00 -6.66189892e-03 1.93276718e-01 -3.17279130e-01 3.37150358e-02 -1.96883976e-01 6.88310146e-01 -5.54826021e-01 1.06897622e-01 1.05578446e+00 -1.05975866e-01 -1.00719690e+00 6.32373631e-01 1.43313929e-01 1.98610276e-01 8.52003157e-01 -3.39112073e-01 -2.81822532e-01 -7.02919722e-01 -6.56138599e-01 2.02296928e-01 7.13156223e-01 5.02440095e-01 1.08295989e+00 -1.45141923e+00 -8.98305357e-01 2.54719675e-01 6.45900548e-01 -1.84277400e-01 6.23260438e-01 2.86447436e-01 -5.54327786e-01 -1.58761263e-01 -5.71789682e-01 -6.57797813e-01 -9.25096691e-01 1.03328943e+00 4.67847347e-01 -7.10843652e-02 -2.25250855e-01 6.42173052e-01 7.73757249e-02 -2.49850407e-01 4.19831485e-01 6.06080070e-02 -4.45621997e-01 -1.53462082e-01 8.02607238e-01 1.68159053e-01 1.06691279e-01 -9.59895313e-01 7.80085847e-02 6.17508650e-01 1.77839398e-01 -2.63088346e-01 1.17323184e+00 -5.80148399e-01 -1.09431092e-02 3.21907908e-01 9.44110096e-01 -3.71851057e-01 -1.48683560e+00 -4.91181523e-01 -2.57531345e-01 -8.96907449e-01 -5.08101098e-02 -1.35862684e+00 -1.31715178e+00 8.11188757e-01 1.16974628e+00 2.66877472e-01 1.80380023e+00 -4.12397206e-01 7.78143287e-01 1.77901641e-01 3.99843127e-01 -1.07192326e+00 5.55441439e-01 7.87559897e-02 1.20761847e+00 -1.72498512e+00 -3.03663641e-01 -3.65688540e-02 -9.10889983e-01 8.08821619e-01 7.51718760e-01 7.83074573e-02 5.12272775e-01 -2.39115596e-01 4.33158994e-01 5.66663183e-02 -5.19517601e-01 -1.49403572e-01 4.35773462e-01 1.00680184e+00 -1.16065741e-01 -1.18952550e-01 2.40353823e-01 3.84128988e-01 -2.58702695e-01 4.29108320e-03 5.90896070e-01 4.16694224e-01 -3.26867938e-01 -9.36299682e-01 -6.79684103e-01 2.27410063e-01 -3.02802980e-01 -1.77748084e-01 -1.74238667e-01 3.02602232e-01 3.69514346e-01 1.26991117e+00 -1.71630606e-01 -4.86534745e-01 5.96204162e-01 -2.36946955e-01 3.07087570e-01 -4.59178463e-02 -5.08700609e-01 -3.22650820e-01 -3.39186102e-01 -9.56248462e-01 -5.93321383e-01 -4.89121825e-01 -7.02137411e-01 -3.40329289e-01 5.75631484e-02 -1.98118255e-01 6.40670717e-01 6.41046464e-01 1.79387838e-01 5.25357008e-01 1.04703939e+00 -8.08265567e-01 -6.97514176e-01 -7.02804685e-01 -5.54760695e-01 9.88500535e-01 6.47608340e-01 -3.63886803e-01 -3.92945945e-01 3.54062855e-01]	[11.883524894714355, -1.8292521238327026]
9a37ca47-f7b3-419c-8eda-934c604e2b83	pstnet-point-spatio-temporal-convolution-on-1	2205.13713	null	https://arxiv.org/abs/2205.13713v1	https://arxiv.org/pdf/2205.13713v1.pdf	PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences	Point cloud sequences are irregular and unordered in the spatial dimension while exhibiting regularities and order in the temporal dimension. Therefore, existing grid based convolutions for conventional video processing cannot be directly applied to spatio-temporal modeling of raw point cloud sequences. In this paper, we propose a point spatio-temporal (PST) convolution to achieve informative representations of point cloud sequences. The proposed PST convolution first disentangles space and time in point cloud sequences. Then, a spatial convolution is employed to capture the local structure of points in the 3D space, and a temporal convolution is used to model the dynamics of the spatial regions along the time dimension. Furthermore, we incorporate the proposed PST convolution into a deep network, namely PSTNet, to extract features of point cloud sequences in a hierarchical manner. Extensive experiments on widely-used 3D action recognition and 4D semantic segmentation datasets demonstrate the effectiveness of PSTNet to model point cloud sequences.	['Mohan Kankanhalli', 'Yi Yang', 'Yuhang Ding', 'Xin Yu', 'Hehe Fan']	2022-05-27	pstnet-point-spatio-temporal-convolution-on	https://openreview.net/forum?id=O3bqkf_Puys	https://openreview.net/pdf?id=O3bqkf_Puys	iclr-2021-1	['3d-human-action-recognition']	['computer-vision']	[-2.76381914e-02 -7.25200415e-01 1.24250270e-01 -3.25461984e-01 1.79346874e-02 -5.25105476e-01 6.21620476e-01 -8.78689215e-02 -2.79062510e-01 1.87210962e-01 -3.74273807e-02 -3.63068193e-01 -1.30542338e-01 -9.55485165e-01 -8.03543746e-01 -6.14826500e-01 -3.21777046e-01 3.45234811e-01 4.65661079e-01 3.64642031e-02 2.83348352e-01 1.25557542e+00 -1.33363974e+00 3.32484335e-01 7.33775377e-01 1.19107258e+00 3.62592250e-01 7.25272834e-01 -5.97744465e-01 6.51214957e-01 -3.57384175e-01 1.63157448e-01 3.08988154e-01 4.17112634e-02 -6.00492656e-01 6.01718843e-01 1.46727577e-01 -5.26515663e-01 -9.21296775e-01 8.84346485e-01 -1.18377626e-01 4.06669855e-01 5.49253285e-01 -1.25261223e+00 -5.39776146e-01 1.33901224e-01 -6.89110458e-01 4.68815982e-01 1.15976028e-01 5.23505926e-01 7.08738744e-01 -7.86665499e-01 4.28913772e-01 1.36698699e+00 6.22443020e-01 1.17353581e-01 -7.49127924e-01 -6.22302175e-01 4.57236081e-01 3.41544569e-01 -1.33983064e+00 1.20849244e-01 1.04207671e+00 -6.27426982e-01 1.24579561e+00 1.23791412e-01 1.25319839e+00 9.72572625e-01 7.50209168e-02 9.77704406e-01 5.55728078e-01 2.68968284e-01 1.37797564e-01 -7.98302174e-01 -8.07479620e-02 4.94853497e-01 -3.24822783e-01 1.50775671e-01 -4.11253452e-01 -5.54733649e-02 1.58630610e+00 8.04156959e-01 7.22963959e-02 -4.57983673e-01 -1.37855303e+00 4.75432694e-01 6.93167031e-01 3.74967039e-01 -7.04041362e-01 5.83611310e-01 3.72514486e-01 -1.17104061e-01 6.25309706e-01 -1.13638997e-01 -4.21811134e-01 -3.61387700e-01 -1.01844156e+00 4.22359705e-01 2.13438436e-01 1.28398931e+00 6.33055151e-01 7.52483308e-02 -1.21669315e-01 5.25211036e-01 2.88389653e-01 4.55134451e-01 1.05715945e-01 -1.19891560e+00 6.27144516e-01 9.32755172e-01 1.69204250e-01 -1.08330619e+00 -3.24378431e-01 -2.08822995e-01 -9.99510765e-01 7.59589300e-02 2.24384636e-01 3.08051497e-01 -1.01548874e+00 1.13379574e+00 3.24579149e-01 1.02134442e+00 -1.80013195e-01 1.16702282e+00 5.60189664e-01 9.76017177e-01 1.39700860e-01 4.67473641e-02 1.18398535e+00 -5.86591423e-01 -3.45106989e-01 1.33858413e-01 3.01914901e-01 -2.75239676e-01 9.32264388e-01 -1.58009589e-01 -1.17323136e+00 -5.62370121e-01 -8.45848739e-01 -2.81427741e-01 -1.92581251e-01 -1.45523742e-01 5.62270403e-01 -2.20392630e-01 -8.27651024e-01 8.21358562e-01 -1.45397139e+00 -1.02453269e-01 8.72466385e-01 2.63709396e-01 -1.33242279e-01 -1.77299961e-01 -8.91582429e-01 2.23615021e-01 3.56501043e-01 3.35829079e-01 -6.90276504e-01 -8.03925753e-01 -8.19810450e-01 3.17292869e-01 7.39627630e-02 -8.34751070e-01 1.07596397e+00 -4.97782677e-01 -1.15637028e+00 5.71053505e-01 -3.28846186e-01 -5.67860067e-01 5.42299390e-01 -9.74189714e-02 -2.40909293e-01 4.73898053e-01 1.32752538e-01 6.73125982e-01 7.18418419e-01 -1.02391863e+00 -8.71603072e-01 -5.13093650e-01 4.75944802e-02 4.62132484e-01 1.69192389e-01 -2.07137823e-01 -6.96194351e-01 -6.45278335e-01 5.50384343e-01 -6.84807301e-01 -3.39131415e-01 2.28602424e-01 -2.57122904e-01 -3.44371945e-01 1.11209106e+00 -5.18048644e-01 7.95588732e-01 -2.38189697e+00 1.39280140e-01 9.82720777e-02 2.51466304e-01 1.02502681e-01 -6.47571459e-02 2.64017582e-01 -3.68523151e-02 3.68338078e-02 -3.68232518e-01 -3.24973822e-01 8.82643741e-03 6.33489788e-01 -4.56410825e-01 5.85393131e-01 4.51695591e-01 1.19937837e+00 -1.00558507e+00 -3.14711213e-01 6.62574470e-01 6.27857029e-01 -4.64113533e-01 -9.69536602e-03 -4.81065631e-01 5.92258513e-01 -8.56189072e-01 6.26272500e-01 8.78277957e-01 -4.08396304e-01 -3.99936706e-01 -3.58124115e-02 -4.65083331e-01 2.60956258e-01 -7.17448950e-01 1.98635411e+00 -1.81398407e-01 5.65774500e-01 -3.67069811e-01 -9.35614228e-01 7.72021651e-01 3.10124964e-01 1.12875378e+00 -6.86580002e-01 3.05122603e-02 6.18387274e-02 -2.64297962e-01 -4.18240130e-01 6.00877583e-01 9.25372690e-02 5.03254943e-02 1.47321403e-01 -2.00513348e-01 -1.19461037e-01 -2.23033786e-01 -1.08435145e-03 1.13662553e+00 1.50731266e-01 -2.43486330e-01 1.04673743e-01 4.26409066e-01 2.40760803e-01 5.41990757e-01 3.56597304e-01 -1.28723994e-01 7.09891140e-01 3.62958461e-01 -8.22987974e-01 -1.23571837e+00 -1.14951324e+00 1.35402396e-01 3.20834190e-01 5.39136589e-01 -1.05779424e-01 -3.57865185e-01 -5.23705184e-01 1.77719682e-01 5.02287149e-01 -5.67766011e-01 -2.98371017e-02 -8.83381605e-01 -2.16162235e-01 2.97081232e-01 8.59303713e-01 8.56216609e-01 -1.06839049e+00 -8.22428763e-01 3.68177116e-01 -1.75394639e-01 -1.36835599e+00 -6.20914876e-01 -1.01777263e-01 -1.27178144e+00 -9.86446440e-01 -5.40495276e-01 -5.71649194e-01 4.49899822e-01 6.29648328e-01 8.80819440e-01 -3.46153602e-03 3.48844938e-02 4.50189501e-01 -2.56129175e-01 -2.45075777e-01 2.39156932e-01 -1.40877873e-01 -1.86051920e-01 4.54530902e-02 7.40596175e-01 -1.10779405e+00 -9.27759588e-01 2.78968215e-01 -9.91570473e-01 1.14781052e-01 3.13068628e-01 5.49629867e-01 8.30421209e-01 1.67582050e-01 -1.50421992e-01 -2.35565796e-01 1.77401334e-01 -5.46542227e-01 -6.71723723e-01 -1.98071659e-01 2.13805422e-01 -3.17383826e-01 2.55547732e-01 -5.40508330e-01 -6.14649236e-01 2.62884885e-01 -1.09243207e-01 -1.36420131e+00 -3.76894206e-01 3.46338302e-01 -6.59017861e-02 5.03283255e-02 -2.14522928e-02 6.73473060e-01 -7.36730024e-02 -5.29075563e-01 2.66296297e-01 1.80487528e-01 6.24799669e-01 -4.68785107e-01 7.78338313e-01 1.01428568e+00 6.32972792e-02 -8.04367900e-01 -4.64284867e-01 -6.07226431e-01 -1.13026083e+00 -1.97327241e-01 1.24827039e+00 -9.10884023e-01 -8.63341987e-01 5.97782075e-01 -1.50732970e+00 -3.87168795e-01 -4.52857047e-01 4.78501976e-01 -9.08782005e-01 3.53553295e-01 -6.52406096e-01 -6.23470962e-01 7.42242411e-02 -1.02691662e+00 1.56430244e+00 1.12852827e-01 2.18600053e-02 -8.85691643e-01 -2.41543144e-01 2.16475520e-02 -1.96022600e-01 3.57876122e-01 8.92551363e-01 -1.40321970e-01 -1.29297364e+00 -9.40554067e-02 -4.65529740e-01 1.46947736e-02 8.40927064e-02 3.90738621e-02 -4.81376737e-01 1.95311815e-01 2.60710984e-01 4.07720268e-01 6.81050897e-01 8.28897357e-01 1.71222699e+00 -1.48625076e-01 -2.80243903e-01 1.09935570e+00 1.24472678e+00 4.65130597e-01 5.91851354e-01 2.97069550e-01 1.06655395e+00 1.85946733e-01 6.13328576e-01 6.66168153e-01 4.95359719e-01 5.58404565e-01 7.77750194e-01 -5.19798882e-02 1.67174399e-01 -5.24784565e-01 -1.21411689e-01 7.69469798e-01 -2.50965863e-01 3.62239406e-02 -1.01422536e+00 6.94930851e-01 -2.02735901e+00 -1.08253741e+00 -2.67029315e-01 1.65399039e+00 1.70956731e-01 1.47002807e-04 9.01922882e-02 2.77459044e-02 6.52157843e-01 3.77088010e-01 -8.12499166e-01 1.39355078e-01 -6.27060831e-02 5.30671626e-02 6.37428761e-01 9.36254859e-02 -1.15649545e+00 9.28277016e-01 5.38801575e+00 6.35047972e-01 -1.16831124e+00 -3.79975401e-02 2.68381029e-01 -3.13287824e-01 -1.98168471e-01 -1.06082149e-01 -2.43182808e-01 5.48181474e-01 3.98042798e-01 -6.79442286e-02 2.88176686e-01 6.58995748e-01 5.28818190e-01 3.39555740e-01 -9.93138433e-01 1.28588653e+00 -5.44142425e-01 -1.67706561e+00 2.36354873e-01 2.93304712e-01 5.12199581e-01 3.43878269e-01 1.51972711e-01 3.52678262e-02 2.84002781e-01 -9.34635341e-01 8.43866050e-01 6.75469279e-01 6.32701099e-01 -9.16799128e-01 2.17119172e-01 5.86625993e-01 -1.43733633e+00 -1.30066589e-01 -5.58487535e-01 -1.54276296e-01 4.52746689e-01 2.59883583e-01 -5.61153173e-01 5.64045072e-01 9.53577876e-01 1.43570924e+00 -1.39763221e-01 1.15362680e+00 1.00310579e-01 3.64710540e-01 -4.15408760e-01 1.58494711e-01 9.10353243e-01 -4.60130125e-01 8.27369630e-01 8.75346541e-01 6.04259431e-01 6.38740838e-01 1.16215706e-01 1.12579691e+00 1.77122965e-01 -4.65762675e-01 -7.71472633e-01 -1.08762302e-01 4.45235789e-01 7.26044178e-01 -8.06292295e-01 -3.41853291e-01 -4.29705203e-01 9.90135789e-01 5.25722504e-02 6.60329759e-01 -8.21933329e-01 -1.01080202e-01 1.24968302e+00 1.00859560e-01 7.30199397e-01 -1.08311701e+00 -4.47306693e-01 -1.22851646e+00 1.02148339e-01 -3.09964925e-01 1.65078327e-01 -9.96196508e-01 -1.34278429e+00 4.51357305e-01 4.53456603e-02 -1.64606917e+00 1.27566420e-02 -4.39224452e-01 -6.30127370e-01 1.13665175e+00 -1.47019386e+00 -1.03295517e+00 -3.96077991e-01 1.05697894e+00 7.56171227e-01 1.46770105e-01 2.93390691e-01 1.96866304e-01 -1.61499649e-01 -1.67406991e-01 -1.57704242e-02 2.84252256e-01 -3.16126138e-01 -9.96269941e-01 1.13337469e+00 7.69877732e-01 2.09124103e-01 5.43279052e-01 2.32094690e-01 -8.01192582e-01 -1.37797642e+00 -1.44867849e+00 6.46990001e-01 -3.79115134e-01 6.90083444e-01 -4.71729368e-01 -1.26700735e+00 6.84331954e-01 -2.94826418e-01 2.91260332e-01 2.64879316e-01 -4.43708658e-01 -2.32033283e-01 1.23353928e-01 -8.87170076e-01 6.80766642e-01 1.51950598e+00 -7.00851619e-01 -4.64343220e-01 4.36540008e-01 1.17760241e+00 -6.95562661e-01 -7.82501042e-01 4.70087349e-01 2.86832929e-01 -7.33658016e-01 1.31566298e+00 -6.25961483e-01 5.44679940e-01 -4.10538763e-01 -2.79751807e-01 -1.12481320e+00 -5.61949730e-01 -2.63992339e-01 -2.22584799e-01 6.73095107e-01 -1.56863391e-01 -3.88422698e-01 1.06001866e+00 3.22194695e-01 -4.22441036e-01 -7.71072626e-01 -1.15313601e+00 -6.80378437e-01 6.31769523e-02 -9.12502468e-01 1.15949249e+00 7.78885365e-01 -4.31115419e-01 -1.43144771e-01 -9.61292256e-03 5.36103904e-01 5.92972398e-01 3.33328724e-01 6.15101278e-01 -1.16964412e+00 1.61156505e-01 -6.89567089e-01 -8.64769936e-01 -1.67959893e+00 2.07106754e-01 -7.09215999e-01 -9.93706807e-02 -1.62974358e+00 -2.11465716e-01 -5.21012008e-01 -2.36293897e-01 -1.60138786e-03 -3.27003002e-02 -6.41721338e-02 3.13289672e-01 5.29395401e-01 -3.72731566e-01 8.73615861e-01 1.52748525e+00 -2.77273148e-01 -2.38812298e-01 8.13930780e-02 2.14147065e-02 6.88467622e-01 6.16702259e-01 -1.93508431e-01 -5.94120324e-01 -9.55715835e-01 -2.16953844e-01 3.38445187e-01 8.98433745e-01 -1.11259413e+00 2.93639451e-01 -4.21230465e-01 5.62752008e-01 -1.49320459e+00 7.54170299e-01 -1.20362937e+00 1.65593296e-01 1.03385642e-01 -7.58457258e-02 2.36646533e-01 2.77551353e-01 8.52698445e-01 -3.55753094e-01 3.61025274e-01 3.86648387e-01 -3.94024760e-01 -8.36804926e-01 1.27808118e+00 -2.03586951e-01 -4.50437665e-01 1.03594840e+00 -6.14990652e-01 1.21642008e-01 -9.01905596e-02 -8.41786146e-01 4.55345392e-01 5.88219821e-01 5.27264237e-01 1.05218673e+00 -1.57438016e+00 -3.26935709e-01 2.72479147e-01 -3.94013114e-02 6.21276140e-01 8.24454606e-01 7.93962836e-01 -8.17470491e-01 4.11289066e-01 -3.37094635e-01 -1.29747009e+00 -9.81273592e-01 5.60608506e-01 4.46992576e-01 5.56893460e-02 -1.33128142e+00 6.71366453e-01 4.13222462e-01 -3.39989066e-01 1.07602589e-01 -8.07200193e-01 -1.52810529e-01 -3.70025396e-01 3.29713255e-01 1.08322814e-01 -2.49878153e-01 -8.06522608e-01 -2.40090594e-01 7.13690817e-01 2.89198488e-01 -8.20594877e-02 1.61103821e+00 -1.54355317e-01 -1.95642352e-01 8.06264699e-01 1.23305500e+00 -8.28193843e-01 -1.83890307e+00 -4.09965605e-01 -3.34283039e-02 -8.35710824e-01 -1.24557979e-01 -6.29035383e-02 -1.13444602e+00 1.29393160e+00 2.14054599e-01 2.11836532e-01 1.10218692e+00 -5.84710799e-02 1.08961678e+00 -3.04268394e-02 4.39112395e-01 -6.00500464e-01 -6.23796247e-02 8.89371276e-01 7.58786082e-01 -6.48748577e-01 -3.96105736e-01 -5.18708289e-01 -5.61698198e-01 1.16811538e+00 5.01468658e-01 -4.49543089e-01 8.03301036e-01 7.51538798e-02 -3.87446672e-01 -5.85766554e-01 -7.32141852e-01 -3.66289169e-02 1.54535875e-01 6.37497604e-01 -1.03286780e-01 5.85892051e-02 2.61269659e-01 2.87996531e-01 -1.54908448e-01 1.68279096e-01 7.04822764e-02 8.54643822e-01 -2.27122203e-01 -6.14137113e-01 -1.95921823e-01 2.74796128e-01 -6.53418303e-02 1.20990023e-01 -1.68035269e-01 7.57906556e-01 2.46128932e-01 4.66109246e-01 7.83444166e-01 -5.01825511e-01 4.94251043e-01 -4.78513762e-02 4.08788979e-01 -3.95137906e-01 -3.45991462e-01 1.47408858e-01 -5.76514482e-01 -7.93662548e-01 -5.04965007e-01 -9.80709553e-01 -1.49515879e+00 -4.22127932e-01 4.28326547e-01 -2.40292288e-02 6.11378431e-01 9.03053582e-01 5.16746938e-01 7.53993392e-01 5.71969390e-01 -1.17546141e+00 -1.30702211e-02 -7.36762047e-01 -7.94983208e-01 3.98594558e-01 5.50394654e-01 -7.56178260e-01 2.53325049e-02 1.35239372e-02]	[8.406068801879883, -2.067034959793091]
1137c404-a32a-475d-a450-faa89e65fe1f	unsupervised-multi-object-segmentation-using	2205.13271	null	https://arxiv.org/abs/2205.13271v2	https://arxiv.org/pdf/2205.13271v2.pdf	Unsupervised Multi-object Segmentation Using Attention and Soft-argmax	We introduce a new architecture for unsupervised object-centric representation learning and multi-object detection and segmentation, which uses a translation-equivariant attention mechanism to predict the coordinates of the objects present in the scene and to associate a feature vector to each object. A transformer encoder handles occlusions and redundant detections, and a convolutional autoencoder is in charge of background reconstruction. We show that this architecture significantly outperforms the state of the art on complex synthetic benchmarks.	['Arnaud de La Fortelle', 'Bruno Sauvalle']	2022-05-26	null	null	null	null	['unsupervised-object-segmentation']	['computer-vision']	[ 1.60983875e-01 -1.68552458e-01 3.44247818e-02 -2.06324339e-01 -7.34101236e-01 -2.66231209e-01 5.50822198e-01 -8.67644697e-03 -3.85452896e-01 2.31027052e-01 -8.79563466e-02 9.95914936e-02 3.34181011e-01 -5.88054001e-01 -1.01130140e+00 -5.75770080e-01 6.85769841e-02 9.50523555e-01 7.60787249e-01 1.45339265e-01 1.67550504e-01 8.57957900e-01 -1.63033187e+00 4.92918521e-01 1.08775161e-01 1.16776764e+00 2.71019012e-01 1.04027748e+00 2.99453791e-02 9.45945501e-01 -7.85064042e-01 -2.36104131e-01 3.12567383e-01 -1.32358372e-02 -6.63410783e-01 5.59620380e-01 7.87962794e-01 -4.14370060e-01 -6.51442170e-01 9.22486663e-01 2.72377789e-01 7.29711205e-02 6.73075020e-01 -1.03061116e+00 -5.21908641e-01 1.74673557e-01 -7.12359011e-01 6.85533762e-01 4.17576823e-03 3.46295349e-02 1.09377670e+00 -1.19209528e+00 7.42284119e-01 1.34403980e+00 3.94775301e-01 3.64618331e-01 -1.32023132e+00 -1.98139176e-01 2.56470263e-01 1.40056565e-01 -1.45980871e+00 -3.38806838e-01 6.31173849e-01 -5.71978927e-01 9.92399752e-01 1.30592227e-01 7.31366813e-01 1.04704010e+00 3.61175627e-01 1.07804549e+00 5.20005107e-01 -1.68149814e-01 1.41651437e-01 5.65600023e-02 1.62885457e-01 9.16855872e-01 3.29798132e-01 -6.47293851e-02 -2.83148766e-01 1.49956644e-02 1.04661274e+00 3.21989745e-01 3.13761681e-01 -8.08370292e-01 -1.25140393e+00 8.89518976e-01 5.72182536e-01 1.54764071e-01 -5.87841213e-01 5.71126521e-01 3.50353360e-01 -1.10887900e-01 2.41605669e-01 3.16481054e-01 -5.72914779e-01 3.28880310e-01 -8.28872204e-01 2.71631181e-01 5.54453075e-01 1.11347890e+00 8.29454184e-01 3.93790364e-01 -1.99456498e-01 4.16017592e-01 4.16414559e-01 4.05797362e-01 5.27316689e-01 -1.21093571e+00 1.52219385e-01 8.76421392e-01 2.73621920e-02 -9.44877684e-01 -3.35803807e-01 -6.41743541e-01 -5.65033674e-01 4.13407564e-01 1.32655114e-01 2.46814042e-02 -1.13189924e+00 1.12404823e+00 3.88616085e-01 4.12296832e-01 4.09070514e-02 9.24862921e-01 8.45649779e-01 4.52246338e-01 -5.33781759e-02 1.47646964e-01 1.40260696e+00 -1.18562043e+00 -3.86373430e-01 -7.33242750e-01 4.19008955e-02 -6.39603078e-01 4.32285339e-01 -8.13476294e-02 -1.15373647e+00 -6.79771245e-01 -1.07380509e+00 -1.69444814e-01 -5.34576893e-01 4.76561606e-01 7.84842372e-01 2.60134131e-01 -7.75005281e-01 3.43195498e-01 -1.16261756e+00 -1.84641659e-01 8.28054309e-01 3.60141546e-01 -4.62701082e-01 1.17037602e-01 -3.35168332e-01 1.00056314e+00 4.36844379e-01 4.63181064e-02 -1.41965640e+00 -3.58313859e-01 -1.12422407e+00 2.58498080e-02 1.46701694e-01 -6.69741392e-01 1.17200327e+00 -1.09865189e+00 -1.31321311e+00 1.10049403e+00 -4.83953059e-02 -6.88440800e-01 3.89690757e-01 -4.42264587e-01 -1.76712081e-01 3.38915437e-01 4.00154442e-01 8.66876245e-01 1.16370070e+00 -1.14543021e+00 -9.19249237e-01 -4.17987257e-01 -1.99090362e-01 1.08205363e-01 2.65153557e-01 4.07416731e-01 -8.52628171e-01 -6.71593189e-01 4.87003982e-01 -7.59149671e-01 -6.94454789e-01 1.24454416e-01 -4.56184059e-01 -6.28652126e-02 1.25999653e+00 -4.58767116e-01 3.86249185e-01 -2.24327374e+00 4.33773220e-01 -1.21646285e-01 3.43049467e-01 1.05947450e-01 -2.37415195e-01 -3.04579347e-01 -3.80177461e-02 -3.45046312e-01 -1.06314413e-01 -5.68696737e-01 -2.60228276e-01 5.11181474e-01 -3.94485444e-01 7.81454921e-01 7.20174789e-01 1.10104227e+00 -6.05555892e-01 -6.40471578e-01 6.07400060e-01 5.53638279e-01 -6.10727072e-01 2.94206381e-01 -5.05411863e-01 2.93535739e-01 -5.04720926e-01 8.86477888e-01 5.21255136e-01 -3.85268152e-01 -1.92518935e-01 -2.38072962e-01 -1.57287851e-01 7.16732368e-02 -1.44071448e+00 1.57818997e+00 -1.39069008e-02 8.95070374e-01 6.35127649e-02 -1.04529953e+00 6.92758322e-01 -1.36654060e-02 5.24740756e-01 -4.12177265e-01 3.39919508e-01 -2.01400638e-01 -1.46332547e-01 -2.51629055e-01 4.94193286e-01 5.34592569e-01 2.05705240e-02 1.75308228e-01 5.13676584e-01 -6.68110102e-02 2.36042678e-01 1.60649270e-01 1.06957269e+00 2.54872799e-01 1.88397869e-01 -3.36263254e-02 3.41801763e-01 -1.01328820e-01 7.37112880e-01 7.92855799e-01 -1.42734915e-01 8.01524103e-01 2.34692484e-01 -9.72444594e-01 -8.86445761e-01 -1.23055410e+00 1.14122003e-01 1.35053158e+00 3.03131431e-01 -2.39605531e-01 -4.12831664e-01 -5.84632397e-01 2.42567696e-02 4.24615830e-01 -7.29320228e-01 6.87063187e-02 -7.66485631e-01 -6.85555756e-01 2.66056418e-01 9.09718573e-01 2.89933503e-01 -1.06880605e+00 -1.36956167e+00 4.22218025e-01 1.90946111e-03 -1.41088784e+00 -1.38694704e-01 7.40991414e-01 -7.55974233e-01 -1.27871644e+00 -3.89204293e-01 -9.00669217e-01 7.12115526e-01 1.04015574e-01 1.20908630e+00 -1.55828431e-01 -1.06823516e+00 2.11926654e-01 9.14768577e-02 -5.08534193e-01 -2.06162900e-01 -1.38464361e-01 -2.37015814e-01 1.86220482e-01 2.59414673e-01 -2.48879120e-01 -5.12528837e-01 2.67906606e-01 -6.07448161e-01 -2.51997560e-01 7.13362336e-01 5.63097239e-01 1.04377830e+00 -3.22845906e-01 -9.37910676e-02 -6.38738811e-01 -3.25909942e-01 -8.09581801e-02 -1.06661773e+00 1.01705037e-01 1.68809980e-01 1.03993572e-01 9.55568552e-02 -4.10755932e-01 -6.35989904e-01 8.88727248e-01 6.23158887e-02 -8.27809334e-01 -3.24097037e-01 -2.53483146e-01 -1.24155588e-01 -1.68956146e-01 5.95275283e-01 2.88881719e-01 -3.56462508e-01 -5.11348605e-01 5.54096282e-01 2.33453467e-01 9.11829114e-01 -2.30716601e-01 6.99510992e-01 7.97461331e-01 3.74733172e-02 -7.59492636e-01 -1.04056644e+00 -6.39421880e-01 -1.20942199e+00 -7.02358037e-02 1.20461130e+00 -1.16347885e+00 -5.06319463e-01 3.35525692e-01 -1.48188567e+00 -1.86693475e-01 -7.53121078e-01 3.95149559e-01 -8.46693277e-01 -9.10434499e-02 -5.59084535e-01 -6.47643566e-01 -8.80301818e-02 -1.31473374e+00 1.43578374e+00 3.08525383e-01 1.36687353e-01 -5.31404734e-01 -1.33625120e-01 3.04501373e-02 3.17741901e-01 4.42646474e-01 3.89897168e-01 -7.14658856e-01 -1.14629340e+00 -4.63333130e-01 -4.05734241e-01 1.83522046e-01 -1.65345967e-01 3.47095907e-01 -1.04591477e+00 -1.55239254e-01 -3.67273502e-02 -1.36047035e-01 1.18796396e+00 5.63452244e-01 1.31120825e+00 -2.27470130e-01 -7.05465972e-01 7.75843203e-01 1.27084804e+00 -4.69720326e-02 5.29395342e-01 2.16650680e-01 8.34936976e-01 2.88062483e-01 2.60898709e-01 3.63115460e-01 4.15426016e-01 6.10211909e-01 8.57208908e-01 -2.44663522e-01 -2.62736976e-01 1.49659470e-01 4.57492173e-02 1.96118444e-01 7.57304281e-02 7.84950182e-02 -7.45043337e-01 6.92371488e-01 -1.81929791e+00 -9.46844339e-01 1.06074408e-01 1.73517442e+00 2.31385052e-01 3.01374525e-01 1.16239570e-01 -1.19916067e-01 8.33130598e-01 1.64358169e-01 -7.78062165e-01 -2.01374143e-02 -4.12194073e-01 1.74663991e-01 6.81628108e-01 3.11077654e-01 -1.64127183e+00 1.36044693e+00 7.97594166e+00 7.63294399e-02 -8.84000361e-01 1.92800626e-01 4.17547286e-01 1.89305589e-01 4.71427172e-01 -1.63436890e-01 -9.83327866e-01 -8.47104043e-02 5.58633149e-01 8.85805860e-02 2.06522584e-01 1.38033664e+00 -4.27131206e-01 2.18443666e-02 -1.17489505e+00 1.00568688e+00 4.38910544e-01 -1.62874722e+00 1.19062372e-01 -1.44661486e-01 5.71440279e-01 6.60345018e-01 1.96593795e-02 1.05269261e-01 5.40311277e-01 -7.31611013e-01 8.55111241e-01 6.57810926e-01 2.41014749e-01 -5.06955445e-01 3.85325044e-01 6.21758439e-02 -1.29504955e+00 -3.06939125e-01 -6.27353787e-01 5.75467199e-02 -1.05456732e-01 2.01557174e-01 -7.05288887e-01 1.67274326e-02 7.42333829e-01 7.84378231e-01 -8.47772360e-01 1.17815316e+00 -1.89630941e-01 2.17927486e-01 -3.60967129e-01 2.78727114e-01 2.47485578e-01 2.06759363e-01 6.97087586e-01 1.56825638e+00 -8.23897496e-02 -1.28964499e-01 5.84920347e-01 8.98689866e-01 -9.33767557e-02 -2.02934489e-01 -4.53379303e-01 2.18147650e-01 1.57913223e-01 1.41581869e+00 -1.17099428e+00 -6.48956478e-01 -4.84048426e-01 1.34758353e+00 4.00314540e-01 2.43000895e-01 -7.55844474e-01 -3.03558886e-01 9.07375872e-01 3.92225571e-02 1.12257504e+00 -3.27756494e-01 -2.60314513e-02 -1.23576653e+00 -1.69179857e-01 -5.67400515e-01 4.97385502e-01 -7.90851712e-01 -9.83339071e-01 5.41137516e-01 -3.73619735e-01 -9.87089336e-01 -3.55817616e-01 -8.85148823e-01 -6.07133269e-01 4.19435799e-01 -1.28938067e+00 -1.21478367e+00 -2.77890265e-01 5.53636670e-01 7.55646825e-01 -2.85443962e-01 9.47228193e-01 1.81590497e-01 -7.32775033e-01 1.22778453e-01 1.15145659e-02 5.60906053e-01 8.15561935e-02 -1.32908058e+00 7.69294083e-01 9.20924544e-01 5.73173165e-01 3.11172068e-01 5.49288571e-01 -4.22037035e-01 -1.61564910e+00 -1.59077835e+00 3.24749500e-01 -6.94233119e-01 6.50680482e-01 -5.84937990e-01 -6.69262946e-01 1.32054436e+00 -9.96032804e-02 9.58598971e-01 2.78556257e-01 -2.90098757e-01 -5.22126317e-01 -5.47626130e-02 -9.57366586e-01 3.74189109e-01 7.49302745e-01 -4.44665879e-01 -6.12997472e-01 5.60644150e-01 8.76607895e-01 -8.59063447e-01 -5.08766115e-01 2.58540571e-01 4.91729409e-01 -7.43149459e-01 1.32752514e+00 -7.19140649e-01 5.09332754e-02 -5.89453757e-01 -4.60278749e-01 -8.22799683e-01 -6.11384571e-01 -2.39183277e-01 -4.97269511e-01 6.32324040e-01 2.53018796e-01 -1.33020580e-01 8.72620881e-01 8.86192247e-02 -2.30073869e-01 -4.94703323e-01 -1.13894737e+00 -3.93589646e-01 -3.62356037e-01 -3.31488550e-01 1.80230826e-01 4.98789787e-01 -8.35064471e-01 3.94255906e-01 -1.81621969e-01 6.69736445e-01 8.20379496e-01 3.45721245e-01 7.51156688e-01 -1.28070772e+00 -2.78312922e-01 -4.58251119e-01 -1.07084668e+00 -1.02115011e+00 1.12751544e-01 -6.25450492e-01 1.72939211e-01 -1.46591043e+00 1.53349414e-01 2.05751926e-01 -3.89423281e-01 4.51371253e-01 2.90663522e-02 6.03187263e-01 9.41439793e-02 -3.81632010e-03 -1.24722326e+00 3.25873107e-01 8.41141999e-01 -5.38279057e-01 -8.58491585e-02 1.66779220e-01 -4.10696656e-01 1.12053907e+00 5.08628488e-01 -4.98373419e-01 3.19039315e-01 -7.83938527e-01 -2.60562539e-01 -1.54412553e-01 7.22531736e-01 -1.34387624e+00 3.33528012e-01 7.77974958e-03 1.13582492e+00 -1.01564205e+00 5.44630945e-01 -8.51450920e-01 -1.82717443e-01 5.24383187e-01 -1.46872208e-01 9.88453105e-02 2.62409031e-01 4.46218312e-01 -4.96840589e-02 5.64377196e-02 9.89357591e-01 -4.01835740e-01 -8.76992345e-01 4.35208529e-01 -4.96818781e-01 -1.34190163e-02 1.13134837e+00 -3.27555835e-02 -1.20292213e-02 2.12082893e-01 -9.79740858e-01 4.15548533e-02 1.64566055e-01 5.85103869e-01 7.53235102e-01 -1.17294800e+00 -7.33580649e-01 5.72742224e-01 1.82983980e-01 2.45581746e-01 -1.80360124e-01 3.40736955e-01 -4.56655920e-01 2.23575100e-01 -3.55674833e-01 -1.01954746e+00 -1.14032435e+00 4.83595252e-01 6.42154455e-01 3.22576016e-02 -9.34767425e-01 1.03600764e+00 2.79073358e-01 -1.55641288e-01 5.56881368e-01 -3.81860316e-01 -1.29269749e-01 -5.26962429e-02 8.12768042e-01 3.16942126e-01 -7.48479739e-02 -1.00823057e+00 -6.41262531e-01 6.54642224e-01 -2.82388180e-01 7.32951611e-02 1.36604261e+00 4.65003811e-02 -3.60277891e-02 5.51977456e-01 1.04832518e+00 -3.44843477e-01 -1.54316568e+00 -4.08616841e-01 1.66033059e-01 -3.73641551e-01 8.17224681e-02 -4.42977786e-01 -1.15718651e+00 8.44734251e-01 6.99179888e-01 -1.37332365e-01 7.96649098e-01 4.64839041e-01 1.87980756e-01 7.55053937e-01 4.50783819e-02 -1.04059672e+00 4.77164596e-01 7.08200097e-01 8.74900639e-01 -1.26155806e+00 -5.23006171e-02 -2.57777691e-01 -6.31194651e-01 9.85257387e-01 7.40455210e-01 -6.02075458e-01 6.19214892e-01 7.54705846e-01 8.04606825e-02 -4.07377541e-01 -6.55451357e-01 -6.15831614e-01 2.28205532e-01 7.19737411e-01 1.67303905e-01 2.70172465e-03 7.14981735e-01 2.02791691e-01 2.08593518e-01 -4.55715537e-01 2.84392983e-01 8.54296207e-01 -6.38627470e-01 -5.25375247e-01 -4.35253441e-01 4.02171582e-01 -4.90639150e-01 1.97951183e-01 -3.29910368e-01 6.11958504e-01 3.60021979e-01 5.60317934e-01 5.99667728e-01 5.74505702e-02 4.43364829e-01 -1.94440037e-02 6.38868690e-01 -9.16987419e-01 -4.37291294e-01 3.06874990e-01 -4.53865469e-01 -9.86058235e-01 -3.29866767e-01 -7.96167016e-01 -1.25030529e+00 5.83982944e-01 -4.00156498e-01 -2.73721427e-01 8.72882485e-01 8.24386120e-01 3.54375929e-01 9.94076729e-01 4.97746676e-01 -1.29668760e+00 -1.29196584e-01 -7.39032030e-01 -3.23978364e-01 1.85917169e-01 7.11394370e-01 -7.19062865e-01 -9.60643291e-02 1.70562431e-01]	[9.127053260803223, 0.2579821050167084]
cbe51eb3-3394-4d60-931c-51e08e8ef4d7	adjustable-visual-appearance-for	2306.01344	null	https://arxiv.org/abs/2306.01344v1	https://arxiv.org/pdf/2306.01344v1.pdf	Adjustable Visual Appearance for Generalizable Novel View Synthesis	We present a generalizable novel view synthesis method where it is possible to modify the visual appearance of rendered views to match a target weather or lighting condition. Our method is based on a generalizable transformer architecture, trained on synthetically generated scenes under different appearance conditions. This allows for rendering novel views in a consistent manner of 3D scenes that were not included in the training set, along with the ability to (i) modify their appearance to match the target condition and (ii) smoothly interpolate between different conditions. Experiments on both real and synthetic scenes are provided including both qualitative and quantitative evaluations. Please refer to our project page for video results: https://ava-nvs.github.io/	['Fredrik Kahl', 'Marcel Büsching', 'Che-Tsung Lin', 'David Nilsson', 'Josef Bengtson']	2023-06-02	null	null	null	null	['novel-view-synthesis']	['computer-vision']	[ 2.75756538e-01 -6.97020814e-02 3.44049901e-01 -3.67678225e-01 -3.39503050e-01 -1.05016375e+00 7.61241257e-01 -5.16776800e-01 2.81471044e-01 4.61492568e-01 2.40915686e-01 -2.67196655e-01 4.45010573e-01 -6.76151335e-01 -8.91274989e-01 -3.18412632e-01 1.86536610e-01 2.10633650e-01 3.13001335e-01 -1.39979035e-01 -2.63581965e-02 8.18768620e-01 -1.77119887e+00 4.97986466e-01 4.00542319e-01 7.60125995e-01 2.58811206e-01 9.02058840e-01 4.17733759e-01 4.07538712e-01 -5.84348738e-01 -1.93492204e-01 6.87493205e-01 -3.85951251e-01 -4.05844778e-01 4.93685067e-01 9.17831838e-01 -5.79264522e-01 -2.93192357e-01 8.57026100e-01 3.88398379e-01 1.69464320e-01 4.36052173e-01 -1.33076859e+00 -8.48336458e-01 -2.10622057e-01 -4.50154036e-01 -6.92453384e-02 7.74859250e-01 4.94660795e-01 4.95474309e-01 -9.77406323e-01 9.77502704e-01 1.17716312e+00 2.73437828e-01 7.20620871e-01 -1.48555851e+00 -7.73082376e-01 2.98770994e-01 2.06360202e-02 -1.13319182e+00 -8.01023960e-01 8.96232367e-01 -4.39077139e-01 8.46938729e-01 4.99569714e-01 9.47052419e-01 1.44375551e+00 3.11825156e-01 1.95199624e-01 1.36464846e+00 -3.06789398e-01 1.37284905e-01 2.77394652e-01 -6.21542394e-01 6.47498906e-01 -1.83898270e-01 3.54136974e-01 -4.18665469e-01 3.01620234e-02 1.09735692e+00 -1.23417944e-01 -5.10759830e-01 -9.18060422e-01 -1.37734330e+00 4.51988429e-01 2.89238065e-01 -1.58141464e-01 -2.36373246e-01 4.29595597e-02 1.31665528e-01 3.78819972e-01 5.29640555e-01 5.47953427e-01 -5.28186142e-01 8.91700834e-02 -5.43593705e-01 4.53155160e-01 4.30242807e-01 1.19134164e+00 7.38189280e-01 4.55041230e-01 -9.48783830e-02 7.09900916e-01 1.95439115e-01 6.98935211e-01 1.69929028e-01 -1.52196884e+00 8.75223577e-02 3.87909979e-01 3.40029210e-01 -9.50353563e-01 -4.17156927e-02 -5.46314381e-02 -6.10999346e-01 1.03511095e+00 1.41568661e-01 -1.26848280e-01 -1.25008917e+00 1.66255379e+00 5.36510527e-01 1.16584465e-01 -1.52967066e-01 7.38804042e-01 9.74336624e-01 6.82512760e-01 -3.59901488e-01 -4.05310616e-02 1.24088907e+00 -7.36108124e-01 -6.11750066e-01 -1.93560451e-01 -8.95206630e-02 -1.00230050e+00 1.40143538e+00 3.20602924e-01 -1.40020859e+00 -7.57496178e-01 -1.10207212e+00 8.12278502e-03 -3.51252526e-01 -4.45508659e-02 4.07098025e-01 4.44039434e-01 -1.64529443e+00 4.13420439e-01 -7.28489339e-01 -5.32050669e-01 4.91004474e-02 2.38393415e-02 -5.40726125e-01 1.58640385e-01 -8.59079719e-01 8.26945424e-01 -3.97100002e-02 4.70058173e-02 -1.13380718e+00 -6.57575607e-01 -9.00293350e-01 -2.02696711e-01 1.24701984e-01 -1.06994247e+00 1.40396070e+00 -1.33068597e+00 -1.93835831e+00 1.00822568e+00 -2.51467884e-01 4.34324034e-02 5.52068412e-01 -4.26725112e-02 -5.65761328e-01 2.04816058e-01 -1.22029655e-01 8.10421348e-01 9.56581652e-01 -1.80409801e+00 -3.17270160e-01 2.24791355e-02 3.79977018e-01 4.32221383e-01 2.50320435e-01 1.24448270e-01 -5.87424934e-01 -6.98261559e-01 3.96759398e-02 -1.05608273e+00 -6.02197796e-02 5.81605852e-01 -3.55886072e-01 5.62255681e-01 1.11690676e+00 -6.57750785e-01 5.50204813e-01 -2.14625454e+00 1.71049133e-01 -7.64249125e-04 2.53741354e-01 3.36653180e-02 -1.93061069e-01 4.93856728e-01 -4.48861957e-01 3.62033658e-02 8.37454274e-02 -4.02593046e-01 -2.08745897e-01 -4.36069295e-02 -4.65934336e-01 2.85193503e-01 -1.61863323e-02 5.57019591e-01 -7.54810572e-01 -5.68125211e-02 6.95957541e-01 6.57130539e-01 -5.48171043e-01 6.18460178e-01 -2.33275846e-01 8.82872403e-01 2.84115449e-02 5.58271825e-01 7.36400247e-01 -5.89205734e-02 2.79919356e-02 -4.95099783e-01 -1.65125266e-01 3.76090467e-01 -1.28752053e+00 1.55581689e+00 -6.07599020e-01 8.26831281e-01 2.40344316e-01 -2.53205180e-01 8.36093605e-01 5.44554651e-01 3.45039904e-01 -7.15381324e-01 -1.04537196e-01 -2.28219852e-01 -3.41489047e-01 -3.05436969e-01 3.65491152e-01 -2.28805333e-01 2.72087216e-01 3.74497831e-01 -7.01239035e-02 -6.73192501e-01 6.12745285e-02 1.80049896e-01 8.08059394e-01 5.71687281e-01 1.81991085e-01 -5.24282865e-02 3.17559749e-01 -2.38145128e-01 4.85930979e-01 3.09377581e-01 1.60805089e-03 1.09131575e+00 2.07989320e-01 -6.10454440e-01 -1.48520625e+00 -1.70596457e+00 -1.02954410e-01 6.11474574e-01 1.74123853e-01 -3.11268330e-01 -3.69903445e-01 -3.45691532e-01 -3.05978507e-01 8.18940878e-01 -8.00632179e-01 2.29599290e-02 -3.21707547e-01 2.68196110e-02 1.23710550e-01 3.66748720e-01 4.76739585e-01 -1.10742080e+00 -6.89418256e-01 -2.45818019e-01 -1.58778176e-01 -1.12473083e+00 -5.10703743e-01 -9.24124494e-02 -6.07270181e-01 -8.38656604e-01 -5.83062649e-01 -5.68447590e-01 7.97791898e-01 4.08053666e-01 1.26631558e+00 -8.00016150e-02 -1.70495242e-01 5.55211902e-01 -2.65233248e-01 -3.97985846e-01 -7.31515706e-01 -5.05302846e-01 9.79779288e-02 -6.92154095e-02 -3.84219795e-01 -9.03861046e-01 -8.34657907e-01 5.51424205e-01 -8.90299022e-01 9.01797056e-01 -1.03072293e-01 5.03057301e-01 5.36368191e-01 -3.59997213e-01 -6.64300285e-03 -6.69472396e-01 1.95991054e-01 -4.82259355e-02 -8.18470240e-01 2.54941314e-01 -3.80692422e-01 -1.97613880e-01 6.63134098e-01 -3.91208500e-01 -1.23517394e+00 -7.30147120e-03 4.04171012e-02 -7.82866776e-01 -4.07238424e-01 -1.15862444e-01 -3.30066204e-01 -4.27028500e-02 6.38701499e-01 7.74508938e-02 -1.67524755e-01 -3.18690687e-01 5.27069509e-01 3.22658360e-01 6.51951075e-01 -5.28673589e-01 1.25166154e+00 6.48527682e-01 -2.41879448e-01 -4.21412766e-01 -3.47447485e-01 1.94921046e-01 -7.76113451e-01 -5.99177003e-01 7.79365838e-01 -9.50684726e-01 -3.49505275e-01 5.74400902e-01 -9.52063680e-01 -7.88027227e-01 -3.82427543e-01 3.49820048e-01 -6.67779982e-01 9.76780057e-02 -4.51049268e-01 -3.71832937e-01 -9.27472040e-02 -1.15227187e+00 1.08599067e+00 3.24633539e-01 -3.07843894e-01 -9.60769355e-01 2.09197298e-01 9.13796723e-02 4.09430563e-01 6.23226345e-01 7.19598830e-01 1.48463681e-01 -6.50096059e-01 2.53077410e-02 -1.24033496e-01 3.78659278e-01 7.14704931e-01 7.04298794e-01 -1.13424265e+00 -5.77316344e-01 -1.66534349e-01 -1.77553415e-01 2.96902746e-01 3.08147013e-01 9.73398685e-01 -2.45856509e-01 -1.08016297e-01 1.02806878e+00 1.40197837e+00 3.45012873e-01 8.31372797e-01 3.52339506e-01 6.04191124e-01 3.65313262e-01 2.51629859e-01 3.33340585e-01 2.68142402e-01 9.35780168e-01 4.42251533e-01 -5.41799903e-01 -5.12553990e-01 -4.24839258e-01 3.33379626e-01 4.91294444e-01 -3.07734191e-01 -4.68173295e-01 -7.37340450e-01 3.76215458e-01 -1.50368452e+00 -1.19373083e+00 1.07664436e-01 2.41096520e+00 6.32413924e-01 5.09890802e-02 -9.28053558e-02 -3.43192577e-01 6.75596714e-01 3.67205799e-01 -5.61865211e-01 -7.91049242e-01 -1.10887647e-01 1.93090081e-01 2.83228993e-01 5.68390012e-01 -8.15370381e-01 7.15754032e-01 7.14774036e+00 2.76847184e-02 -1.35616314e+00 -1.12471491e-01 5.05919278e-01 -2.87287235e-01 -6.61009014e-01 2.11730152e-01 -1.92758173e-01 2.43615299e-01 6.83811247e-01 -3.52582067e-01 7.02345133e-01 5.00171483e-01 5.81770301e-01 2.01889612e-02 -1.11370051e+00 7.43179321e-01 1.08820617e-01 -1.39078236e+00 3.43276292e-01 -1.05330124e-01 8.25868666e-01 -1.28904402e-01 2.74850011e-01 6.19387105e-02 5.76060474e-01 -7.99805999e-01 1.00255466e+00 5.80600142e-01 1.23230278e+00 -3.85160953e-01 -8.27007815e-02 -2.36778572e-01 -1.14617109e+00 3.38940382e-01 -3.76704410e-02 1.69431213e-02 2.70039469e-01 9.26739052e-02 -8.45325828e-01 5.67661464e-01 1.09268570e+00 7.40029454e-01 -7.56689429e-01 9.10121977e-01 -3.84736091e-01 2.90134877e-01 -1.71175987e-01 5.57923853e-01 -1.92016736e-01 -2.74446040e-01 6.78552628e-01 8.29748273e-01 5.01570702e-01 -5.55021800e-02 -4.67998311e-02 9.23477888e-01 2.76769996e-02 -1.19636744e-01 -9.59466696e-01 4.11643624e-01 2.94020355e-01 1.14605737e+00 -6.25367165e-01 -3.55840951e-01 -3.70358199e-01 1.13696396e+00 5.78122400e-02 8.08692098e-01 -1.08867514e+00 -1.45583108e-01 9.15093303e-01 4.64430720e-01 3.06462049e-01 -2.92476416e-01 -1.35543227e-01 -1.31408048e+00 1.35526165e-01 -1.05224156e+00 -6.17855880e-03 -1.68472850e+00 -1.02713990e+00 7.84959853e-01 2.71728486e-01 -1.70189559e+00 -2.97925770e-01 -4.07115728e-01 -7.08434522e-01 1.03309906e+00 -1.04127121e+00 -1.34913290e+00 -6.45898044e-01 7.67272830e-01 5.47476113e-01 -7.99706355e-02 1.02246904e+00 1.98356360e-01 -3.01299363e-01 3.71243834e-01 3.57973725e-02 -1.63646653e-01 1.02806139e+00 -1.19798946e+00 7.21506178e-01 9.38929617e-01 -5.90733886e-02 3.80486578e-01 1.11001122e+00 -3.32105279e-01 -1.09752131e+00 -1.00955391e+00 2.50524193e-01 -6.30387306e-01 3.56684655e-01 -5.55781662e-01 -8.00765991e-01 1.12112975e+00 6.28971279e-01 -5.68715185e-02 4.61107373e-01 -1.92163080e-01 -5.24445117e-01 -2.31245413e-01 -1.19609928e+00 1.05759048e+00 1.03167784e+00 -6.05685949e-01 -2.41365254e-01 3.18956047e-01 7.00306237e-01 -8.63438547e-01 -6.57666087e-01 5.33964157e-01 8.04844916e-01 -1.29322982e+00 1.07870269e+00 -4.02811646e-01 5.62455058e-01 -6.62298203e-01 -2.04793245e-01 -1.65315723e+00 -5.62119186e-01 -5.18867910e-01 1.47050964e-02 1.11173296e+00 4.31287557e-01 -8.36691678e-01 3.92827958e-01 7.98264205e-01 -1.26489148e-01 -5.55297196e-01 -6.20268941e-01 -7.15557516e-01 -1.46838039e-01 -2.08788291e-01 7.17658341e-01 7.99844086e-01 -3.53978336e-01 2.01871380e-01 -3.65312666e-01 4.35986608e-01 4.77696151e-01 3.66005212e-01 1.11845767e+00 -7.42202342e-01 -5.30144334e-01 -2.26948619e-01 -3.48457217e-01 -7.01401711e-01 -1.18113674e-01 -5.21643043e-01 -1.06330782e-01 -1.78218746e+00 8.60723928e-02 -2.47703180e-01 -6.32520318e-02 5.35673141e-01 3.38270003e-03 5.97466052e-01 3.53636116e-01 1.58568040e-01 -1.77990779e-01 5.93854010e-01 1.56593788e+00 1.81345437e-02 -2.09962100e-01 -4.75379899e-02 -5.27218759e-01 6.11218333e-01 8.82578492e-01 -1.05446048e-01 -7.74098217e-01 -6.37269676e-01 1.77359566e-01 1.58118412e-01 6.14140809e-01 -1.11498129e+00 -4.61018175e-01 -4.32854921e-01 8.01271319e-01 -3.41098249e-01 6.71078503e-01 -8.66913617e-01 8.72639179e-01 9.35734883e-02 -1.82577074e-01 5.06627023e-01 6.16303921e-01 1.90593302e-01 1.17154814e-01 2.92019457e-01 8.35117996e-01 -1.81078196e-01 -6.36497438e-01 2.53662556e-01 -3.64130527e-01 -2.09633246e-01 1.10049629e+00 -5.96723497e-01 -4.04466957e-01 -7.95718074e-01 -8.45172644e-01 -5.29462099e-02 1.32527661e+00 6.69215918e-01 7.40415573e-01 -1.47775161e+00 -6.63670897e-01 4.48082298e-01 2.62260795e-01 -1.48846149e-01 4.37035233e-01 3.03646237e-01 -8.09231162e-01 -8.15565065e-02 -5.24300694e-01 -5.89031279e-01 -1.33915401e+00 7.37711430e-01 7.12316036e-01 1.69384837e-01 -7.72300005e-01 4.03513610e-01 5.97735286e-01 -6.45782590e-01 -1.08435191e-01 -3.09907377e-01 1.48334607e-01 -5.31835139e-01 5.02910852e-01 -8.61104503e-02 2.79554930e-02 -5.71524560e-01 -2.95412511e-01 5.40778875e-01 3.16522330e-01 -3.58337343e-01 1.26994526e+00 -3.75942111e-01 2.22751066e-01 5.44693172e-01 9.84640658e-01 1.82740986e-01 -1.77243757e+00 3.25951679e-03 -9.98762131e-01 -8.69564176e-01 -1.69590622e-01 -1.00734842e+00 -1.29976249e+00 5.26989758e-01 9.43952799e-01 8.84625036e-03 1.36151266e+00 -1.66149437e-01 4.10827816e-01 1.33991567e-03 4.21671242e-01 -6.86619818e-01 5.39973974e-02 2.83159375e-01 1.37259376e+00 -9.33041275e-01 1.54052407e-01 -3.56097817e-01 -6.40942633e-01 1.06819487e+00 7.84163475e-01 -1.51132226e-01 6.76534355e-01 5.13933063e-01 5.87708533e-01 -2.95705557e-01 -9.58635807e-01 1.99977115e-01 2.80439228e-01 1.01438951e+00 4.92168754e-01 6.82109147e-02 3.30983907e-01 -3.52840900e-01 -2.88066536e-01 -2.49779537e-01 7.64114380e-01 6.55915439e-01 1.02089845e-01 -9.35605943e-01 -4.31744307e-01 2.00136155e-01 5.79668805e-02 7.06567094e-02 -3.39274406e-01 6.34758651e-01 8.78905430e-02 8.72435451e-01 2.01774731e-01 -4.06857848e-01 6.24677837e-01 -5.91079518e-02 7.42883265e-01 -7.39381790e-01 -3.89076591e-01 1.67946722e-02 1.88965082e-01 -7.77802885e-01 -4.33901787e-01 -7.21419632e-01 -8.13532352e-01 -4.46778923e-01 1.43394530e-01 -4.07303333e-01 4.96158749e-01 3.64941746e-01 4.65982527e-01 6.85114503e-01 9.24153805e-01 -1.35633111e+00 9.43100527e-02 -6.36689484e-01 -3.78317475e-01 6.44886494e-01 4.25861955e-01 -6.16983891e-01 -4.56943989e-01 6.01448357e-01]	[9.30609130859375, -2.98089337348938]
5271c2f7-6bc1-47d8-8262-20595dbe6ec6	high-dimensional-statistical-estimation-under	2202.13157	null	https://arxiv.org/abs/2202.13157v4	https://arxiv.org/pdf/2202.13157v4.pdf	High Dimensional Statistical Estimation under Uniformly Dithered One-bit Quantization	In this paper, we propose a uniformly dithered 1-bit quantization scheme for high-dimensional statistical estimation. The scheme contains truncation, dithering, and quantization as typical steps. As canonical examples, the quantization scheme is applied to the estimation problems of sparse covariance matrix estimation, sparse linear regression (i.e., compressed sensing), and matrix completion. We study both sub-Gaussian and heavy-tailed regimes, where the underlying distribution of heavy-tailed data is assumed to have bounded moments of some order. We propose new estimators based on 1-bit quantized data. In sub-Gaussian regime, our estimators achieve near minimax rates, indicating that our quantization scheme costs very little. In heavy-tailed regime, while the rates of our estimators become essentially slower, these results are either the first ones in an 1-bit quantized and heavy-tailed setting, or already improve on existing comparable results from some respect. Under the observations in our setting, the rates are almost tight in compressed sensing and matrix completion. Our 1-bit compressed sensing results feature general sensing vector that is sub-Gaussian or even heavy-tailed. We also first investigate a novel setting where both the covariate and response are quantized. In addition, our approach to 1-bit matrix completion does not rely on likelihood and represent the first method robust to pre-quantization noise with unknown distribution. Experimental results on synthetic data are presented to support our theoretical analysis.	['Di Wang', 'Michael K. Ng', 'Cheng-Long Wang', 'Junren Chen']	2022-02-26	null	null	null	null	['low-rank-matrix-completion']	['methodology']	[ 7.65553892e-01 1.45669252e-01 -4.40900475e-01 -2.67763555e-01 -1.27386570e+00 -3.47600251e-01 2.64747292e-01 1.35132149e-01 -3.58073652e-01 8.43815863e-01 3.62747729e-01 -2.27757409e-01 -2.83479571e-01 -5.25730312e-01 -1.00053716e+00 -9.95590627e-01 -3.70098531e-01 3.85145187e-01 -1.59698457e-01 1.86214298e-02 1.50723726e-01 5.77387735e-02 -1.12564564e+00 -3.17769974e-01 5.67054570e-01 1.18631864e+00 6.43376261e-02 9.36889410e-01 4.94664192e-01 1.67632207e-01 -6.09114021e-02 -3.08974594e-01 6.60617471e-01 -1.80200130e-01 -1.44570082e-01 2.57678211e-01 3.83103371e-01 -3.45957071e-01 -4.60149050e-01 1.54841423e+00 5.97563624e-01 -1.59101844e-01 8.15172672e-01 -8.99335980e-01 -5.95796645e-01 9.37750399e-01 -8.80057454e-01 2.68138424e-02 4.11040992e-01 -3.95419151e-01 9.95041549e-01 -9.26552474e-01 2.03115433e-01 1.37415886e+00 8.72606277e-01 1.36107221e-01 -1.23577166e+00 -7.74671137e-01 -2.63000280e-01 -1.59739032e-01 -1.85635352e+00 -9.05446947e-01 4.29898441e-01 -5.53021550e-01 8.78333002e-02 1.78063661e-01 1.07506357e-01 8.70231509e-01 1.65440932e-01 6.90442979e-01 9.62146521e-01 -4.91213500e-01 6.76983595e-01 -2.47262083e-02 -4.57704365e-02 3.34090322e-01 8.84798348e-01 2.19569847e-01 -5.64410508e-01 -6.37665927e-01 5.65914392e-01 3.03796530e-01 -4.91553307e-01 -4.34184253e-01 -1.32761049e+00 1.10668147e+00 -2.28740633e-01 7.61509538e-02 -6.77962959e-01 4.88823712e-01 2.29823232e-01 4.42708671e-01 3.70636821e-01 -3.64456415e-01 -2.90917605e-01 -1.51930138e-01 -1.31060672e+00 3.04744035e-01 9.30917740e-01 1.32603800e+00 8.14089954e-01 1.68151692e-01 -4.01326180e-01 5.13683975e-01 3.36045146e-01 1.17498446e+00 4.10858572e-01 -9.04852450e-01 7.73925245e-01 -4.39234436e-01 4.50143635e-01 -1.12056804e+00 -1.04564011e-01 -5.46653390e-01 -1.61110926e+00 -5.27946174e-01 3.48816931e-01 -4.08979475e-01 -6.15050972e-01 1.90851414e+00 2.56878525e-01 3.14961135e-01 1.76278964e-01 8.94286275e-01 -8.14155489e-02 4.59907204e-01 -4.63153690e-01 -7.58144677e-01 1.38173056e+00 -1.02740377e-01 -1.12587786e+00 1.65274870e-02 5.69651067e-01 -6.34696662e-01 6.74146414e-01 6.16831362e-01 -1.09458673e+00 -1.91673115e-01 -1.00045347e+00 2.79653907e-01 1.42707720e-01 -1.09384969e-01 5.18917918e-01 1.04046679e+00 -9.73085403e-01 4.94211227e-01 -7.64104605e-01 -6.61359280e-02 3.45320612e-01 2.73959577e-01 -2.59566069e-01 -4.37835217e-01 -1.15148723e+00 5.28923981e-02 2.98814118e-01 -2.93813616e-01 -7.38335073e-01 -6.01563454e-01 -9.83637333e-01 1.72993451e-01 3.83599311e-01 -6.05068207e-01 1.20732141e+00 -3.19646716e-01 -1.18096781e+00 3.72247487e-01 -5.34626603e-01 -7.95934916e-01 2.21976086e-01 -2.50901639e-01 -1.80192143e-01 1.14093810e-01 9.96663049e-02 -1.50161192e-01 1.27528167e+00 -6.59910679e-01 -3.15199822e-01 -5.59358716e-01 -6.34285867e-01 -1.67501435e-01 -3.73781085e-01 -3.29164654e-01 -2.35405937e-01 -9.12905753e-01 4.16138470e-01 -9.18313205e-01 -5.47729611e-01 7.15748742e-02 -5.67298889e-01 2.13837296e-01 5.33266068e-01 -3.71612221e-01 1.42352355e+00 -2.45251727e+00 -9.62825045e-02 4.21561360e-01 1.27550125e-01 -2.10049704e-01 1.11342378e-01 7.52597749e-01 -2.83412933e-02 1.10151790e-01 -6.35061383e-01 -8.04422796e-01 3.12094480e-01 1.77398786e-01 -4.79665250e-01 1.17240572e+00 -2.37636849e-01 5.36216080e-01 -8.41489315e-01 -4.16657835e-01 -7.04318956e-02 4.04498428e-01 -8.58137488e-01 -2.36336887e-02 1.80417508e-01 2.40370706e-01 -5.27555883e-01 8.00101399e-01 1.08605933e+00 -4.86859053e-01 8.93082693e-02 -2.55647868e-01 2.12511301e-01 -1.45958737e-01 -1.80592704e+00 1.74051046e+00 -1.63453326e-01 3.33702207e-01 5.90441108e-01 -1.28440416e+00 6.10176802e-01 5.29993474e-01 3.31506193e-01 -2.86410451e-01 1.50877893e-01 3.35521698e-01 -2.89015651e-01 -1.97611853e-01 6.81963384e-01 -5.34605742e-01 -3.93133372e-01 3.98097426e-01 -2.34998941e-01 -1.24865077e-01 -1.44947309e-03 4.32804108e-01 1.07515383e+00 -6.71988308e-01 9.79801536e-01 -3.48458409e-01 4.56904769e-02 -7.85352826e-01 6.01419270e-01 1.25276089e+00 -3.45085040e-02 7.71646857e-01 2.79811382e-01 4.28192407e-01 -1.21566749e+00 -8.21029007e-01 -5.81356823e-01 7.74429798e-01 -2.46933103e-02 -6.71155572e-01 -4.76480573e-01 2.03362629e-02 3.05808336e-01 4.28873301e-01 -5.57125330e-01 1.20906174e-01 1.00164123e-01 -9.42471445e-01 5.10914087e-01 1.67696506e-01 2.05932647e-01 -3.10504274e-03 -1.90077096e-01 3.45368177e-01 8.52446482e-02 -1.42239249e+00 -7.20810473e-01 2.90931672e-01 -1.00975919e+00 -6.98549688e-01 -1.03342628e+00 -2.72595555e-01 4.26132202e-01 3.64711136e-01 6.35992825e-01 -2.54978120e-01 7.67294019e-02 5.10246396e-01 -3.50839585e-01 -1.32104933e-01 1.37708988e-02 -2.85131186e-01 4.98499513e-01 5.12545884e-01 1.65517569e-01 -9.39211726e-01 -8.40960383e-01 4.52681147e-02 -1.25073206e+00 -4.81316596e-01 7.82734811e-01 8.82183850e-01 7.82774210e-01 1.38406128e-01 3.88196290e-01 -9.28966582e-01 5.72832048e-01 -9.36757743e-01 -7.23835230e-01 -1.63434058e-01 -5.84398091e-01 3.04728240e-01 6.12676203e-01 -5.79803765e-01 -4.02084023e-01 3.94031972e-01 1.24931127e-01 -5.44744015e-01 2.21742112e-02 6.07974350e-01 -2.75871288e-02 -6.09552488e-02 5.61151564e-01 3.68437767e-01 -1.08984485e-01 -6.12862408e-01 4.87091392e-01 1.10092115e+00 6.23669147e-01 -6.22788131e-01 1.11240935e+00 7.41251469e-01 3.37944776e-01 -9.60624397e-01 -6.99622333e-01 -6.71171308e-01 -3.41521382e-01 6.56830668e-01 2.97673434e-01 -1.32146537e+00 -7.95824289e-01 1.65732294e-01 -8.53792071e-01 -6.37316406e-02 -4.30581301e-01 8.40428472e-01 -8.24471712e-01 9.12572145e-01 -3.84313941e-01 -1.39110970e+00 -2.54144281e-01 -9.06892121e-01 1.51287711e+00 -1.83783695e-01 2.18850411e-02 -9.70661402e-01 1.70570552e-01 -9.19131413e-02 4.70778584e-01 1.87096342e-01 4.23011988e-01 -6.26622021e-01 -4.04534638e-01 -4.43465859e-01 -1.59652546e-01 1.93045676e-01 1.63964018e-01 -7.04712570e-01 -7.20269799e-01 -7.30365694e-01 1.17752455e-01 -4.33322817e-01 7.91234970e-01 6.95732355e-01 1.32771432e+00 -6.44009233e-01 -3.00521106e-01 8.36007535e-01 1.44926763e+00 -5.00810564e-01 4.75045502e-01 -3.32645297e-01 2.09259823e-01 8.28139782e-02 6.93481624e-01 1.43186057e+00 2.95324266e-01 6.72481716e-01 3.43649745e-01 1.68702245e-01 1.56257153e-01 -2.26719067e-01 3.76897901e-01 9.76051748e-01 4.56707686e-01 -2.63068289e-01 -4.84840721e-01 6.75361633e-01 -1.74881816e+00 -9.29554045e-01 -2.18517736e-01 2.70062947e+00 1.20857632e+00 -6.14948794e-02 1.74511168e-02 3.47182423e-01 7.51449168e-01 1.30294681e-01 -5.58490574e-01 -2.72590164e-02 -4.18415368e-01 2.63089895e-01 1.20327985e+00 5.64319789e-01 -1.17648339e+00 4.62881953e-01 6.85077333e+00 1.15953255e+00 -6.68838501e-01 2.29612976e-01 4.25828993e-01 8.58554393e-02 -2.77543008e-01 5.71072921e-02 -1.06664300e+00 7.85072982e-01 1.14012742e+00 -3.81480902e-01 4.69298691e-01 7.58258700e-01 3.11783046e-01 -2.16057420e-01 -1.21244431e+00 1.47720647e+00 -4.44141729e-03 -1.00853348e+00 -1.85619026e-01 4.64777291e-01 9.51813400e-01 3.15199569e-02 3.36139292e-01 -3.98250222e-02 4.19034928e-01 -9.77962971e-01 3.76420349e-01 5.57263076e-01 1.32275486e+00 -3.80495816e-01 6.98200703e-01 5.47214329e-01 -1.13037360e+00 -5.94823472e-02 -7.94388473e-01 -1.74794912e-01 4.10063088e-01 1.35829592e+00 -4.59370822e-01 4.48936671e-01 4.23307478e-01 6.80142105e-01 -1.17012441e-01 1.14943206e+00 3.04190844e-01 9.91851151e-01 -8.14506829e-01 1.13892525e-01 6.19391864e-03 -1.85446620e-01 6.03365481e-01 1.28891289e+00 8.44790459e-01 3.52897465e-01 2.95822352e-01 3.77600253e-01 -1.27064764e-01 1.08117610e-01 -7.96554267e-01 -6.24050386e-02 8.39302480e-01 6.54851198e-01 -1.14525400e-01 -5.78581452e-01 -5.38810968e-01 8.63115370e-01 -1.54863507e-01 4.99083698e-01 -4.34866697e-01 -5.59219241e-01 5.37257552e-01 1.70274898e-01 9.18922961e-01 -4.43758607e-01 -2.49799564e-01 -1.26014435e+00 -1.07259281e-01 -9.66157138e-01 3.20513070e-01 -1.82244912e-01 -1.38302553e+00 -2.59196401e-01 1.35970652e-01 -1.21127796e+00 -5.23331881e-01 -2.38102406e-01 -4.31768456e-03 7.44854748e-01 -1.60978317e+00 -4.17141080e-01 1.83681458e-01 9.34203982e-01 2.34617472e-01 -3.67807373e-02 7.03878462e-01 3.44619781e-01 -2.24756584e-01 8.24090838e-01 9.21562314e-01 -1.13401309e-01 6.04493320e-01 -1.09042168e+00 1.23322578e-02 7.96258271e-01 -1.58649404e-02 6.75005317e-01 9.84386504e-01 -7.13838756e-01 -1.87809443e+00 -1.00031328e+00 6.61811829e-01 -1.74591467e-02 8.39464068e-01 -5.60524583e-01 -7.61535645e-01 6.75723791e-01 -2.36451238e-01 3.34027916e-01 9.67608392e-01 -5.42010441e-02 -2.30237260e-01 6.21952908e-03 -1.28823006e+00 1.73756018e-01 7.94207573e-01 -5.26541173e-01 -4.07285571e-01 7.37093329e-01 6.10870302e-01 -2.65688270e-01 -1.09488273e+00 3.89045596e-01 4.34952945e-01 -7.12639213e-01 9.50572729e-01 -3.11227262e-01 -5.79685196e-02 -1.62645131e-01 -1.12939870e+00 -9.23994422e-01 -2.86441356e-01 -1.32210910e+00 -5.34774125e-01 8.41750443e-01 9.93193910e-02 -4.59642589e-01 8.29702914e-01 2.89446801e-01 3.13533783e-01 -3.81677657e-01 -1.18667972e+00 -8.89381289e-01 -3.04145422e-02 -6.18129551e-01 4.47083265e-01 7.44361997e-01 -8.89213234e-02 9.20240954e-02 -1.03260136e+00 5.42561054e-01 1.36187613e+00 -8.93488750e-02 8.59685004e-01 -1.15698099e+00 -7.81707227e-01 5.80624864e-02 -5.60507417e-01 -1.75240111e+00 2.08415370e-02 -6.83497310e-01 9.49396342e-02 -7.24891961e-01 4.26770985e-01 -4.63789016e-01 -2.09210619e-01 7.21233562e-02 -1.28035769e-01 3.39067280e-01 -9.51430425e-02 2.39674479e-01 -7.09178150e-01 8.81677508e-01 8.70174170e-01 -1.27289491e-02 1.35510966e-01 3.63910139e-01 -7.97009885e-01 5.07942379e-01 6.51298165e-01 -6.59311891e-01 -3.89040172e-01 -1.53705440e-02 3.45779240e-01 5.84563971e-01 2.16691807e-01 -9.40784693e-01 4.31400418e-01 -1.00632422e-01 5.67367114e-02 -6.94715500e-01 5.66259503e-01 -8.45601320e-01 5.49877845e-02 5.34895480e-01 -2.88254529e-01 -3.68385494e-01 -2.56548256e-01 1.17800438e+00 -7.63709918e-02 -2.67626077e-01 7.97076464e-01 2.38643959e-01 1.09799467e-02 5.98193228e-01 -4.07342613e-01 3.13034624e-01 5.93214512e-01 -2.03313500e-01 2.20961377e-01 -1.09856486e+00 -7.61531830e-01 9.91799161e-02 3.64734232e-01 -4.46155280e-01 6.91507638e-01 -1.39224458e+00 -1.00612545e+00 3.22926342e-01 -3.85858081e-02 -1.31913766e-01 1.74499899e-01 1.08685303e+00 2.69338012e-01 6.54419601e-01 5.99773169e-01 -7.73168981e-01 -8.94269943e-01 6.35674238e-01 -2.48864159e-01 -6.68055266e-02 -3.77937526e-01 6.11426532e-01 2.54797637e-01 -2.21323241e-02 5.51977515e-01 -3.84409070e-01 4.03114885e-01 -2.31926307e-01 8.37553799e-01 2.19609097e-01 -4.97137941e-02 -5.15241623e-01 -4.54363748e-02 7.81771123e-01 5.99218085e-02 -2.80588388e-01 1.16079283e+00 -5.35352290e-01 1.50396422e-01 5.94367087e-01 1.38778901e+00 4.79323804e-01 -1.17840326e+00 -8.01591039e-01 -9.77555886e-02 -6.96725607e-01 1.38328433e-01 -4.60465290e-02 -8.34390640e-01 8.27132761e-01 5.56601405e-01 2.23732308e-01 1.04421496e+00 2.65327543e-02 7.21636891e-01 5.51883996e-01 5.78983247e-01 -6.82697952e-01 -2.10247934e-01 3.32028091e-01 7.21863210e-01 -1.24712718e+00 3.03359002e-01 -3.98281485e-01 -1.99478731e-01 8.05860817e-01 -3.93306524e-01 -1.08628221e-01 1.01274323e+00 3.98283809e-01 -6.39961600e-01 1.23146161e-01 -7.69354284e-01 -1.40523687e-01 1.64682254e-01 7.49207079e-01 3.13824773e-01 2.30811134e-01 -3.37834358e-01 7.18394041e-01 -4.35494661e-01 2.84831394e-02 7.21773446e-01 8.28503311e-01 -7.52047658e-01 -9.51951146e-01 -8.02540302e-01 6.70020759e-01 -7.55706668e-01 -4.65880603e-01 2.33828112e-01 4.26831692e-01 -4.18428659e-01 1.03309464e+00 -1.79783806e-01 -1.21599093e-01 3.03980103e-03 -1.59636751e-01 1.76737115e-01 -5.26991725e-01 2.31443748e-01 3.32716107e-01 -2.50555784e-01 -6.23106003e-01 -3.01367402e-01 -8.92541766e-01 -8.08030546e-01 -5.39454341e-01 -4.52923864e-01 3.14750135e-01 7.09413886e-01 6.83742225e-01 3.97685796e-01 -8.99442732e-02 8.15794647e-01 -6.75574541e-01 -1.53155375e+00 -1.01005161e+00 -1.22832191e+00 2.58920193e-01 8.35734844e-01 -5.48039556e-01 -7.48185337e-01 3.29272114e-02]	[6.931488037109375, 4.529102802276611]
71d29a30-7eaf-4261-a64d-2348ad7ba9ec	majority-rule-better-patching-via-self	2306.00108	null	https://arxiv.org/abs/2306.00108v1	https://arxiv.org/pdf/2306.00108v1.pdf	Majority Rule: better patching via Self-Consistency	Large Language models (LLMs) can be induced to solve non-trivial problems with "few-shot" prompts including illustrative problem-solution examples. Now if the few-shots also include "chain of thought" (CoT) explanations, which are of the form problem-explanation-solution, LLMs will generate a "explained" solution, and perform even better. Recently an exciting, substantially better technique, self-consistency [1] (S-C) has emerged, based on the intuition that there are many plausible explanations for the right solution; when the LLM is sampled repeatedly to generate a pool of explanation-solution pairs, for a given problem, the most frequently occurring solutions in the pool (ignoring the explanations) tend to be even more likely to be correct! Unfortunately, the use of this highly-performant S-C (or even CoT) approach in software engineering settings is hampered by the lack of explanations; most software datasets lack explanations. In this paper, we describe an application of the S-C approach to program repair, using the commit log on the fix as the explanation, only in the illustrative few-shots. We achieve state-of-the art results, beating previous approaches to prompting-based program repair, on the MODIT dataset; we also find evidence suggesting that the correct commit messages are helping the LLM learn to produce better patches.	['Premkumar Devanbu', 'Toufique Ahmed']	2023-05-31	null	null	null	null	['program-repair', 'program-repair']	['computer-code', 'reasoning']	[ 0.23314472 0.6641451 -0.39493126 -0.23927633 -1.092112 -0.27668485 0.40382552 0.4068613 0.46037173 0.51211786 0.39492947 -0.7038273 -0.31369945 -0.42073566 -1.0097634 -0.2724784 -0.03994587 0.47643995 0.12624148 -0.42110822 0.8146838 -0.27457875 -1.84366 0.72156197 0.9883091 -0.04655772 0.43887624 0.9882427 -0.42383057 1.1611121 -0.63160366 -0.15699625 0.02169286 -0.68208313 -1.2948161 -0.02586853 0.47566855 0.03202729 0.3101923 0.94161594 0.07490341 0.10613974 0.27297854 -1.4635453 -0.86537176 1.184103 -0.747584 0.09119942 0.8226748 0.31378186 1.1573133 -0.86612856 0.7766698 1.3905509 0.6266945 0.879234 -1.5452954 -0.40365306 0.26174784 0.29488912 -0.9297402 -0.09461165 0.42515987 -0.38492334 1.6250355 0.5341643 0.16752271 0.88763005 0.56189555 0.6019695 0.9221626 -0.8889652 0.22892082 0.29343945 0.6505624 0.80071974 0.17032114 0.3142939 -0.7473183 -0.6787284 0.13789028 0.0666066 -0.28321743 -0.02147653 -1.0161842 0.9100811 0.14741749 0.6255738 -0.16007139 0.45702034 0.31914198 0.69232875 0.31466767 1.0740304 -0.74575025 -0.35294324 -0.7397227 0.680004 1.0910987 1.0294247 1.0471922 0.01022747 -0.19075857 0.4931755 0.11345355 -0.12736586 0.6764712 -1.1586677 0.4074551 0.7526122 0.14116876 -0.74643767 -0.2898392 -0.35733283 -0.22769353 0.21353255 0.22099155 0.08545443 -0.50859416 1.9172633 0.05400121 0.17443854 0.08849312 0.7670468 0.5378673 0.5901723 0.03041552 -0.37078688 1.0107763 -1.1720376 -0.39329198 -0.8090925 1.143904 -0.7938235 1.5307763 0.48543903 -1.1050361 -0.54242593 -0.8726077 0.18088542 0.11350597 -0.2980261 0.91430867 0.24058583 -1.1781783 0.8386676 -0.34552857 -0.5708472 -0.15209742 0.0984161 -0.30611724 -0.4448623 -0.57300407 0.98463285 0.11444095 -0.5156666 -1.0994208 -0.99501395 -0.8359016 0.32963604 0.6615009 -0.5985038 1.6447202 -1.0429082 -0.822338 0.61387026 -0.53443563 -0.346173 -0.08880664 -0.34814405 -0.07653531 -0.4065374 0.41216618 0.4719166 0.7927684 -1.5074973 -0.33048803 0.03953037 0.23973897 -0.53920984 0.05327804 0.3478751 0.11063143 -0.44063026 0.10222916 -0.903207 -0.57737285 -0.55523616 -0.4568762 -0.5743618 0.3438219 -0.6284166 1.5453641 -2.0812166 0.4778486 -0.01704666 0.46935007 -0.14047219 -0.5899758 0.84130025 -0.6490641 0.48795465 -0.310603 -0.49095106 0.18348798 0.3618958 -0.7509159 0.11523562 0.38662574 0.7533079 -1.0576538 -0.3089586 -0.14550884 -0.2941985 -1.0366305 0.47878385 -0.9632922 0.11775737 0.00821125 0.45470646 0.30783975 -0.5340381 0.16359632 0.6017912 -0.12340216 0.38576373 -0.9799381 1.6069465 -0.58531374 0.62010413 -0.40767044 -0.73169684 0.8707315 0.34757507 -0.16142435 -0.43327802 -0.3037819 0.44990882 0.29170182 -1.0087576 0.53127 -0.09253897 -0.16034897 0.8541205 -0.12294554 -0.13210528 0.24569863 0.73639387 1.6863012 -0.09587378 0.42329508 -0.23801436 0.19413944 0.48286363 0.6085514 1.2026485 0.34917596 0.7526275 0.8535212 -0.41050684 -0.9079103 -0.52609175 0.3373427 1.0517699 -0.17642112 -1.0754926 -0.69966847 -0.76472336 -0.08253519 1.4359462 -0.57791793 -0.34226814 -0.5210133 -0.23393993 0.16545182 0.40045267 -0.23861855 -1.1300406 -0.6307728 0.42424497 -0.2341921 -0.40565744 -0.49138066 0.47133914 -0.7767859 -1.3267733 -0.09575664 -0.5760439 0.9591109 0.5435812 1.6137756 1.2756014 -0.28493986 0.49980977 -0.54022765 -0.10781791 -0.9730169 -0.22503255 -0.13081214 -0.67772186 0.3045175 -0.6061455 0.04291696 0.06542181 -0.8013224 0.08339738 0.49223167 1.0086904 0.16916488 -0.01336755 0.55267626 -1.381966 0.7155888 -1.0173408 -0.28065845 0.39318848 -0.92658585 0.48025754 0.7976314 -0.71183515 -0.91303045 -0.36938173 0.18979035 -0.41385996 -0.2482486 0.8032145 0.30946165 -0.01800939 1.2412422 0.05071886 -0.2635188 -0.56278414 0.30888695 0.1207652 0.5248122 -0.9307192 0.8012852 -0.31203026 -0.33528662 -0.33084813 -0.7769786 -0.2823428 0.2316757 0.05071768 0.359821 -0.44039425 -0.3402778 -0.21662451 -1.7367276 -0.48304787 -0.31988946 0.09891421 -0.62842 0.40676263 -0.48867542 -0.9133896 -0.05405028 -1.2874134 0.96110755 0.31025314 -1.0987731 -0.74135923 0.26126316 0.19102687 0.62057924 0.08666344 1.8512462 -0.7861864 -0.7582325 -0.1147299 0.1286288 -0.03366653 -0.2169007 0.11178657 -0.63437074 -0.18709715 0.23478955 -0.4158494 0.45032188 0.12129538 1.0456892 -0.7321921 -0.38508597 -0.01861518 1.5309047 -0.41105908 0.5787731 0.2113435 0.34892455 0.77676713 0.8304779 0.4529966 0.4053024 0.5223441 0.51571685 0.17764208 -0.24408387 -0.3381493 0.6088426 0.7817192 0.37592202 -0.08745183 -1.1105752 0.83838296 -2.2435415 -0.9702155 -0.72396034 2.0600076 0.97836775 0.13570976 -0.29415864 0.05291947 0.42317897 -0.17373136 -0.35366264 -0.8251756 0.22255468 0.38967508 -0.17169245 0.8967917 -0.13988642 0.7302695 6.6840925 0.6848852 -0.7170197 0.2128301 0.16943723 0.07829048 -0.9018498 0.8043892 -0.70044607 0.28176513 1.1748103 -0.38153833 0.7161841 1.1524171 0.0362024 -0.50998837 -1.6038834 0.48857525 0.14094634 -1.5777252 -0.23696792 -0.30579504 0.9742834 -0.26599127 -0.13167359 0.6732547 0.545329 -1.0779719 0.7531446 0.44344756 0.20382991 -0.47928745 0.6038174 0.9778796 -0.80678916 -0.3731818 -0.38613406 -0.44723728 -0.1677337 0.4898552 -1.1065989 0.34442127 0.63451713 0.5059871 -0.8870194 0.96136916 -0.4618389 0.66347146 0.16004007 -0.07578056 -0.03373725 0.45564613 0.6787235 1.0787553 0.3375988 0.00777601 0.34658164 1.3952327 0.39429086 -0.27648172 -0.6179713 -0.05535642 0.58339053 0.9900663 -0.42200994 -0.48388886 -0.38504484 0.52409583 0.5049648 0.24786286 -0.72186846 -0.13164419 0.45946464 0.2031024 -0.1047456 0.04468488 -0.50779504 -0.94591063 0.06392957 -1.6960055 0.29175925 -1.1404817 -1.2491713 0.44193918 0.19211268 -0.9255003 -0.6872689 -0.04970856 -1.1397163 0.9555677 -1.3054202 -0.59508765 -0.24970564 0.13587472 1.125395 0.01582628 0.9087093 -0.13165982 -0.29223284 0.36397052 -0.58420897 -0.86936325 0.7350902 -1.5095772 0.5365598 1.0815821 0.22091927 1.3726423 1.3837813 -0.9339835 -1.6503185 -0.81652266 1.3799398 -0.7216045 0.6921038 -0.04828477 -1.4491494 0.88087213 0.31404972 -0.38681823 0.43331182 0.36725876 -0.50767887 0.42794067 -0.97094864 0.7014734 0.90409416 -0.60316956 -0.8142577 0.79225206 1.1915689 -0.3482115 -0.38381183 -0.05708861 -0.13347267 -1.2013808 0.5968005 -0.9770496 1.1411312 -0.4956468 -0.24486062 -1.3318776 -0.31360984 -0.9918673 -0.22013408 1.3659185 0.64168584 -0.47140652 0.5186548 0.8920589 -0.48567504 -0.70288247 -0.61373043 -0.6700905 -0.15841979 -0.650386 0.6090054 0.8346062 0.5872894 0.22422932 -0.4584015 0.29827195 0.46432945 0.306314 1.0361323 -1.0806937 -1.1097014 -0.09803629 0.27947563 -0.79207313 0.473504 -1.12486 0.4323582 -1.3344145 0.57370925 -0.33715206 0.2991606 0.8096062 -0.4966846 -0.47414175 0.22163635 0.21208234 -0.67242986 0.06639181 0.65977603 -0.03487377 -0.15258974 -0.18391442 -1.0620373 0.7121868 0.42943004 -1.0871291 -0.29002547 -0.49733984 0.6494911 0.5946678 0.603334 -0.7318566 0.4188446 -0.30708852 -0.36788297 -0.07539461 -0.19869818 -0.5730415 0.5907609 0.8189788 -0.8314674 0.52393395 0.26848483 0.56567305 0.02159896 -0.9186065 0.42613342 -0.40939894 -0.7490423 -0.32161573 -0.3916011 0.04889975 0.78883976 -0.13449211 -0.8900665 -0.25929874 -0.401178 0.25261885 0.7170362 0.6416353 0.6225969 -0.9951367 -0.5883351 0.1027385 0.40877497 -0.19471331 0.24184522 0.9178759 0.0471512 0.15412597 0.27034113 -0.6851687 -1.1917082 0.7208145 0.01904448 -0.34946114 -0.7795166 0.9189234 0.10224303 -0.48653767 0.13530189 -0.37817237 0.28039387 -0.59314775 0.68243206 0.24554266 0.0086634 0.26895648 -0.3014174 0.31819472 -0.24133193 0.15572874 1.5506995 0.26319265 -0.5560111 0.55721927 0.7416112 0.0608313 -0.88861674 -0.19715938 0.5718639 -0.80613524 -0.4070428 -0.8995777 -0.6420678 0.71968544 0.0296955 0.55360943 0.63931555 0.37388465 0.4330467 0.28428108 0.6579033 -0.61734074 0.49596417 0.44452465 1.167844 -1.1285962 -0.30610144 -0.28673694 -0.5319863 1.1652639 0.98198646 -0.14674059 -0.11950766 0.43867978 -0.2599119 -0.40609965 -1.5483183 0.31636962 -0.19578205 0.642379 0.5887023 -0.14250231 -0.3139625 0.99151653 -0.22003366 -0.0844275 1.0309579 1.0007731 -0.59632367 -1.3935893 -0.63983786 0.44686043 -0.04980076 -0.25112957 -0.4002933 0.7233162 0.03667453 1.2107493 -0.39120987 -0.4385674 0.2571837 0.18193972 0.41245946 -1.3591241 -1.1512892 -0.3870319 0.19684938 -0.9275521 0.0695703 -0.39539498 -1.4959527 -0.70231235 -0.5519445 0.31084606 0.2907543 1.2716668 0.4723894 0.5936657 0.43576652 -0.7888125 -0.9163778 -0.6980017 -0.14991187 0.41315192 0.46543664 -0.38203612 -0.68365896 -0.01096352]	[7.716716766357422, 7.733617782592773]
b939e5e4-6d43-4681-bf28-d0986a327f30	does-my-multimodal-model-learn-cross-modal	2010.06572	null	https://arxiv.org/abs/2010.06572v1	https://arxiv.org/pdf/2010.06572v1.pdf	Does my multimodal model learn cross-modal interactions? It's harder to tell than you might think!	Modeling expressive cross-modal interactions seems crucial in multimodal tasks, such as visual question answering. However, sometimes high-performing black-box algorithms turn out to be mostly exploiting unimodal signals in the data. We propose a new diagnostic tool, empirical multimodally-additive function projection (EMAP), for isolating whether or not cross-modal interactions improve performance for a given model on a given task. This function projection modifies model predictions so that cross-modal interactions are eliminated, isolating the additive, unimodal structure. For seven image+text classification tasks (on each of which we set new state-of-the-art benchmarks), we find that, in many cases, removing cross-modal interactions results in little to no performance degradation. Surprisingly, this holds even when expressive models, with capacity to consider interactions, otherwise outperform less expressive models; thus, performance improvements, even when present, often cannot be attributed to consideration of cross-modal feature interactions. We hence recommend that researchers in multimodal machine learning report the performance not only of unimodal baselines, but also the EMAP of their best-performing model.	['Lillian Lee', 'Jack Hessel']	2020-10-13	null	https://aclanthology.org/2020.emnlp-main.62	https://aclanthology.org/2020.emnlp-main.62.pdf	emnlp-2020-11	['image-text-classification']	['miscellaneous']	[ 4.38914955e-01 6.81644753e-02 -2.13587403e-01 -2.49517500e-01 -9.48235750e-01 -8.08475673e-01 1.14088571e+00 7.36930296e-02 -3.62342775e-01 5.52600861e-01 4.94881213e-01 -5.35244465e-01 -1.15694746e-01 -1.93997234e-01 -8.79580855e-01 -9.29529011e-01 1.08216092e-01 5.16991317e-01 -2.69426346e-01 -6.86207786e-02 7.41605759e-02 1.17577769e-01 -1.80027890e+00 9.80916560e-01 6.75972223e-01 7.67392337e-01 -2.44194493e-01 7.85840333e-01 -2.21271977e-01 8.04323673e-01 -2.94309914e-01 -7.68255830e-01 -1.32363841e-01 -4.92268920e-01 -9.13772166e-01 1.29773170e-02 7.85661340e-01 -1.99989811e-01 -2.08714709e-01 7.79520154e-01 4.19409335e-01 1.41407941e-02 1.17888510e+00 -1.39312899e+00 -5.92074215e-01 7.59146690e-01 -7.36302972e-01 -1.21507965e-01 5.03202498e-01 3.84885907e-01 1.46500039e+00 -1.11003089e+00 7.95358181e-01 1.63521624e+00 4.30805534e-01 4.36438978e-01 -1.87410605e+00 -1.79866493e-01 2.73264885e-01 1.27202332e-01 -1.00249755e+00 -5.54612637e-01 8.06438386e-01 -5.96738160e-01 9.17350888e-01 7.55771101e-01 6.75063431e-02 1.36166751e+00 8.12277868e-02 1.19958091e+00 1.33164394e+00 -3.90926808e-01 -2.13162526e-01 3.52458566e-01 2.01381132e-01 5.63109636e-01 -2.19517753e-01 -1.11190893e-01 -6.68517649e-01 -3.61416310e-01 -3.34852040e-02 -4.58551705e-01 -5.25501132e-01 -5.23658693e-01 -1.53764713e+00 7.26975203e-01 4.19213891e-01 1.98360860e-01 -2.49376968e-01 8.88741240e-02 4.71368849e-01 5.01291215e-01 2.78483510e-01 2.80633181e-01 -2.51116306e-01 -2.10625932e-01 -7.51213074e-01 2.28310555e-01 5.50527275e-01 4.71831024e-01 6.76692188e-01 -2.38702044e-01 -4.77729559e-01 1.06844521e+00 1.72003299e-01 3.61508846e-01 2.96931028e-01 -1.04596686e+00 4.51051265e-01 7.31276691e-01 -6.81144446e-02 -8.93452406e-01 -6.82424963e-01 -1.47564694e-01 -7.48485386e-01 2.23599553e-01 8.59102368e-01 4.54409905e-02 -8.19091141e-01 2.01034522e+00 6.92076907e-02 -6.36101961e-01 6.23025522e-02 8.67169857e-01 9.40231860e-01 6.49785519e-01 2.64831901e-01 -7.47518614e-02 1.44261897e+00 -8.32276165e-01 -5.34099400e-01 -2.13086307e-01 8.10436308e-01 -8.76028657e-01 1.76052642e+00 4.32854682e-01 -1.07486475e+00 -4.48754013e-01 -7.28185713e-01 -2.06044883e-01 -4.37988877e-01 6.25363141e-02 4.89624619e-01 5.59292793e-01 -7.54325390e-01 4.75791484e-01 -4.76455331e-01 -4.19796050e-01 1.31797060e-01 2.29083613e-01 -7.11280704e-01 -2.31607005e-01 -9.17028189e-01 1.07295346e+00 2.10675359e-01 -5.18040396e-02 -5.92958152e-01 -7.08604574e-01 -7.50410914e-01 1.06710732e-01 3.77177447e-01 -7.98818469e-01 1.12547886e+00 -1.40218532e+00 -9.40237343e-01 1.10432208e+00 -4.64112192e-01 -2.07304835e-01 7.01083422e-01 -7.26683736e-02 -2.51851648e-01 2.14566886e-01 -2.03121692e-01 1.22425485e+00 9.42769229e-01 -1.83484697e+00 -3.27638716e-01 -4.04287398e-01 1.04239412e-01 4.17340249e-01 -4.15373206e-01 -3.39019597e-02 -4.26540166e-01 -3.58181238e-01 -1.26039460e-01 -1.04387701e+00 2.95771629e-01 3.39951143e-02 -6.57976329e-01 -3.34523320e-01 7.48977244e-01 -6.64595485e-01 1.07682371e+00 -2.35361505e+00 4.98614341e-01 1.21030733e-01 2.21793264e-01 -2.31630683e-01 -4.04303402e-01 4.36122388e-01 -3.77363592e-01 1.67187870e-01 -3.85723591e-01 -6.97533071e-01 6.18566036e-01 1.53159767e-01 -4.82078552e-01 4.35341090e-01 4.46382076e-01 1.12788379e+00 -3.34661007e-01 -6.38866603e-01 3.01824003e-01 5.06672442e-01 -4.15744275e-01 -2.28807211e-01 -3.87269318e-01 4.24759835e-01 2.36792237e-01 7.89176702e-01 6.26527190e-01 -4.22544539e-01 -2.09767520e-02 -2.97390759e-01 1.00002892e-01 -1.18005805e-01 -8.32301676e-01 1.41498041e+00 -3.50443274e-01 1.03615332e+00 4.39585224e-02 -8.12918961e-01 3.07802558e-01 1.07944325e-01 2.49518946e-01 -9.05479193e-01 -3.26278359e-02 6.76773041e-02 4.78394538e-01 -5.98435938e-01 4.31617647e-01 -1.49356589e-01 1.65174529e-01 3.20121109e-01 1.81878190e-02 2.84004927e-01 4.16312665e-01 4.03905421e-01 7.87471175e-01 1.09037168e-01 -1.22465394e-01 -1.05667330e-01 5.37386954e-01 1.07328534e-01 -1.99464798e-01 8.10066879e-01 -5.16219474e-02 7.76790500e-01 1.08399832e+00 -4.93089706e-02 -8.50202262e-01 -1.18524063e+00 -4.37058240e-01 1.66468585e+00 -1.75494943e-02 -4.64257210e-01 -5.19210398e-01 -6.83164179e-01 1.26823306e-01 9.00979400e-01 -9.74019587e-01 -1.52569324e-01 -2.33647332e-01 -1.02920806e+00 6.18245482e-01 3.47839922e-01 -6.77246694e-03 -1.05212677e+00 -4.57976580e-01 -3.26140165e-01 -3.34270597e-01 -1.05298197e+00 -2.36592203e-01 2.99485058e-01 -5.66196263e-01 -9.13809776e-01 -1.13688803e+00 -4.85495120e-01 5.38616300e-01 4.41646241e-02 1.30076551e+00 1.87739842e-02 -1.66658998e-01 8.39809597e-01 -2.00012475e-01 -8.19036439e-02 -2.96980143e-01 -1.36256114e-01 -4.99350131e-01 3.09185654e-01 2.40681127e-01 -1.53680250e-01 -5.07450998e-01 4.16423410e-01 -9.41897869e-01 1.31075099e-01 8.08032751e-01 1.07517684e+00 3.17864358e-01 -4.44931328e-01 3.11558276e-01 -7.10173905e-01 6.50348902e-01 -4.00640309e-01 -7.09134154e-03 4.16308016e-01 -2.84299612e-01 2.11353987e-01 4.74167526e-01 -8.54554296e-01 -9.73898649e-01 -8.89972076e-02 3.96058485e-02 -4.87940639e-01 -3.40786159e-01 7.35008478e-01 -2.94484615e-01 1.50475591e-01 8.14392626e-01 1.84616655e-01 5.14506027e-02 -3.49481106e-01 5.70557833e-01 4.13888872e-01 5.45680404e-01 -7.50805259e-01 4.12005812e-01 5.62965810e-01 4.97049242e-02 -1.08246815e+00 -4.43775386e-01 -3.26234639e-01 -3.80070716e-01 -3.00211519e-01 9.15169179e-01 -6.07231915e-01 -8.54855835e-01 2.25807652e-01 -1.14145660e+00 -2.13625953e-01 2.92324647e-02 3.53065014e-01 -5.10147452e-01 4.60084289e-01 -3.39326382e-01 -9.43687677e-01 1.06288910e-01 -1.41584826e+00 1.20383763e+00 -6.13087378e-02 -4.89680499e-01 -1.05997443e+00 6.35799468e-02 6.83404446e-01 2.78544545e-01 1.97217256e-01 1.69819570e+00 -7.44531870e-01 -2.27972463e-01 -8.49847943e-02 -4.56218451e-01 2.67353892e-01 -3.44090402e-01 3.13583255e-01 -1.52293658e+00 -1.59752190e-01 -5.07958770e-01 -4.96532679e-01 1.25763178e+00 3.79481196e-01 1.08003473e+00 -1.86243430e-01 -1.99327603e-01 3.02706003e-01 8.29972804e-01 -1.76395610e-01 6.66735888e-01 6.95147812e-02 7.04054594e-01 1.19887662e+00 2.16404930e-01 5.12690209e-02 4.49436456e-01 7.25112498e-01 5.79983175e-01 -2.39587113e-01 -6.58954009e-02 -1.60667449e-01 6.01228833e-01 1.84269071e-01 5.38446195e-02 -4.72302556e-01 -1.04826891e+00 4.60180104e-01 -1.83285522e+00 -9.37496781e-01 -5.53733826e-01 2.27288008e+00 6.90699935e-01 1.13251902e-01 3.71443838e-01 9.33060050e-02 4.22567338e-01 1.28074259e-01 -4.15690094e-01 -4.82408464e-01 -5.78547299e-01 -1.87218383e-01 7.11159455e-03 5.02117336e-01 -1.23979986e+00 5.17358303e-01 5.85932446e+00 9.21096325e-01 -1.09333396e+00 -1.46703973e-01 7.28699327e-01 -2.17769504e-01 -6.89934671e-01 1.32274237e-02 -2.90257543e-01 3.18277061e-01 8.60834837e-01 2.88540661e-01 4.83393878e-01 6.39053822e-01 -1.67175651e-01 -3.96826595e-01 -1.55503368e+00 1.20869637e+00 3.24786633e-01 -9.71713126e-01 3.11908841e-01 1.65215552e-01 5.82830727e-01 -2.60038644e-01 5.59258521e-01 4.77007776e-01 -2.26215199e-01 -1.43796062e+00 6.80105090e-01 4.69220668e-01 4.65667129e-01 -7.30030239e-01 5.88527858e-01 4.00027364e-01 -5.98387718e-01 -1.74228512e-02 -2.32017245e-02 2.49215752e-01 8.67595524e-02 1.97577968e-01 -4.68433380e-01 4.09606934e-01 5.79256892e-01 2.67944872e-01 -9.56187487e-01 8.53292525e-01 1.39132649e-01 4.38464522e-01 -1.48951441e-01 9.31349024e-02 2.69319296e-01 1.63513105e-02 6.94851577e-01 1.47298658e+00 3.49374814e-03 -3.86224836e-01 -2.60181487e-01 8.18633258e-01 -1.11515820e-01 3.30773801e-01 -8.15493405e-01 -2.67720163e-01 -1.40424967e-01 1.29748857e+00 -4.81317788e-01 -1.58836827e-01 -6.92284703e-01 8.67054224e-01 1.28128022e-01 5.39019406e-01 -8.66191447e-01 -7.63457268e-02 4.30893064e-01 -1.54574611e-03 2.38901842e-02 3.43499444e-02 -6.61902189e-01 -1.01451516e+00 1.00280210e-01 -1.21983123e+00 6.45063519e-01 -1.03784037e+00 -1.38199770e+00 3.45418870e-01 1.35773703e-01 -1.07021463e+00 -4.06847179e-01 -8.36036623e-01 -4.30851489e-01 7.30912328e-01 -1.16471672e+00 -1.40742278e+00 -2.13604286e-01 7.42610276e-01 3.00808519e-01 1.09501496e-01 7.25183725e-01 2.36011803e-01 -3.79107803e-01 8.50475848e-01 5.27949594e-02 -1.56500563e-01 1.09444034e+00 -1.41422164e+00 -3.37740958e-01 4.96280491e-01 5.02582967e-01 6.27531290e-01 1.00774026e+00 -2.57312894e-01 -1.57644904e+00 -4.45546120e-01 7.59351134e-01 -6.97123051e-01 7.55795479e-01 -4.91540849e-01 -1.21377051e+00 6.54839456e-01 6.78879976e-01 -3.70901883e-01 7.31933713e-01 4.86877263e-01 -6.99422598e-01 2.31369659e-01 -7.42845356e-01 9.18234706e-01 7.06707418e-01 -6.77285314e-01 -6.07822955e-01 3.61891031e-01 3.36435199e-01 -1.55087218e-01 -6.41224504e-01 5.52148104e-01 8.17104876e-01 -1.01951504e+00 9.92308438e-01 -1.07220590e+00 9.77005064e-01 -9.09462944e-02 -4.56143498e-01 -1.24047852e+00 4.80431840e-02 -2.94971555e-01 -1.28340051e-01 1.22898090e+00 8.58720660e-01 -3.98620695e-01 4.97347921e-01 9.49930668e-01 -2.02975478e-02 -6.42493844e-01 -8.80630672e-01 -5.83395958e-01 3.97941947e-01 -5.99287987e-01 -3.08185797e-02 1.01726294e+00 1.53441623e-01 6.86256826e-01 -5.15067518e-01 -1.81746334e-01 3.56011182e-01 2.01100603e-01 9.78905320e-01 -9.63165998e-01 -4.16894406e-01 -1.00626016e+00 -1.49186924e-01 -9.10376191e-01 3.20318729e-01 -9.17576730e-01 -1.73153117e-01 -1.38004613e+00 6.04121149e-01 1.49033159e-01 -2.18736351e-01 5.46071291e-01 -2.19918430e-01 3.72025609e-01 3.55086893e-01 3.25361779e-03 -5.81348479e-01 5.47534347e-01 1.33587241e+00 -4.40590233e-01 -1.46590009e-01 -2.15818048e-01 -7.39022493e-01 7.61296868e-01 3.28513920e-01 -1.24569543e-01 -3.61709267e-01 -3.83421689e-01 3.83929700e-01 -1.34046406e-01 7.66514182e-01 -5.46922207e-01 7.31517524e-02 -4.67128418e-02 5.75185418e-01 -5.79055548e-01 7.50232756e-01 -8.32831144e-01 7.02792630e-02 2.18103811e-01 -6.68390632e-01 1.07501052e-01 5.28993547e-01 3.35368782e-01 -3.38973194e-01 -1.55907810e-01 5.98908544e-01 2.49420196e-01 -5.52532613e-01 -3.15394431e-01 -3.29656929e-01 1.65545449e-01 8.56912374e-01 -1.85587212e-01 -8.55746746e-01 -6.90347075e-01 -9.37877476e-01 2.20403031e-01 4.35547084e-01 5.62610447e-01 3.45924884e-01 -1.25339937e+00 -7.93133199e-01 -1.03618421e-01 5.02084672e-01 -5.29980242e-01 7.50598192e-01 1.42459512e+00 -2.53726393e-02 4.50060368e-01 -7.76469260e-02 -9.30596411e-01 -1.58497107e+00 6.71334982e-01 2.20802605e-01 -2.92151440e-02 -2.89132208e-01 7.58302808e-01 7.98744917e-01 -4.29893672e-01 4.14962023e-01 -1.51516542e-01 -1.48266524e-01 6.26659811e-01 3.02738369e-01 2.46073768e-01 8.67510661e-02 -9.15376902e-01 -3.83850157e-01 5.21397829e-01 2.27892902e-02 -4.18244004e-01 8.81023943e-01 5.72441667e-02 -7.12730512e-02 8.64017904e-01 1.44894254e+00 -2.92673223e-02 -1.05840743e+00 3.60220969e-02 -1.26622275e-01 -4.24700826e-01 -2.23536223e-01 -1.09248424e+00 -6.50779247e-01 1.37947476e+00 5.10490179e-01 3.35690022e-01 1.07647026e+00 2.59388268e-01 2.81149731e-03 4.26316977e-01 -3.02273870e-01 -8.46917808e-01 8.69170427e-02 3.84869218e-01 1.18173718e+00 -1.49787796e+00 -1.11187249e-01 7.75354952e-02 -1.20729017e+00 9.02218759e-01 5.78682363e-01 3.09644163e-01 2.93112516e-01 -1.29244253e-01 -3.53909023e-02 -7.88530409e-02 -1.14600766e+00 -2.87031084e-01 8.33118379e-01 3.96595389e-01 5.44690967e-01 2.74190940e-02 -1.20126374e-01 3.56881559e-01 -8.44930187e-02 -6.88602328e-01 1.74418185e-02 5.82334936e-01 -9.17820185e-02 -8.75968993e-01 -6.08223140e-01 5.64730406e-01 -3.76370668e-01 -1.98975384e-01 -8.66305232e-01 1.27657866e+00 -7.91583061e-02 8.09035301e-01 2.12757468e-01 -3.56357843e-01 3.68386418e-01 6.12652957e-01 5.87359369e-01 4.08410616e-02 -4.74615604e-01 3.12227011e-01 3.37888658e-01 -3.63139540e-01 -2.74731517e-01 -7.36402273e-01 -1.04235339e+00 -4.28110838e-01 -3.78408772e-03 -2.11626425e-01 6.85874045e-01 8.96159768e-01 2.26640269e-01 2.84111023e-01 1.47901788e-01 -8.34314585e-01 -5.33877850e-01 -9.99957860e-01 -2.97292888e-01 8.77142549e-01 4.66532230e-01 -8.06663036e-01 -5.74260533e-01 5.82971163e-02]	[10.879786491394043, 1.612903356552124]
a3c50dc5-ca53-46e1-9189-8543b4154112	document-image-classification-with-intra	1801.09321	null	http://arxiv.org/abs/1801.09321v3	http://arxiv.org/pdf/1801.09321v3.pdf	Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks	In this work, a region-based Deep Convolutional Neural Network framework is proposed for document structure learning. The contribution of this work involves efficient training of region based classifiers and effective ensembling for document image classification. A primary level of `inter-domain' transfer learning is used by exporting weights from a pre-trained VGG16 architecture on the ImageNet dataset to train a document classifier on whole document images. Exploiting the nature of region based influence modelling, a secondary level of `intra-domain' transfer learning is used for rapid training of deep learning models for image segments. Finally, stacked generalization based ensembling is utilized for combining the predictions of the base deep neural network models. The proposed method achieves state-of-the-art accuracy of 92.2% on the popular RVL-CDIP document image dataset, exceeding benchmarks set by existing algorithms.	['Swapan Kumar Parui', 'Ujjwal Bhattacharya', 'Saikat Roy', 'Arindam Das']	2018-01-29	null	null	null	null	['document-image-classification']	['computer-vision']	[ 2.27669492e-01 -7.92133734e-02 -4.48824525e-01 -6.44507766e-01 -8.79865468e-01 -7.84715474e-01 8.28323543e-01 3.69833380e-01 -2.20340818e-01 4.27233636e-01 -7.29575977e-02 -5.32797217e-01 -9.17573646e-02 -8.59524965e-01 -9.97177482e-01 -5.38294733e-01 -1.29373699e-01 4.76266265e-01 3.65519553e-01 -2.47063667e-01 6.55382633e-01 9.51634526e-01 -1.24870110e+00 1.19117260e+00 6.19552553e-01 1.68569088e+00 -5.68636954e-02 1.18714786e+00 -6.13387465e-01 1.15882468e+00 -9.88935649e-01 -2.04708755e-01 -7.19482377e-02 -1.54477835e-01 -9.21428204e-01 2.01609626e-01 6.25995696e-01 -5.72070420e-01 -1.25506774e-01 4.46686238e-01 2.71625727e-01 1.64167479e-01 1.12967563e+00 -6.46171153e-01 -6.73417985e-01 6.79433048e-01 -6.95849359e-01 2.68798530e-01 2.26642266e-02 -5.15305340e-01 1.01815021e+00 -7.94664323e-01 7.33205616e-01 8.12700987e-01 8.25218439e-01 6.09894060e-02 -1.01524341e+00 -4.07973111e-01 2.88430721e-01 1.30489543e-01 -1.05519259e+00 -3.87031734e-02 1.02457416e+00 -5.41941822e-01 1.34401906e+00 -9.21414793e-02 4.84216243e-01 1.09266067e+00 5.12528181e-01 1.16595650e+00 7.70313740e-01 -7.01753438e-01 9.47611555e-02 1.73535481e-01 4.81619596e-01 7.09999263e-01 -1.76266477e-01 -7.86751732e-02 -4.34154868e-01 1.71006560e-01 5.49951077e-01 -1.14192292e-01 8.84484500e-02 -2.21348286e-01 -5.27558982e-01 7.62483180e-01 1.02261007e+00 5.55464983e-01 -3.30454022e-01 1.64371923e-01 8.26963663e-01 9.70561504e-02 7.83581972e-01 1.73949257e-01 -5.50343335e-01 -1.24750137e-02 -1.40079951e+00 1.49343893e-01 4.99821097e-01 8.55769873e-01 4.56706524e-01 4.79823910e-02 -4.08152223e-01 1.24242735e+00 3.98340434e-01 4.19978611e-02 3.97329956e-01 -3.50389719e-01 7.69071400e-01 9.00256634e-01 -3.26500893e-01 -6.79572821e-01 -3.16616446e-01 -8.73488605e-01 -7.94355810e-01 3.20290655e-01 3.21045309e-01 2.58610636e-01 -1.34698379e+00 6.85443223e-01 -1.87923908e-01 -2.37844199e-01 1.32606357e-01 4.30576622e-01 6.24062181e-01 1.06033075e+00 -1.66978791e-01 3.76711756e-01 1.06588030e+00 -1.23831522e+00 -1.61513895e-01 1.28998592e-01 7.67330825e-01 -6.53565586e-01 6.55480981e-01 7.82580674e-01 -9.17168558e-01 -8.82659912e-01 -1.27910161e+00 -1.89588562e-01 -8.62378538e-01 4.18623209e-01 2.35416055e-01 5.23634315e-01 -8.88858140e-01 3.50685656e-01 -4.75526303e-01 -2.04001322e-01 9.06364202e-01 3.89565825e-01 -2.22964883e-01 -2.77748078e-01 -8.61254573e-01 5.17917395e-01 7.97568858e-01 4.13264968e-02 -9.86323714e-01 -6.18769348e-01 -5.34136355e-01 1.13955289e-01 -3.65817547e-01 1.44902170e-01 1.09727395e+00 -1.19881094e+00 -1.30125391e+00 9.88199353e-01 3.53438795e-01 -7.13822305e-01 5.59461474e-01 -2.82519851e-02 -4.06272143e-01 4.25759882e-01 -1.81003556e-01 7.66681731e-01 1.05077410e+00 -1.64373398e+00 -7.51049280e-01 -5.31583130e-01 -1.57595932e-01 -3.35918665e-02 -3.93418193e-01 2.18818542e-02 -7.73538530e-01 -7.51345396e-01 -1.49329126e-01 -4.69421297e-01 3.17520022e-01 -1.67053372e-01 -4.58099395e-01 -3.07581365e-01 1.30781198e+00 -1.05408573e+00 1.02449179e+00 -2.01315546e+00 -1.02307186e-01 7.04885364e-01 -1.81061864e-01 4.22006160e-01 -2.33949527e-01 2.48742774e-01 -7.83507600e-02 -1.89036682e-01 -3.99235263e-02 -2.71411926e-01 -2.72743851e-01 -7.68920109e-02 -5.35808623e-01 1.77645892e-01 2.00339168e-01 1.02158535e+00 -2.54929900e-01 -5.80557525e-01 2.67767876e-01 6.57390535e-01 -3.34706485e-01 1.44222334e-01 -5.15274107e-01 4.90461066e-02 -2.77342439e-01 7.81194866e-01 7.04445601e-01 -7.46480152e-02 1.24514900e-01 -1.00540347e-01 -1.37717696e-02 1.57572359e-01 -6.68736875e-01 1.82625329e+00 -5.88205814e-01 7.90874898e-01 -9.65247750e-02 -1.47277653e+00 1.35982430e+00 1.01442197e-02 3.65002662e-01 -7.49373615e-01 4.30329859e-01 1.39638841e-01 -2.56695032e-01 7.03923553e-02 5.92996120e-01 4.90683377e-01 -6.23271205e-02 5.00927210e-01 4.40459818e-01 6.86834231e-02 1.56859532e-02 4.36510928e-02 8.62053156e-01 4.41206515e-01 -1.61861748e-01 -3.47166419e-01 7.82187998e-01 3.76535088e-01 -2.92212278e-01 7.33460963e-01 1.04865834e-01 6.31881475e-01 4.57605749e-01 -7.07238317e-01 -1.25900829e+00 -8.79854381e-01 -4.99060541e-01 1.60428607e+00 -3.18090737e-01 2.66783535e-02 -9.11079228e-01 -1.06154180e+00 9.02882740e-02 6.36791646e-01 -8.95710588e-01 2.64393371e-02 -5.01156867e-01 -4.29620981e-01 8.81106317e-01 1.27620184e+00 8.25320542e-01 -1.03666127e+00 -3.10359269e-01 3.78404766e-01 2.35804543e-01 -8.28080714e-01 -3.41186896e-02 7.32432663e-01 -9.87737000e-01 -7.74323106e-01 -1.06347489e+00 -1.00255716e+00 6.49011374e-01 -1.53888479e-01 8.98000598e-01 8.88984054e-02 -4.38871711e-01 1.84688151e-01 -4.19873387e-01 -5.05185068e-01 -5.49858689e-01 5.96327007e-01 -6.42714322e-01 3.35662924e-02 2.62748182e-01 3.85262677e-03 -5.56037903e-01 -5.93814254e-02 -8.56106460e-01 -2.11678341e-01 6.42468929e-01 1.03520811e+00 4.70538080e-01 2.68073857e-01 3.88177842e-01 -7.23649204e-01 8.89806449e-01 -1.11538112e-01 -6.73460245e-01 4.32795763e-01 -6.68960214e-01 4.34766673e-02 7.94261694e-01 -1.50615796e-01 -1.38528192e+00 -1.59105897e-01 -1.16247527e-01 -1.79874361e-01 -2.99213111e-01 5.18521786e-01 1.23588704e-01 2.47461170e-01 8.77719402e-01 4.34541821e-01 -3.69238816e-02 -4.43991899e-01 4.33761388e-01 1.32397354e+00 6.93789184e-01 -7.98269689e-01 2.24244550e-01 3.79919261e-01 -1.78292006e-01 -6.74358606e-01 -8.42343211e-01 -6.25142217e-01 -1.09181690e+00 -4.22237426e-01 1.00077510e+00 -7.60789454e-01 -2.70074964e-01 8.02989900e-01 -1.25572813e+00 -4.48977470e-01 -1.15887448e-01 -1.84330456e-02 -3.51747066e-01 -9.53975022e-02 -7.02951729e-01 -5.90897918e-01 -5.89201450e-01 -1.13876343e+00 1.30522478e+00 1.07802302e-02 -4.32261229e-02 -1.23728335e+00 -1.33997540e-03 6.63612962e-01 1.73384279e-01 1.29162362e-02 1.12715495e+00 -8.36221218e-01 -4.09888834e-01 -7.17698812e-01 -6.84486628e-01 8.58838856e-01 -1.64109111e-01 3.51466030e-01 -1.16146076e+00 -2.77379453e-01 -7.74245262e-01 -5.78774631e-01 1.34398234e+00 6.05614483e-01 1.54741681e+00 5.50349019e-02 -4.52045828e-01 6.23028278e-01 1.52305973e+00 4.79178369e-01 6.80433750e-01 7.05047011e-01 7.80180454e-01 5.64158201e-01 5.45016050e-01 3.46649855e-01 5.94441257e-02 5.78499913e-01 3.98911834e-01 -9.69416276e-02 -1.93383485e-01 -7.91451484e-02 9.81476232e-02 1.54494956e-01 -2.08163202e-01 -5.22981226e-01 -1.26050675e+00 4.65552658e-01 -1.63866901e+00 -7.96883881e-01 5.48503771e-02 1.67781281e+00 5.77233672e-01 4.03260678e-01 -1.51945872e-03 4.28541690e-01 5.84712744e-01 2.01251701e-01 -2.65787840e-01 -1.13546264e+00 4.99380333e-03 2.89070398e-01 5.38138092e-01 3.00305605e-01 -1.45363545e+00 1.04337132e+00 6.08952951e+00 8.76889825e-01 -1.33404207e+00 -2.63342857e-01 8.94400239e-01 2.53204316e-01 1.96880490e-01 -5.88861287e-01 -1.09065866e+00 2.71322221e-01 1.05901790e+00 7.64182150e-01 1.63929507e-01 1.17763209e+00 -2.71877766e-01 1.75035577e-02 -8.25795472e-01 4.60298032e-01 3.38035107e-01 -1.78298807e+00 2.87618965e-01 2.29244277e-01 9.93060052e-01 1.20101444e-01 2.56688476e-01 3.26393574e-01 2.17262655e-01 -1.20112133e+00 6.73703015e-01 5.47278285e-01 8.48984122e-01 -1.42873299e+00 7.49219239e-01 2.13528514e-01 -9.77611482e-01 -4.19534832e-01 -3.74740958e-01 5.03480136e-01 -4.14622337e-01 3.63586038e-01 -1.05241013e+00 6.06408060e-01 8.10728312e-01 8.77069294e-01 -5.66425800e-01 5.58993876e-01 -5.15941530e-02 7.51302898e-01 -1.22406930e-01 9.87991244e-02 8.04618776e-01 -3.18750143e-02 -6.63670897e-02 1.66411805e+00 8.43288079e-02 -6.20175242e-01 -1.35440141e-01 6.86736405e-01 -3.87871236e-01 9.12584513e-02 -5.76808035e-01 -4.95207272e-02 8.59848037e-02 1.18016732e+00 -9.18974578e-01 -4.53642488e-01 -2.83696890e-01 1.14319146e+00 3.06107163e-01 2.53256589e-01 -6.38960719e-01 -6.51261389e-01 7.60151744e-02 -2.73098536e-02 9.44414318e-01 -5.83246648e-02 -6.48847759e-01 -7.02593982e-01 -1.43335983e-01 -7.47889698e-01 3.71137679e-01 -8.43230426e-01 -8.71698320e-01 6.65232837e-01 -1.77639320e-01 -1.02786672e+00 -4.71321642e-01 -1.16320348e+00 -8.32588613e-01 9.10531938e-01 -1.46907413e+00 -1.85721135e+00 -3.40141356e-01 5.41085005e-01 5.83905518e-01 -8.52586687e-01 8.36238265e-01 -2.79774740e-02 -4.10685778e-01 6.52579308e-01 7.56175220e-01 6.36995316e-01 3.68261456e-01 -1.43498003e+00 3.22721630e-01 6.73160553e-01 2.77215123e-01 3.17337006e-01 -6.48260638e-02 -4.57939357e-01 -9.11321163e-01 -1.45728219e+00 5.15135288e-01 -3.44072312e-01 4.42027122e-01 -5.10486543e-01 -9.40169930e-01 6.21628881e-01 2.63544083e-01 5.30336089e-02 6.51647866e-01 6.29258305e-02 -7.55285084e-01 -3.06656420e-01 -1.07849038e+00 1.03694908e-01 3.54733527e-01 -5.92839956e-01 -5.74098587e-01 2.44637802e-01 2.25016192e-01 -3.13168436e-01 -1.11399603e+00 1.62300810e-01 8.55924964e-01 -7.94261873e-01 1.10697687e+00 -6.61292672e-01 1.03518152e+00 6.40337393e-02 -3.29766721e-01 -1.15022254e+00 -5.53701334e-02 1.90806031e-01 -2.19893649e-01 1.37019563e+00 4.88782942e-01 -2.94792242e-02 1.06987453e+00 -1.12746030e-01 -2.69793451e-01 -9.02991652e-01 -5.44412732e-01 -7.96580195e-01 4.99912471e-01 -6.41622543e-01 3.71062487e-01 6.37412429e-01 -4.67459887e-01 2.05600008e-01 2.36703858e-01 -2.94767525e-02 5.88212967e-01 6.42730743e-02 5.60137272e-01 -1.28009546e+00 -2.20076025e-01 -6.84779346e-01 -3.67769480e-01 -1.03972805e+00 3.49064291e-01 -1.20775878e+00 -3.59223336e-02 -1.81962216e+00 -2.33109662e-04 -3.41166139e-01 -5.96514404e-01 4.55754101e-01 4.98052895e-01 5.24468064e-01 -2.46955585e-02 2.16957033e-01 -3.85444105e-01 1.39157310e-01 1.08792412e+00 -6.34609997e-01 -1.66007295e-01 9.40413177e-02 -3.57467353e-01 3.64555389e-01 8.67224216e-01 5.50881959e-03 -4.75803941e-01 -4.10828561e-01 -3.45116556e-02 -3.34945410e-01 2.49141365e-01 -8.92537355e-01 -3.30219306e-02 4.88632560e-01 1.18095410e+00 -1.42671204e+00 2.10151985e-01 -8.10683429e-01 -7.54978657e-01 2.70693272e-01 -6.55042291e-01 -5.06913841e-01 4.62989062e-01 4.09807920e-01 -4.39372808e-01 -3.51503342e-01 9.10686612e-01 -8.68251175e-03 -7.17599094e-01 -1.09081335e-01 -4.14829999e-01 -4.06971991e-01 9.97778416e-01 -6.53017759e-01 -2.88735300e-01 -1.63007844e-02 -4.63097930e-01 -2.46083140e-01 1.02258220e-01 4.23826903e-01 6.59855306e-01 -1.00678718e+00 -5.43290555e-01 2.83744872e-01 4.16930705e-01 2.11178139e-01 1.76147103e-01 2.61552989e-01 -9.64951992e-01 9.26360190e-01 -3.34490120e-01 -9.05077994e-01 -1.30052471e+00 2.88512379e-01 4.20768440e-01 -5.74354529e-01 -5.68367362e-01 1.16996431e+00 -1.20850936e-01 -5.92308402e-01 4.42682892e-01 -4.69335258e-01 -3.82161409e-01 2.38280684e-01 5.05273819e-01 2.45765537e-01 6.29578173e-01 -5.48123598e-01 -2.85077751e-01 5.07725954e-01 -7.48637259e-01 -9.99019742e-02 1.40244687e+00 2.99890071e-01 -2.04919744e-03 2.47213408e-01 1.60200918e+00 -4.31819081e-01 -1.35779917e+00 1.46374181e-02 5.44073544e-02 2.23921925e-01 6.92408144e-01 -1.28988826e+00 -9.49077010e-01 1.22074783e+00 5.60680330e-01 -4.86370102e-02 1.25504947e+00 -8.65270346e-02 3.17650676e-01 5.71663678e-01 -1.03956968e-01 -1.55828857e+00 2.84805596e-01 7.33248651e-01 1.08222020e+00 -1.15406156e+00 -3.28015089e-02 1.77393243e-01 -5.93622565e-01 1.51026392e+00 4.47160870e-01 -3.55831712e-01 7.90537894e-01 4.88572299e-01 1.30263388e-01 -1.48204789e-01 -5.09273469e-01 2.58852869e-01 6.61629975e-01 7.86911964e-01 6.72918379e-01 -1.77042738e-01 2.55207032e-01 4.31696177e-01 3.43531445e-02 -3.44606005e-02 3.93233076e-02 1.18301177e+00 -3.42908651e-01 -1.05474496e+00 -4.11866993e-01 5.98220229e-01 -5.13132393e-01 -8.56865495e-02 -6.31207228e-01 7.22644508e-01 8.69128108e-03 4.55446184e-01 6.63310111e-01 -2.46112466e-01 -2.60276850e-02 1.49133191e-01 6.70726895e-01 -3.97229731e-01 -9.01921570e-01 9.08827633e-02 -5.31413034e-02 -2.50056267e-01 -1.22373961e-01 -2.54656285e-01 -1.22937560e+00 6.61339462e-02 -2.87654608e-01 -1.20036200e-01 1.24192727e+00 9.31454003e-01 2.70253748e-01 9.93168890e-01 5.77850521e-01 -7.97140300e-01 -5.00012040e-01 -1.14864540e+00 -6.41153634e-01 1.13112189e-01 1.75692350e-01 -2.58214533e-01 1.98822290e-01 3.04016382e-01]	[11.454648971557617, 2.6130287647247314]
d577b3c0-0c7d-4c13-bfcc-de7b7030effe	reliable-lexical-simplification-for-non	null	null	https://aclanthology.org/N15-2002	https://aclanthology.org/N15-2002.pdf	Reliable Lexical Simplification for Non-Native Speakers	null	['Gustavo Paetzold']	2015-06-01	null	null	null	naacl-2015-6	['complex-word-identification']	['natural-language-processing']	[-8.63703638e-02 1.71006292e-01 -6.22772932e-01 -4.08054382e-01 -8.41685571e-03 -9.08429027e-01 6.55310392e-01 -6.53472245e-01 -2.85945535e-01 1.06888819e+00 -4.63127941e-02 -1.01159286e+00 -3.91567826e-01 -9.63214397e-01 -4.95059669e-01 -6.31337762e-01 -9.79754329e-01 7.25764990e-01 3.30370307e-01 -6.93831444e-01 7.03166842e-01 7.88774848e-01 -1.68942046e+00 7.18545914e-01 7.04417467e-01 8.52217197e-01 2.49141872e-01 1.14950800e+00 -1.95044339e-01 1.55633950e+00 -7.48382092e-01 -5.46825826e-01 3.13719302e-01 -1.23176083e-01 -7.22945035e-01 -1.01074085e-01 9.28529128e-02 -8.59008506e-02 -2.09758401e-01 9.22211111e-01 5.37373662e-01 4.49454933e-02 1.08379531e+00 -1.42548037e+00 -5.91619551e-01 6.10313773e-01 -4.01565880e-02 1.21627934e-01 1.03678203e+00 -5.39447069e-01 1.19919395e+00 -1.13026452e+00 7.20913768e-01 1.26888943e+00 8.66221786e-01 5.44149756e-01 -1.22286928e+00 -1.94712028e-01 -3.26822817e-01 -9.51717794e-02 -1.46558487e+00 -3.25250506e-01 4.25783843e-02 -2.08119690e-01 1.66093647e+00 1.26596653e+00 1.20609856e+00 1.01401424e+00 1.26658809e+00 8.34431887e-01 1.04267764e+00 -5.13792276e-01 3.35295945e-01 3.66983831e-01 1.54683650e-01 6.33519173e-01 8.40953708e-01 5.26628852e-01 -7.06372619e-01 -9.13127720e-01 9.33553874e-01 -2.94925272e-01 1.71355158e-01 -5.05680561e-01 -9.05919552e-01 6.91228509e-01 1.78732842e-01 3.83959889e-01 -1.39880210e-01 9.89067405e-02 1.26390755e-01 5.30987144e-01 -2.58292928e-02 6.47037446e-01 -9.11868811e-01 -1.33165747e-01 -8.71728659e-01 5.10332465e-01 1.25398111e+00 1.52653182e+00 1.24482810e-01 2.94908643e-01 -9.34252143e-02 3.17179203e-01 8.92314315e-01 1.01808000e+00 4.28362608e-01 -1.36146402e+00 -6.87414408e-02 1.72361732e-01 5.01781464e-01 -8.52631688e-01 -6.33224547e-01 -9.64177120e-03 -8.93263519e-01 4.49267089e-01 3.49161088e-01 4.57367361e-01 -8.02827001e-01 5.07305264e-01 4.33481112e-02 -2.34125629e-01 4.53833073e-01 5.55570945e-02 4.99930978e-01 3.76208365e-01 -1.34477139e-01 -5.73289394e-01 1.06082785e+00 -1.36716676e+00 -1.35299087e+00 2.33215362e-01 9.05734658e-01 -1.07320261e+00 4.35900748e-01 5.33875942e-01 -1.55548143e+00 -1.37560293e-01 -1.08699942e+00 1.78573877e-01 -7.27255583e-01 -3.14239264e-01 8.57801437e-01 1.43120694e+00 -1.60129595e+00 9.73287821e-01 -4.91727620e-01 6.59165755e-02 1.20568443e-02 8.24621081e-01 -2.64718989e-03 4.62812334e-01 -1.33193445e+00 1.08501506e+00 2.22979754e-01 -1.21242590e-01 -1.65216476e-01 -2.13068098e-01 -8.23704481e-01 -5.63443303e-01 -4.78693932e-01 -5.29636025e-01 1.44139910e+00 -2.59346128e-01 -1.65295815e+00 9.71794367e-01 -1.42069459e-01 -1.97814897e-01 6.14786744e-01 -1.28011424e-02 -8.31891418e-01 2.42498964e-01 -1.89849049e-01 5.76383233e-01 9.28263724e-01 -1.35132408e+00 -7.59897232e-01 -1.67359829e-01 -1.23336017e-01 2.66287565e-01 -1.25510961e-01 1.89734384e-01 2.11616129e-01 -1.12999000e-01 3.27147305e-01 -7.20919967e-01 -2.53068686e-01 -5.32041907e-01 -1.46512717e-01 -7.10518599e-01 7.70373225e-01 -4.51523662e-01 1.83705616e+00 -1.67618537e+00 -2.06720144e-01 3.98590982e-01 3.57815564e-01 -1.24705513e-03 2.40583986e-01 1.08380008e+00 -2.76906848e-01 7.32199550e-01 4.11965609e-01 -1.10722095e-01 2.24991128e-01 4.85861301e-01 -4.16602850e-01 3.05609167e-01 -1.29282743e-01 1.15307164e+00 -1.16605783e+00 -5.23096442e-01 4.11106765e-01 9.42391157e-02 -4.58732933e-01 4.79237735e-01 2.99364805e-01 1.47170946e-01 -3.56553018e-01 1.39399457e+00 1.15709066e+00 -1.31984919e-01 1.45911396e-01 5.30878425e-01 -3.79135728e-01 3.55090618e-01 -6.96863770e-01 1.05554795e+00 7.08333924e-02 5.00173986e-01 1.02364108e-01 -7.94621468e-01 3.33247900e-01 8.61540735e-01 4.37155962e-01 -9.67555881e-01 -2.26398129e-02 6.92409754e-01 1.12803578e-01 -6.07703328e-01 7.58228302e-01 3.94563079e-02 -3.64872098e-01 6.40070081e-01 -2.37588286e-01 -6.59476995e-01 9.64643434e-02 3.08100313e-01 6.22585893e-01 -5.18246442e-02 5.62923312e-01 -1.05613089e+00 7.86340594e-01 -1.82965681e-01 -1.81299388e-01 1.03415680e+00 -3.09923887e-01 3.19085121e-01 2.99841821e-01 -6.65102363e-01 -6.45341039e-01 -1.12307119e+00 -4.89381433e-01 1.30636716e+00 3.24267983e-01 -4.39044595e-01 -9.54439282e-01 -2.49762803e-01 1.77620783e-01 6.89606130e-01 -5.90509653e-01 3.84124845e-01 -5.03739953e-01 -8.32535863e-01 7.39044368e-01 3.45434904e-01 -5.07752821e-02 -1.33414865e+00 -6.58416986e-01 1.25490099e-01 -2.20292807e-01 -6.63697243e-01 -6.23428151e-02 4.48765576e-01 -1.35989368e+00 -5.18594682e-01 -6.66252747e-02 -8.20914626e-01 5.87345481e-01 2.46782884e-01 1.27047324e+00 5.39230824e-01 -2.31483161e-01 4.26904231e-01 -1.21292919e-01 -4.95818377e-01 -4.59671497e-01 -8.00336525e-02 5.28869390e-01 -5.87835789e-01 5.19427478e-01 -2.50617653e-01 -7.29350567e-01 5.37953973e-01 -6.88540697e-01 1.62748516e-01 1.79803044e-01 1.04410267e+00 1.35816500e-01 -9.34035778e-02 1.22507080e-01 -6.38007045e-01 8.72274399e-01 -1.69219792e-01 -3.78732830e-01 5.77745810e-02 -6.77108407e-01 -3.74140263e-01 3.21430594e-01 -3.25342178e-01 -1.01981449e+00 -4.87835288e-01 -9.82677937e-02 2.45538145e-01 1.11353043e-02 -1.46784872e-01 6.47139177e-02 -5.24923325e-01 8.02199244e-01 9.25758183e-02 1.99174434e-02 -6.80815242e-03 3.01039815e-01 7.09525108e-01 -6.82967342e-03 -6.68678164e-01 8.44880998e-01 4.91470337e-01 7.98524171e-02 -9.57177758e-01 -1.52186140e-01 -2.60129690e-01 -9.51962709e-01 -6.54426932e-01 6.56643391e-01 -6.78531289e-01 -9.10833478e-01 3.91110867e-01 -9.38691139e-01 -3.38627815e-01 -3.91645581e-01 4.25431967e-01 -1.01278400e+00 2.75717527e-02 -3.90154392e-01 -1.27895141e+00 -5.10977268e-01 -1.02017939e+00 9.43384409e-01 5.30070923e-02 -5.10597289e-01 -1.26927447e+00 5.87685481e-02 2.71537274e-01 1.81734428e-01 -1.73075795e-01 6.90226793e-01 -2.38256708e-01 -4.24233019e-01 -1.53791070e-01 2.34436691e-02 -1.39755070e-01 1.70832314e-02 4.95917559e-01 -9.81751978e-01 -5.31145096e-01 6.65065646e-02 -1.92070693e-01 -1.08835101e-01 6.52520418e-01 5.91872573e-01 -2.29931593e-01 -8.56000841e-01 5.40386558e-01 1.38545322e+00 3.85070026e-01 5.32770038e-01 7.28214979e-01 1.41836226e-01 5.53460240e-01 9.17806149e-01 4.63203549e-01 1.30579369e-02 3.28798652e-01 2.40537539e-01 1.49327129e-01 1.11720070e-01 -1.54819340e-01 3.77893507e-01 1.16112018e+00 -8.18235934e-01 -2.69281328e-01 -5.07867396e-01 4.42987174e-01 -1.72482407e+00 -1.40330648e+00 -4.32368398e-01 6.90478683e-01 6.25676990e-01 1.56016424e-01 -1.48347050e-01 3.35214496e-01 4.99015123e-01 -2.03574806e-01 -1.19133167e-01 -1.06291151e+00 -1.43546045e-01 3.15233678e-01 7.37729073e-01 1.00061214e+00 -7.20721722e-01 1.03317809e+00 1.29781246e+01 1.02230716e+00 2.21112028e-01 1.03134915e-01 5.16071796e-01 3.48020852e-01 -4.36954498e-01 -4.56139445e-02 -1.04416132e+00 2.72933897e-02 1.38140702e+00 -4.30666685e-01 6.85999811e-01 5.44219851e-01 3.44648361e-01 -4.23268199e-01 -1.26188684e+00 5.26221812e-01 9.73738134e-02 -1.40886843e+00 -2.83300440e-04 6.85225725e-01 7.73699820e-01 -5.08050561e-01 6.22419357e-01 3.24184299e-01 6.09259963e-01 -1.14389277e+00 8.60300779e-01 2.53660440e-01 1.03040910e+00 -6.05088234e-01 5.67372203e-01 1.68872893e-01 -1.14389896e+00 -2.20873043e-01 -8.77727985e-01 -1.00755692e+00 3.93533185e-02 -1.81779593e-01 -4.29956943e-01 3.48861217e-01 9.58353162e-01 2.99398601e-01 -3.93658698e-01 9.95779395e-01 -4.78694476e-02 1.04875881e-02 -2.71853864e-01 -4.48467314e-01 4.83122796e-01 -3.54241252e-01 4.66730654e-01 1.00164843e+00 2.48499006e-01 3.51035744e-01 -9.84472036e-02 4.01770771e-01 5.45058846e-01 3.29446048e-02 -1.19659424e+00 -1.78908288e-01 2.83276141e-01 9.16795909e-01 -4.83487815e-01 -4.22520459e-01 -2.00212970e-01 8.62069130e-01 -3.55488248e-02 5.01107454e-01 -6.11489356e-01 -4.35615242e-01 9.72222984e-01 -1.27327025e-01 -1.14700586e-01 -3.48497719e-01 -6.23769283e-01 -7.30352640e-01 -5.89872956e-01 -4.54965204e-01 5.93606755e-02 -5.53365827e-01 -1.39813089e+00 5.79277515e-01 -2.27688253e-02 -1.40553558e+00 -6.99901402e-01 -1.27676582e+00 -4.76714373e-01 4.92853165e-01 -1.11898029e+00 -1.10984349e+00 2.50124663e-01 4.52870727e-01 1.64141744e-01 -5.34416080e-01 1.39563632e+00 3.57715860e-02 1.00637585e-01 9.24474537e-01 6.69434488e-01 -7.37814724e-01 5.56605101e-01 -1.27867436e+00 5.68737745e-01 -1.37897313e-01 -4.31265175e-01 9.05828118e-01 6.28349900e-01 -5.39804697e-01 -1.41196322e+00 -3.66917729e-01 1.08350635e+00 -9.83769417e-01 6.55218959e-01 -3.86345625e-01 4.23767231e-02 7.88592756e-01 7.15902448e-01 -6.18741751e-01 8.21781039e-01 -1.83753878e-01 1.80774391e-01 5.75296998e-01 -1.39248300e+00 6.12354755e-01 1.66275799e+00 -4.63594139e-01 -6.25784039e-01 7.60327101e-01 8.13696027e-01 -6.94087505e-01 -1.30082703e+00 3.34633321e-01 8.65424156e-01 -8.75409484e-01 1.61978090e+00 -1.32660246e+00 -4.43697497e-02 2.81152606e-01 -2.61993498e-01 -9.32519078e-01 -5.96193194e-01 -1.23518765e+00 -5.33532679e-01 -5.83747849e-02 5.96577883e-01 -1.13057327e+00 3.42365682e-01 8.74560475e-01 -2.82833427e-01 -6.42737269e-01 -1.06996536e+00 -1.32016802e+00 -3.35779637e-02 -1.45572275e-01 4.90409225e-01 7.63798356e-01 6.83744550e-01 1.09839931e-01 -6.36873543e-02 -1.00294888e-01 5.33176839e-01 9.55312885e-03 4.41501856e-01 -1.34294486e+00 3.86843324e-01 -5.75816095e-01 -3.07655483e-01 -9.45992947e-01 -8.85957032e-02 -8.12076271e-01 -6.53862000e-01 -1.28511906e+00 -8.32044985e-03 -1.91056758e-01 -1.11109078e-01 -1.65725678e-01 3.67937148e-01 2.13746816e-01 1.20859891e-02 1.03788137e-01 -3.71160030e-01 6.18435517e-02 1.29639816e+00 6.91750320e-05 -1.62315920e-01 4.85058486e-01 -4.81304944e-01 7.84440815e-01 8.58408585e-02 -2.99253196e-01 -6.78878546e-01 6.11881316e-02 6.69384480e-01 4.61409837e-02 3.24159935e-02 -7.42885649e-01 5.37211418e-01 -3.75702560e-01 4.78586555e-01 -1.32223868e+00 1.30741090e-01 -9.61415648e-01 6.95283338e-02 9.40189242e-01 2.74610907e-01 1.20424610e-02 8.66204947e-02 5.39500564e-02 -1.44871444e-01 -5.70943117e-01 9.21121240e-01 -4.07591403e-01 -4.92852688e-01 -5.20386267e-03 -1.03226590e+00 8.97834301e-02 9.92593169e-01 -7.84614205e-01 -3.59281451e-01 -4.20183957e-01 -8.29068601e-01 -1.95836127e-02 6.50830388e-01 3.03609259e-02 7.30431557e-01 -1.51530886e+00 -2.30721906e-01 7.18729138e-01 -3.22939813e-01 -3.74400020e-01 -1.70157343e-01 6.58265352e-01 -1.32361674e+00 1.02442718e+00 -5.41665435e-01 -4.55340147e-01 -1.14228773e+00 4.78126436e-01 4.28307921e-01 -2.41845414e-01 -2.15481281e-01 1.11954463e+00 2.71224789e-02 -8.23025763e-01 1.85185194e-01 -9.21545625e-02 -7.54407048e-01 3.55081353e-03 6.88606799e-01 1.05194807e+00 -2.91290224e-01 -6.04341030e-01 -4.56784427e-01 6.65885091e-01 2.32151806e-01 -2.87484169e-01 9.17833567e-01 -2.19243199e-01 -9.89108324e-01 4.28274393e-01 8.38715494e-01 -1.36269778e-01 -3.69319022e-02 4.16855574e-01 1.25943512e-01 -8.02164078e-01 -4.32406247e-01 -3.55811834e-01 -1.85641110e-01 5.54822803e-01 5.34874737e-01 8.99602413e-01 8.57008278e-01 -3.02566767e-01 8.18335712e-01 9.66778398e-01 5.72402716e-01 -1.68019545e+00 -2.13140488e-01 6.89524531e-01 9.12339568e-01 -9.28350806e-01 5.44190466e-01 -7.27165341e-01 -4.14997995e-01 1.32979155e+00 4.68304873e-01 -1.55325383e-01 1.27306652e+00 5.74917436e-01 1.14069022e-02 -3.70670199e-01 -9.44949508e-01 1.12705544e-01 3.75366658e-01 1.11147714e+00 5.06513238e-01 5.07374525e-01 -9.66500878e-01 3.21953118e-01 -7.28706717e-01 -2.34555230e-01 4.90474731e-01 1.41972518e+00 -6.43810987e-01 -1.20391917e+00 -7.23931909e-01 4.61561680e-01 -5.49773455e-01 -1.16372630e-01 -5.28106689e-01 8.46754074e-01 -5.76629937e-02 1.49448860e+00 -1.97535474e-03 -5.03491640e-01 4.11356747e-01 1.41089618e-01 7.21762300e-01 -1.23501487e-01 -9.04846430e-01 4.15413082e-01 3.84890139e-01 -1.23056793e+00 -8.58632207e-01 -1.05834293e+00 -1.40667629e+00 -1.19437599e+00 -5.12782812e-01 1.89310342e-01 3.83317530e-01 3.90289724e-01 -2.06836104e-01 2.85260603e-02 9.80917513e-01 -1.07949340e+00 -3.90341938e-01 -9.39418614e-01 -1.00026262e+00 -7.84516707e-02 2.89751232e-01 -8.00943017e-01 -7.83523321e-01 2.83909619e-01]	[-7.328296184539795, 3.64961838722229]
01aaed08-10cf-41ab-9854-d902f9f86957	unsupervised-deep-video-denoising	2011.15045	null	https://arxiv.org/abs/2011.15045v3	https://arxiv.org/pdf/2011.15045v3.pdf	Unsupervised Deep Video Denoising	Deep convolutional neural networks (CNNs) for video denoising are typically trained with supervision, assuming the availability of clean videos. However, in many applications, such as microscopy, noiseless videos are not available. To address this, we propose an Unsupervised Deep Video Denoiser (UDVD), a CNN architecture designed to be trained exclusively with noisy data. The performance of UDVD is comparable to the supervised state-of-the-art, even when trained only on a single short noisy video. We demonstrate the promise of our approach in real-world imaging applications by denoising raw video, fluorescence-microscopy and electron-microscopy data. In contrast to many current approaches to video denoising, UDVD does not require explicit motion compensation. This is advantageous because motion compensation is computationally expensive, and can be unreliable when the input data are noisy. A gradient-based analysis reveals that UDVD automatically adapts to local motion in the input noisy videos. Thus, the network learns to perform implicit motion compensation, even though it is only trained for denoising.	['Carlos Fernandez-Granda', 'Eero P. Simoncelli', 'Mitesh M. Khapra', 'Peter A. Crozier', 'Ramon Manzorro', 'Joshua L. Vincent', 'Sreyas Mohan', 'Dev Yashpal Sheth']	2020-11-30	null	http://openaccess.thecvf.com//content/ICCV2021/html/Sheth_Unsupervised_Deep_Video_Denoising_ICCV_2021_paper.html	http://openaccess.thecvf.com//content/ICCV2021/papers/Sheth_Unsupervised_Deep_Video_Denoising_ICCV_2021_paper.pdf	iccv-2021-1	['video-denoising']	['computer-vision']	[ 4.70833540e-01 -2.31947213e-01 3.12855273e-01 -1.97513118e-01 -6.30726993e-01 -5.28191447e-01 3.45250517e-01 -1.88992694e-01 -8.98956001e-01 7.05048800e-01 1.03576027e-01 5.53099625e-03 2.19813958e-01 -3.75065923e-01 -1.04551446e+00 -1.05586004e+00 9.81757343e-02 -3.24471947e-03 1.00648813e-01 -1.01240762e-02 3.52552459e-02 4.63951290e-01 -1.37046373e+00 2.46185869e-01 3.78552884e-01 7.44512260e-01 4.94074911e-01 9.96445358e-01 2.50281155e-01 8.37990642e-01 -5.78477561e-01 -9.01744813e-02 2.52706200e-01 -6.25731230e-01 -7.71607339e-01 1.80986211e-01 4.71604705e-01 -9.83035147e-01 -6.90010011e-01 1.09573483e+00 4.72431779e-01 2.71425962e-01 2.62047470e-01 -7.38851011e-01 -5.50400555e-01 8.57495237e-03 -1.28854945e-01 6.87023997e-01 5.32554872e-02 4.26584423e-01 4.52488571e-01 -6.90801620e-01 1.23119128e+00 9.93622243e-01 8.38643253e-01 9.82589304e-01 -1.63254476e+00 1.40387537e-02 1.23040572e-01 9.41423103e-02 -8.40366364e-01 -7.49158919e-01 5.56620181e-01 -3.33500117e-01 8.24158907e-01 -6.26308694e-02 5.97491443e-01 1.34806776e+00 2.70076662e-01 6.42037988e-01 8.73194337e-01 -1.81254879e-01 4.29564625e-01 -5.52154183e-01 -2.34958515e-01 4.22569335e-01 1.05234720e-01 9.91999172e-03 -5.90947151e-01 1.18658185e-01 9.79804873e-01 2.55575299e-01 -5.59499621e-01 -3.37526023e-01 -1.42885029e+00 4.50890511e-01 1.18987657e-01 3.50566596e-01 -5.22970855e-01 4.37915623e-01 6.08248174e-01 5.60036719e-01 5.99938035e-01 1.96143791e-01 -4.60547060e-01 -4.25147980e-01 -1.29344189e+00 1.51254401e-01 5.80478430e-01 5.02004862e-01 6.74989820e-01 3.56061518e-01 2.15867609e-01 4.60394710e-01 -6.34190291e-02 8.84063467e-02 5.43369412e-01 -1.64178944e+00 -9.51995552e-02 -2.87030824e-02 2.11100876e-01 -8.35202694e-01 -3.53443354e-01 -7.13767111e-02 -1.19367838e+00 5.44604063e-01 6.38950706e-01 -5.96606694e-02 -1.06773293e+00 1.81435645e+00 2.78664529e-01 4.29081023e-01 5.00694364e-02 1.17830157e+00 6.99038208e-01 5.02132893e-01 -3.73349413e-02 -4.88465220e-01 6.91218913e-01 -6.91082895e-01 -9.71878171e-01 -3.02783847e-02 5.02057135e-01 -5.93181551e-01 7.63914704e-01 7.43924618e-01 -1.08471394e+00 -4.44113851e-01 -9.53911245e-01 -3.43826294e-01 -2.10176751e-01 -1.20016508e-01 4.21819985e-01 2.61321634e-01 -1.38579941e+00 1.16702664e+00 -1.42238510e+00 -4.75420505e-01 5.65954745e-01 5.05721927e-01 -9.31090415e-01 -3.60167861e-01 -7.57457078e-01 6.24168754e-01 1.00701034e-01 5.32467902e-01 -1.44588840e+00 -5.13181746e-01 -7.29738235e-01 -1.66458322e-03 -7.44437054e-03 -7.43528247e-01 1.28038359e+00 -1.35528743e+00 -1.60845923e+00 8.25783014e-01 -3.14742774e-01 -5.78864038e-01 8.31013024e-01 -2.12275565e-01 7.86851272e-02 6.70986474e-01 -4.46381904e-02 6.05959535e-01 1.08505571e+00 -1.18917561e+00 -1.97089478e-01 -1.70466542e-01 -3.11576650e-02 -7.20340312e-02 -1.60662934e-01 -3.16449217e-02 -4.64883387e-01 -7.03572631e-01 5.14949225e-02 -6.57566607e-01 -4.42351669e-01 3.71497512e-01 -1.63132586e-02 3.75012517e-01 1.29856372e+00 -9.10319626e-01 6.82842791e-01 -2.30899668e+00 5.21309495e-01 -2.89700627e-01 5.10620236e-01 4.97025520e-01 -2.26972595e-01 3.13067555e-01 -1.20849781e-01 -2.61650584e-03 -4.02645499e-01 -5.39801776e-01 -4.39027995e-01 6.10518277e-01 8.52720067e-02 8.71336281e-01 3.40736926e-01 7.43662715e-01 -1.11480129e+00 -5.05200811e-02 2.54921019e-01 9.02423620e-01 -5.22778571e-01 3.55284691e-01 -1.62025750e-01 1.09414232e+00 -2.23536175e-02 5.02909660e-01 6.83054209e-01 -2.51725048e-01 4.48509008e-01 -3.08255345e-01 -1.36951366e-02 -7.87927117e-03 -9.45869327e-01 1.90848279e+00 -1.54997781e-01 1.08199680e+00 7.44859636e-01 -1.40723848e+00 3.08525205e-01 5.29678404e-01 6.25284135e-01 -4.70285505e-01 1.73948750e-01 2.55036235e-01 -2.34968662e-01 -8.05866659e-01 2.42853224e-01 -1.66891634e-01 6.65102363e-01 3.16985220e-01 4.31753784e-01 5.85998371e-02 4.29849207e-01 2.48971403e-01 1.69306409e+00 4.21181053e-01 -5.55320643e-02 -1.18107766e-01 1.83867350e-01 -1.54653341e-01 7.41820693e-01 7.76431918e-01 -4.88759249e-01 9.79948759e-01 5.80864966e-01 -7.29022443e-01 -1.42944419e+00 -6.68276608e-01 1.25361800e-01 8.33053231e-01 9.91472155e-02 -1.65973574e-01 -1.10452545e+00 -5.01715779e-01 -3.72198373e-01 -1.74963623e-01 -5.90258777e-01 1.35408752e-02 -6.62589967e-01 -6.41013741e-01 3.48772705e-01 3.30520988e-01 3.41383755e-01 -1.03806686e+00 -7.32837021e-01 5.99326015e-01 -1.85431719e-01 -1.40848815e+00 -2.95222461e-01 4.33626443e-01 -1.12303185e+00 -1.07073069e+00 -8.60670328e-01 -8.42543900e-01 8.47993255e-01 4.33239520e-01 1.05778432e+00 4.12514895e-01 -2.77722359e-01 5.33137679e-01 -2.28754893e-01 1.20485790e-01 -4.00654286e-01 -2.04942986e-01 9.22031477e-02 -4.41897511e-02 1.48912460e-01 -9.49275613e-01 -8.77095878e-01 1.88481882e-02 -1.54554451e+00 -2.17962325e-01 4.24637496e-01 1.34449005e+00 7.72973478e-01 6.16005696e-02 3.34710032e-01 -9.51422751e-01 3.94337714e-01 -3.15437704e-01 -4.83135313e-01 -3.47800493e-01 -1.73487648e-01 -1.48158804e-01 8.85570824e-01 -5.43321311e-01 -8.86284590e-01 2.74991333e-01 -3.89600337e-01 -7.76381373e-01 -5.16836643e-01 5.80754161e-01 8.24633315e-02 -3.12747747e-01 5.93022406e-01 3.05137604e-01 3.72202784e-01 -5.69885433e-01 1.85534433e-02 3.07556450e-01 9.81475174e-01 -1.55292481e-01 5.53898811e-01 1.10891640e+00 7.87396077e-03 -1.12717402e+00 -6.10355556e-01 -5.58885336e-01 -7.73103058e-01 -2.72079766e-01 1.07047212e+00 -8.50347042e-01 -7.48362422e-01 6.81998670e-01 -1.22930956e+00 -6.27267420e-01 -2.15210095e-01 4.82008457e-01 -6.91770792e-01 7.90959477e-01 -1.12996078e+00 -5.22915542e-01 -1.64744914e-01 -1.21599782e+00 1.01278019e+00 3.46264765e-02 -1.87707543e-02 -1.02201366e+00 -5.26801050e-02 1.58732176e-01 4.00612175e-01 4.68442112e-01 5.89865267e-01 -2.25646645e-01 -7.35893726e-01 -1.61715969e-01 1.00115156e-02 7.98160255e-01 -3.56187997e-03 5.64437397e-02 -9.60555255e-01 -4.81209308e-01 3.15704644e-01 -4.13119316e-01 1.11296356e+00 7.55802453e-01 1.23941827e+00 -1.35524914e-01 7.70657212e-02 9.97021854e-01 1.44839466e+00 -6.02212846e-02 8.29000175e-01 5.32947063e-01 6.47899210e-01 3.98110211e-01 1.37686849e-01 1.16421424e-01 -4.03468721e-02 2.47498885e-01 8.13458800e-01 -3.55424315e-01 -2.01222107e-01 1.50427207e-01 4.29728091e-01 8.61835122e-01 -3.59254539e-01 -1.88520342e-01 -5.77563226e-01 7.04758704e-01 -1.87431288e+00 -1.00794160e+00 -1.93532363e-01 1.96295547e+00 7.22179592e-01 -8.56732428e-02 -5.85090220e-02 2.18504325e-01 5.13190329e-01 5.68151027e-02 -6.10252619e-01 -6.73695430e-02 -3.35209846e-01 1.96199358e-01 4.15597618e-01 3.00460935e-01 -1.22376513e+00 6.51719809e-01 7.10162497e+00 3.58757466e-01 -1.41036296e+00 2.81135708e-01 6.52560174e-01 -2.11915374e-01 2.80672330e-02 -5.57164811e-02 -1.53625637e-01 5.38187385e-01 9.03442740e-01 4.06179994e-01 6.36279821e-01 5.55052102e-01 6.91574633e-01 -2.82145679e-01 -1.11303973e+00 1.07580769e+00 -1.60843596e-01 -1.59164345e+00 -2.21121579e-01 2.01626513e-02 7.16379046e-01 1.84364825e-01 -1.18347779e-01 -1.36352718e-01 4.93531190e-02 -1.00451279e+00 4.36393291e-01 4.65086222e-01 6.68107450e-01 -6.01545513e-01 9.49514806e-01 3.64833593e-01 -6.32049561e-01 1.23285465e-01 -5.49369037e-01 -1.18914088e-02 3.72770965e-01 8.01539838e-01 -2.45690018e-01 3.40224415e-01 1.11099756e+00 9.58283782e-01 -1.24657005e-01 7.69504905e-01 -2.77942661e-02 6.54556513e-01 -2.45607153e-01 6.27012193e-01 2.63329953e-01 -3.45499277e-01 6.04046524e-01 1.28790736e+00 2.73187637e-01 1.38498843e-01 -7.55699351e-02 4.67225730e-01 -3.83625805e-01 -4.31856811e-01 -6.97898626e-01 -1.95669696e-01 -6.56565130e-02 1.25061369e+00 -7.92237639e-01 -3.18274379e-01 -4.90673810e-01 1.35057485e+00 3.61325741e-01 7.41136312e-01 -3.59766692e-01 -2.09755346e-01 6.85772300e-01 9.44161117e-02 5.99247813e-01 -5.20329475e-01 1.20108299e-01 -1.47504449e+00 9.36557353e-03 -9.17011678e-01 5.73789962e-02 -9.03573930e-01 -1.16223419e+00 3.90462518e-01 -4.47385967e-01 -1.08528769e+00 -2.37736091e-01 -6.76714838e-01 -5.31999707e-01 4.47428763e-01 -1.59178281e+00 -8.88758779e-01 -3.59376907e-01 5.16574860e-01 5.89611530e-01 1.75246567e-01 7.09682167e-01 4.49001342e-01 -4.74402934e-01 1.00155808e-01 6.65108979e-01 1.58717573e-01 7.86096752e-01 -1.16750205e+00 2.55443037e-01 1.20021713e+00 -2.48120263e-01 7.34093189e-01 1.02811182e+00 -4.13190484e-01 -1.58192718e+00 -1.06392407e+00 5.71727395e-01 -1.66419953e-01 6.09213769e-01 -2.37278774e-01 -1.27089095e+00 7.18487263e-01 4.28540349e-01 5.31868339e-01 4.89662647e-01 -5.74438453e-01 -1.12224981e-01 -2.52192598e-02 -1.18822622e+00 4.65462506e-01 9.53667581e-01 -5.84479868e-01 -2.58875728e-01 4.56197649e-01 4.72395688e-01 -4.83852476e-01 -9.22611237e-01 -2.77964529e-02 4.80327785e-01 -1.21297550e+00 9.92858887e-01 -5.69974244e-01 5.64470887e-01 -5.64527810e-01 4.91658896e-02 -1.36548877e+00 -9.62814465e-02 -9.62799966e-01 -3.94927800e-01 8.28680754e-01 -1.36699483e-01 -2.72325903e-01 9.32109475e-01 3.33907723e-01 -2.47274488e-01 -3.56705725e-01 -1.06780076e+00 -7.74444222e-01 -2.15606794e-01 -1.71549365e-01 -2.39714757e-02 1.01931620e+00 -4.14161831e-01 -1.02379687e-01 -6.89486265e-01 5.89891560e-02 7.78043807e-01 -4.24009591e-01 6.28698349e-01 -9.17561948e-01 -2.43386626e-01 -4.77871150e-02 -7.61723578e-01 -1.05007529e+00 1.97975472e-01 -3.67005825e-01 4.17366356e-01 -1.36994529e+00 4.99842353e-02 3.49477381e-01 -1.46541297e-01 3.40043426e-01 -9.68931522e-03 6.26146615e-01 -1.40695497e-01 3.78738135e-01 -5.79930604e-01 3.80253911e-01 1.29467130e+00 -1.70681864e-01 -9.46766604e-03 -3.76235574e-01 -3.11324000e-01 7.70005345e-01 6.34463429e-01 -5.71865737e-01 -1.86358541e-01 -7.90982306e-01 2.06419732e-02 -9.35445055e-02 5.41219890e-01 -8.89181018e-01 3.78813893e-01 2.34172624e-02 5.86482167e-01 -1.60047784e-01 2.80532777e-01 -7.33887255e-01 3.59546572e-01 5.03264070e-01 -1.92614913e-01 -6.01138324e-02 -3.35005149e-02 8.80071044e-01 -5.11020660e-01 -1.48460001e-01 1.09840572e+00 -5.35714090e-01 -7.40817189e-01 2.81999737e-01 -9.34881747e-01 -1.13643661e-01 6.51362300e-01 -2.97427714e-01 -2.54024714e-01 -5.86952925e-01 -1.07003343e+00 -1.96999952e-01 7.58400500e-01 -2.80764759e-01 7.07210541e-01 -1.07465255e+00 -3.75057399e-01 1.80832729e-01 -2.94825286e-01 3.81458700e-01 4.43091065e-01 1.06531429e+00 -9.95121479e-01 -9.71764252e-02 -2.69773632e-01 -7.93678761e-01 -1.19647622e+00 6.32330358e-01 4.00110960e-01 -8.56334642e-02 -8.84458899e-01 7.12961793e-01 1.06366843e-01 -1.76294833e-01 2.23885119e-01 -3.28749508e-01 1.22400131e-02 -2.62333602e-01 7.26720273e-01 1.98245123e-01 3.59503120e-01 -4.89747018e-01 3.02880853e-02 3.13576072e-01 -4.96652462e-02 7.76645914e-02 1.87803423e+00 -3.48987550e-01 -3.88177395e-01 1.91851377e-01 1.25633800e+00 -4.53519762e-01 -1.80621135e+00 1.46596169e-03 -1.61913037e-01 -4.34594542e-01 3.02437037e-01 -1.28033757e-01 -1.30092752e+00 9.36852694e-01 5.45638740e-01 1.97356269e-01 1.29637241e+00 -5.25677323e-01 9.27276313e-01 6.02861702e-01 7.10495412e-02 -1.21434164e+00 1.09178245e-01 5.26239693e-01 4.54107404e-01 -1.26126349e+00 -1.27528474e-01 -9.31117684e-02 -2.27527812e-01 1.33677065e+00 2.57989883e-01 -2.77770042e-01 4.89256948e-01 3.40087742e-01 2.96351582e-01 -1.75235689e-01 -9.13279235e-01 -1.14981234e-01 -3.59915197e-01 9.53846753e-01 3.51313919e-01 -7.17884123e-01 -6.29987344e-02 1.62870008e-02 5.31095088e-01 3.87847066e-01 9.05326307e-01 1.43767905e+00 -2.56527245e-01 -8.56726587e-01 -2.67499119e-01 3.95139843e-01 -9.13379014e-01 -2.94116400e-02 -1.78701445e-01 5.84958434e-01 -2.18040794e-02 8.37385833e-01 -3.18623260e-02 -2.29640026e-02 1.21748306e-01 -1.24550156e-01 4.56051111e-01 -4.53547180e-01 -4.99783963e-01 4.34397936e-01 -2.02343628e-01 -8.28141034e-01 -1.02992344e+00 -5.50667882e-01 -9.31535840e-01 -5.95807910e-01 5.20358142e-03 -1.01939783e-01 5.49465775e-01 9.79717374e-01 3.01075429e-01 6.29192233e-01 3.18070620e-01 -1.53796387e+00 -2.05133572e-01 -6.90702140e-01 -7.39030600e-01 6.99263215e-01 1.01820338e+00 -3.69260132e-01 -7.25072443e-01 8.75659943e-01]	[11.50440788269043, -2.1845409870147705]
950d7429-c1bd-47c9-94ab-cd5655a0b284	nbmod-find-it-and-grasp-it-in-noisy	2306.10265	null	https://arxiv.org/abs/2306.10265v1	https://arxiv.org/pdf/2306.10265v1.pdf	NBMOD: Find It and Grasp It in Noisy Background	Grasping objects is a fundamental yet important capability of robots, and many tasks such as sorting and picking rely on this skill. The prerequisite for stable grasping is the ability to correctly identify suitable grasping positions. However, finding appropriate grasping points is challenging due to the diverse shapes, varying density distributions, and significant differences between the barycenter of various objects. In the past few years, researchers have proposed many methods to address the above-mentioned issues and achieved very good results on publicly available datasets such as the Cornell dataset and the Jacquard dataset. The problem is that the backgrounds of Cornell and Jacquard datasets are relatively simple - typically just a whiteboard, while in real-world operational environments, the background could be complex and noisy. Moreover, in real-world scenarios, robots usually only need to grasp fixed types of objects. To address the aforementioned issues, we proposed a large-scale grasp detection dataset called NBMOD: Noisy Background Multi-Object Dataset for grasp detection, which consists of 31,500 RGB-D images of 20 different types of fruits. Accurate prediction of angles has always been a challenging problem in the detection task of oriented bounding boxes. This paper presents a Rotation Anchor Mechanism (RAM) to address this issue. Considering the high real-time requirement of robotic systems, we propose a series of lightweight architectures called RA-GraspNet (GraspNet with Rotation Anchor): RARA (network with Rotation Anchor and Region Attention), RAST (network with Rotation Anchor and Semi Transformer), and RAGT (network with Rotation Anchor and Global Transformer) to tackle this problem. Among them, the RAGT-3/3 model achieves an accuracy of 99% on the NBMOD dataset. The NBMOD and our code are available at https://github.com/kmittle/Grasp-Detection-NBMOD.	['Qianqiu Tan', 'Yuchen Liu', 'Baohua Zhang', 'Congmin Guo', 'Xinyu Zhou', 'Boyuan Cao']	2023-06-17	null	null	null	null	['robotic-grasping']	['robots']	[-2.07643852e-01 -5.39914668e-01 1.29591629e-01 -1.63790047e-01 -1.69242948e-01 -7.17008770e-01 -6.59395941e-03 1.03192814e-01 -1.06182352e-01 2.23065302e-01 -5.11781812e-01 -2.74283960e-02 -3.17426383e-01 -8.76543701e-01 -8.41579616e-01 -1.02906930e+00 -3.61134022e-01 5.37533641e-01 6.24531090e-01 -3.38758945e-01 3.46284568e-01 7.79531002e-01 -1.74042737e+00 1.47410572e-01 7.31311083e-01 1.24593711e+00 1.06878805e+00 4.70185071e-01 -4.58618589e-02 1.47309229e-01 -6.63903177e-01 -4.28624712e-02 4.97947186e-01 1.43697292e-01 -2.49775544e-01 -2.29526863e-01 -2.04801783e-02 -6.94314420e-01 -1.59718245e-01 1.05257952e+00 5.48108339e-01 -1.26892596e-01 6.22377515e-01 -1.57535052e+00 -5.23077190e-01 6.74086273e-01 -8.10509086e-01 -1.62961334e-01 2.40921631e-01 2.31407478e-01 5.77904105e-01 -8.70674610e-01 2.98166692e-01 1.48044157e+00 3.57496858e-01 4.20709193e-01 -8.51509690e-01 -7.32868135e-01 2.64787823e-01 2.14740843e-01 -1.14548767e+00 1.59633383e-01 6.92123830e-01 -3.01086992e-01 3.96933973e-01 1.06235065e-01 6.49696887e-01 1.25480270e+00 1.68321863e-01 1.02894795e+00 9.84789968e-01 -2.07408145e-01 2.66096205e-01 -2.55990893e-01 1.08909898e-01 4.61808562e-01 6.65252864e-01 -2.64741063e-01 -1.25057846e-01 -4.22745384e-03 1.22121465e+00 2.98955619e-01 -2.72242129e-01 -8.02119255e-01 -1.44289756e+00 4.28852111e-01 7.86103606e-01 2.27418631e-01 -5.93674839e-01 1.71612591e-01 3.38741302e-01 -7.88647383e-02 -2.31718898e-01 1.97273150e-01 -5.06835938e-01 1.34620154e-02 -4.57468070e-02 3.07401747e-01 9.77187097e-01 1.68664813e+00 4.76187259e-01 -2.82347471e-01 1.02375388e-01 8.35183263e-01 2.57968128e-01 8.64576876e-01 7.90495947e-02 -7.49392927e-01 5.58862507e-01 6.11953497e-01 4.40735847e-01 -1.38525915e+00 -6.33951008e-01 -8.07430781e-03 -9.41971183e-01 2.78914064e-01 7.32260942e-01 1.09421477e-01 -9.21755791e-01 1.35339057e+00 5.95826387e-01 -5.27161002e-01 -1.40900686e-01 1.27648890e+00 8.08000982e-01 5.64878464e-01 -5.24798371e-02 1.67071626e-01 1.40311325e+00 -7.63040781e-01 -4.98389751e-01 -1.46613434e-01 6.86567128e-02 -8.96062613e-01 1.10971940e+00 7.17856288e-01 -7.40708411e-01 -5.20377278e-01 -8.62514377e-01 2.75050938e-01 -3.81391436e-01 7.17207789e-01 8.07010174e-01 1.78806588e-01 -5.26162207e-01 4.37172055e-01 -9.00632977e-01 -4.55373853e-01 2.53449142e-01 3.28952432e-01 -2.98324585e-01 -5.23450553e-01 -6.16365850e-01 9.40423310e-01 4.34580892e-01 7.39513934e-01 -9.96961117e-01 -1.90735608e-01 -4.02267337e-01 -1.39535010e-01 7.56741405e-01 -7.21310545e-03 1.01750994e+00 -5.48011839e-01 -1.47960830e+00 4.49982971e-01 3.49672914e-01 3.01965952e-01 7.13587284e-01 -5.56565940e-01 2.30850860e-01 2.04796046e-01 -6.38949350e-02 4.33450311e-01 8.45369756e-01 -1.63871717e+00 -4.75873441e-01 -6.72102988e-01 3.65910530e-01 -4.88981903e-02 -1.84351221e-01 4.43763435e-02 -3.47415149e-01 -6.26557648e-01 6.09607518e-01 -9.38294947e-01 -1.34260347e-02 2.02850938e-01 -4.08585757e-01 -4.11198288e-01 1.22126043e+00 -5.61651051e-01 3.94760221e-01 -2.14959192e+00 3.17378163e-01 -1.75671633e-02 -2.60293365e-01 2.66945213e-01 -2.78325260e-01 4.03980583e-01 2.51928151e-01 -3.62042427e-01 1.47728950e-01 3.64484191e-01 2.77376864e-02 3.16881359e-01 -3.18630636e-01 5.40469825e-01 1.87732205e-01 5.26835144e-01 -1.10755622e+00 -4.43363219e-01 4.53758448e-01 2.89213538e-01 -1.93087429e-01 3.99044484e-01 -4.99276608e-01 3.90491664e-01 -7.72546351e-01 1.44076180e+00 1.10239172e+00 5.44338338e-02 1.79155841e-01 -7.21159875e-01 -1.66137218e-01 -4.98619944e-01 -1.48823345e+00 1.44294119e+00 -1.53904468e-01 -1.54574709e-02 6.74336076e-01 -9.06187654e-01 1.33553326e+00 -8.34271486e-04 6.06586456e-01 -2.56507993e-01 3.71106178e-01 5.55417895e-01 5.75900339e-02 -7.76440263e-01 4.96136010e-01 5.90483785e-01 1.46296799e-01 -1.21588986e-02 -2.02299386e-01 -4.65140849e-01 2.40207464e-01 -1.09815352e-01 1.08686638e+00 6.03683591e-01 -1.85536459e-01 -2.57674396e-01 5.79335615e-02 1.68171406e-01 5.40587008e-01 6.20325863e-01 -2.59019226e-01 6.48290515e-01 4.90379661e-01 -4.66012269e-01 -8.15041721e-01 -9.98981416e-01 -8.53845626e-02 8.88803124e-01 8.58600140e-01 3.70133407e-02 -4.57113743e-01 -3.87724012e-01 4.89542484e-01 2.36623421e-01 -3.74864876e-01 9.51360464e-02 -7.92159140e-01 -7.61845767e-01 8.26878175e-02 7.80237436e-01 6.95077956e-01 -1.28130734e+00 -1.13182068e+00 2.65055329e-01 -1.86770692e-01 -1.21765840e+00 1.39880031e-01 4.38091964e-01 -7.48505652e-01 -1.41471457e+00 -1.06031787e+00 -9.51620281e-01 9.19306278e-01 7.58440077e-01 7.43306339e-01 1.15246981e-01 -7.36530781e-01 2.74534613e-01 -9.40548539e-01 -6.85407400e-01 -7.72970393e-02 -9.06407312e-02 7.36818388e-02 -4.87974346e-01 2.62134463e-01 -2.20138893e-01 -6.95151389e-01 9.57301795e-01 -8.42488289e-01 -1.15552984e-01 7.94740319e-01 6.99815333e-01 4.06154007e-01 -8.80641490e-02 5.41786373e-01 8.77438635e-02 2.79239684e-01 -4.30289060e-01 -9.88980949e-01 4.11508828e-01 2.69771457e-01 -4.76956487e-01 4.06536281e-01 -8.12252164e-01 -5.21418512e-01 1.46129072e-01 3.20097417e-01 -8.08866680e-01 -1.82377741e-01 1.37050748e-01 -3.14846933e-01 -9.40472558e-02 2.86542147e-01 -1.40738219e-01 1.67691991e-01 -4.80541766e-01 1.75158828e-02 9.13846493e-01 4.11393434e-01 -9.24989283e-01 4.94105935e-01 2.44879276e-01 8.81289393e-02 -8.82466137e-01 -4.47448313e-01 -4.09380019e-01 -7.51663029e-01 -5.80895483e-01 6.27713203e-01 -6.77502155e-01 -1.14158857e+00 9.85713661e-01 -1.37088287e+00 -4.58017737e-01 2.48443916e-01 4.68094528e-01 -4.81297404e-01 3.34562659e-01 -6.41791999e-01 -1.04052114e+00 -3.23532492e-01 -1.47810674e+00 1.19149816e+00 4.59556758e-01 2.33365849e-01 -7.91846663e-02 -8.16046655e-01 5.17616682e-02 4.69120026e-01 5.33235550e-01 8.76899540e-01 -2.16357410e-01 -8.90793025e-01 -2.21614733e-01 -5.23479998e-01 3.07508171e-01 5.53131282e-01 3.19645762e-01 -4.72717583e-01 -5.83494544e-01 -2.58994073e-01 -4.82583582e-01 4.86768901e-01 4.52949166e-01 1.37417555e+00 2.75060326e-01 -5.21138251e-01 1.75217345e-01 1.29384983e+00 3.24549019e-01 3.82049114e-01 4.30936247e-01 5.30508816e-01 6.03518844e-01 1.41864491e+00 6.48729980e-01 2.32999951e-01 5.99747300e-01 1.24799216e+00 2.41340965e-01 1.51037723e-01 1.76011726e-01 2.28874788e-01 6.52886689e-01 -5.22811353e-01 -2.49441162e-01 -8.46736372e-01 5.29554784e-01 -1.80999660e+00 -5.13811171e-01 -1.71024442e-01 2.08753991e+00 4.49507117e-01 -6.93683922e-02 8.65940377e-02 3.88159379e-02 9.62809741e-01 -2.58460701e-01 -8.27865958e-01 1.90116882e-01 -1.46888882e-01 -3.41528505e-01 5.51198423e-01 -2.43263140e-01 -1.12926698e+00 7.78556585e-01 4.87663889e+00 6.03725195e-01 -1.03977692e+00 -3.16607118e-01 5.97269014e-02 1.99276716e-01 3.78323615e-01 -3.13343555e-01 -8.06635797e-01 6.29010081e-01 -1.31240830e-01 5.53725719e-01 4.32361782e-01 1.32829678e+00 -1.48715645e-01 -5.75138688e-01 -1.03175485e+00 9.89488840e-01 1.09807393e-02 -5.62573731e-01 -1.80969611e-01 -2.47834772e-01 1.74491599e-01 -4.71838415e-02 -1.97119474e-01 2.36611322e-01 3.58598650e-01 -6.44132733e-01 1.01056075e+00 2.26973847e-01 5.40258646e-01 -3.52572948e-01 7.45626330e-01 4.06529754e-01 -1.15849471e+00 -4.18665886e-01 -8.70921135e-01 3.09253663e-01 -7.48694912e-02 6.22963309e-01 -6.12464070e-01 6.84020638e-01 1.37318552e+00 4.56829578e-01 -6.25430048e-02 1.22128642e+00 -2.75066108e-01 -7.75987953e-02 -5.98929584e-01 -5.21806836e-01 2.18347088e-02 -3.46558511e-01 6.20966554e-01 8.51249933e-01 5.95569134e-01 2.33617246e-01 3.80210042e-01 7.91513860e-01 2.88568407e-01 -1.88863143e-01 -4.26706284e-01 9.81842354e-02 5.33927500e-01 1.53643525e+00 -1.12590826e+00 4.14833091e-02 -1.01367369e-01 6.92665040e-01 1.08097978e-01 9.59917605e-02 -8.27540874e-01 -5.35423756e-01 5.10361731e-01 -2.00741753e-01 5.12923777e-01 -5.76228023e-01 -4.02452890e-03 -9.67067242e-01 4.59270656e-01 -9.10061181e-01 4.73650210e-02 -1.04408777e+00 -1.36517346e+00 3.49191695e-01 1.85582623e-01 -1.22984672e+00 4.13776696e-01 -1.31767595e+00 -1.92175284e-01 5.74006736e-01 -1.34683049e+00 -1.24137783e+00 -1.11121929e+00 3.44797760e-01 7.71023810e-01 5.14099821e-02 6.80641651e-01 1.36880457e-01 -5.85824072e-01 1.03407782e-02 1.95154682e-01 1.66175500e-01 6.94196641e-01 -1.06781435e+00 -1.91704944e-01 3.80100876e-01 -5.33309996e-01 5.40681541e-01 7.34537542e-01 -6.57625973e-01 -2.28151846e+00 -7.84301519e-01 -2.99494028e-01 -1.90934554e-01 5.60579360e-01 -4.44924802e-01 -8.20626676e-01 4.88984823e-01 -2.89142162e-01 1.05292946e-01 -1.89137444e-01 -2.91197658e-01 -6.69363588e-02 -2.90142924e-01 -1.29347932e+00 3.49097043e-01 9.73634481e-01 3.34175855e-01 -3.59410167e-01 5.17890692e-01 4.73033994e-01 -9.27707613e-01 -8.54803085e-01 8.01047683e-01 8.80222142e-01 -7.91368246e-01 1.04587781e+00 -5.60716204e-02 4.81323004e-01 -3.48557025e-01 -4.70651239e-01 -1.23218715e+00 -1.29086033e-01 -2.35702351e-01 -4.40434366e-02 1.11920714e+00 -3.57398987e-01 -6.12822890e-01 6.73335135e-01 4.28592712e-01 -1.00294158e-01 -7.88969815e-01 -6.55910254e-01 -9.77897227e-01 -1.79894045e-01 9.30017978e-02 7.49759078e-01 5.97065270e-01 -1.42944232e-01 -4.65603769e-01 5.60427643e-02 5.52374721e-01 6.99334562e-01 6.07764661e-01 1.07154918e+00 -1.25138927e+00 6.41630366e-02 -1.80843994e-01 -4.94586259e-01 -1.16159201e+00 -2.90200770e-01 -4.04208601e-01 4.66751397e-01 -1.70388997e+00 1.99512377e-01 -1.15046597e+00 -7.01141134e-02 6.50498867e-01 5.11289462e-02 -1.94926634e-01 4.71877158e-01 2.93860763e-01 -2.70277917e-01 4.75828439e-01 1.50212109e+00 -2.33426124e-01 -4.10584062e-02 1.32745251e-01 -4.50550215e-05 6.49444580e-01 8.63727629e-01 -1.48545295e-01 3.02295461e-02 -8.24781001e-01 -8.07063580e-02 -1.79559179e-02 7.09965885e-01 -1.01952684e+00 7.26813078e-02 -4.28656369e-01 4.35115457e-01 -1.03481233e+00 5.25881469e-01 -1.25574088e+00 -8.61029401e-02 6.60940289e-01 2.87062198e-01 1.50903523e-01 1.52706131e-01 4.68084306e-01 1.28197923e-01 -3.79275322e-01 6.60591543e-01 -3.88092488e-01 -7.21477211e-01 1.48762837e-01 -2.02413499e-02 -4.37866390e-01 1.52738571e+00 -1.02697663e-01 -6.91326976e-01 5.69682494e-02 -4.79886293e-01 4.85941619e-01 4.13780868e-01 7.52401233e-01 7.02012420e-01 -9.48641777e-01 -4.45516407e-01 1.08794019e-01 -7.54245520e-02 7.26825655e-01 9.44773331e-02 8.57738614e-01 -8.75876665e-01 1.33035749e-01 -5.16014218e-01 -1.01352465e+00 -1.11171269e+00 5.40883064e-01 -2.93090660e-03 3.38738233e-01 -5.73579371e-01 7.58508980e-01 -1.31964162e-01 -4.82205302e-01 6.42637253e-01 -8.29873860e-01 -1.21241976e-02 -5.00757471e-02 3.07184249e-01 6.35698438e-01 4.11475599e-02 -2.24991769e-01 -4.09473449e-01 6.68136179e-01 9.60146412e-02 6.51524127e-01 1.65048742e+00 2.63911366e-01 -4.24506634e-01 2.35096231e-01 5.18878877e-01 -3.55568826e-01 -1.29235041e+00 9.18063000e-02 -2.13859379e-01 -7.54380584e-01 -4.28005517e-01 -7.78806627e-01 -1.14578068e+00 7.82770872e-01 5.92465162e-01 2.90903389e-01 9.45749819e-01 1.21531650e-01 4.69431967e-01 6.46547198e-01 1.26965427e+00 -1.04332364e+00 3.72259229e-01 5.30307770e-01 1.42581379e+00 -1.33518422e+00 -3.05673797e-02 -8.00147414e-01 -3.54440272e-01 1.46156847e+00 1.22082543e+00 -2.16425583e-01 4.55635577e-01 4.24052745e-01 5.43123782e-02 -1.51482657e-01 -6.34045377e-02 1.25068948e-01 -4.21184570e-01 6.47404194e-01 -1.23044260e-01 1.74804598e-01 -1.31282527e-02 4.08466220e-01 7.70357624e-02 -6.30125254e-02 3.54357243e-01 1.50310493e+00 -5.51095724e-01 -7.62994587e-01 -8.40077817e-01 4.20887768e-01 -7.21110255e-02 6.02766812e-01 8.50355776e-04 8.76485705e-01 -4.88429330e-02 9.45991993e-01 -9.64212939e-02 -3.68423462e-01 6.25208855e-01 -5.29293895e-01 7.40759492e-01 -2.81252682e-01 -2.76140571e-01 -3.71470815e-03 -3.95052671e-01 -6.25904441e-01 -4.36822921e-01 -6.19957447e-01 -1.32305574e+00 -7.23060519e-02 -8.41381013e-01 -2.16034591e-01 1.11191964e+00 4.49537247e-01 2.07002908e-01 4.83555704e-01 5.70324779e-01 -1.52840328e+00 -1.01035285e+00 -1.18564856e+00 -8.17573309e-01 2.29402333e-01 1.91205030e-03 -1.24028766e+00 -1.67190045e-01 -3.04320514e-01]	[5.845089912414551, -0.9252120852470398]
75516527-0957-43a8-9a0a-eef483ca6f35	arrhythmia-detection-using-deep-convolutional	null	null	https://www.researchgate.net/publication/327602644_Arrhythmia_Detection_Using_Deep_Convolutional_Neural_Network_With_Long_Duration_ECG_Signals	https://www.researchgate.net/publication/327602644_Arrhythmia_Detection_Using_Deep_Convolutional_Neural_Network_With_Long_Duration_ECG_Signals	Arrhythmia Detection Using Deep Convolutional Neural Network With Long Duration ECG Signals	This article presents a new deep learning approach for cardiac arrhythmia (17 classes) detection based on long-duration electrocardiography (ECG) signal analysis. Cardiovascular disease prevention is one of the most important tasks of any health care system as about 50 million people are at risk of heart disease in the world. Although automatic analysis of the ECG signal is very popular, current methods are not satisfactory. The goal of our research was to design a new method based on deep learning to efficiently and quickly classify cardiac arrhythmias. Described research is based on 1000 ECG signal fragments from the MIT - BIH Arrhythmia database for one lead (MLII) from 45 persons. Approach based on the analysis of 10-s ECG signal fragments (not a single QRS complex) is applied (on average, 13 times less classifications/analysis). A complete end-to-end structure was designed instead of the hand-crafted feature extraction and selection used in traditional methods. Our main contribution is to design a new 1D-Convolutional Neural Network model (1D-CNN). Proposed method is 1) efficient, 2) fast (real-time classification) 3) non-complex and 4) simple to use (combined feature extraction and selection, and classification in one stage). Deep 1D-CNN achieved a recognition overall accuracy of 17 cardiac arrhythmia disorders (classes) at a level of 91.33% and classification time per single sample of 0.015 sec. Compared to the current research, our results are one of the best results to date, and our solution can be implemented in mobile devices and cloud computing.	['Ru-San Tan', 'Rajendra Acharya', 'Pawel Plawiak', 'Ozal Yildirima']	2018-09-01	null	null	null	computers-in-biology-and-medicine-2018-9	['arrhythmia-detection', 'electrocardiography-ecg']	['medical', 'methodology']	[ 7.58105516e-02 -4.10313934e-01 2.73909956e-01 -1.92762077e-01 -5.83169878e-01 -3.91410768e-01 -1.88722163e-01 3.78586382e-01 -5.61142564e-01 7.64186203e-01 -3.53475064e-01 -5.01202047e-01 -2.37663820e-01 -6.60649300e-01 -7.61945471e-02 -4.83939379e-01 -3.78619492e-01 3.09772193e-01 -3.28765154e-01 -8.03460646e-03 9.45189968e-02 9.02802825e-01 -1.22923660e+00 1.46058217e-01 5.86601198e-01 1.28733134e+00 -2.22581074e-01 1.16473174e+00 5.76379061e-01 4.25762147e-01 -8.73023510e-01 1.10465959e-01 1.62602082e-01 -7.20223129e-01 -5.53197682e-01 -1.94699526e-01 -6.75578341e-02 -2.70714700e-01 1.10915758e-01 4.17035669e-01 1.48577440e+00 -3.25957030e-01 5.89802325e-01 -8.17559838e-01 -5.33322543e-02 3.02603573e-01 -3.74677420e-01 7.26377368e-01 -3.68771702e-02 -7.86401331e-02 3.38037819e-01 -1.02334058e+00 2.77518213e-01 3.61872196e-01 1.34451401e+00 3.04815501e-01 -7.18040884e-01 -8.02473128e-01 -6.82333410e-01 6.38523549e-02 -1.74390519e+00 -2.09302381e-01 8.99867833e-01 -4.19911027e-01 1.19353223e+00 2.81160265e-01 1.16657472e+00 7.32791483e-01 6.11632884e-01 2.84582734e-01 8.19258630e-01 -3.41733426e-01 1.38654903e-01 1.06522292e-02 3.87088776e-01 6.42977417e-01 4.62236881e-01 -3.73394080e-02 -1.40269428e-01 -4.43146229e-01 7.98315704e-01 2.17264861e-01 -3.51824053e-02 4.31734249e-02 -1.26359510e+00 6.36211753e-01 -4.18834314e-02 6.24281228e-01 -7.52986729e-01 8.50413442e-02 8.99379849e-01 6.20478034e-01 1.58663884e-01 3.70895535e-01 -6.77263618e-01 -6.29124224e-01 -9.33596015e-01 4.62242901e-01 5.74019194e-01 5.32173038e-01 2.40432650e-01 5.33206463e-01 -2.24722728e-01 6.85935736e-01 -3.15615460e-02 4.31502879e-01 7.91664362e-01 -3.31800073e-01 1.04863316e-01 4.89407301e-01 3.12026367e-02 -1.11003017e+00 -9.62538481e-01 -1.29211390e+00 -1.41436648e+00 1.17543966e-01 2.33032539e-01 -8.36600721e-01 -7.09559202e-01 1.18848991e+00 -9.66413170e-02 2.28589196e-02 4.36935723e-02 8.21785510e-01 8.16017807e-01 4.16916698e-01 -1.47972718e-01 -4.09088373e-01 1.43611610e+00 -2.64160812e-01 -6.78729832e-01 4.43885922e-01 8.00673723e-01 -6.16669059e-01 5.88347733e-01 8.14851284e-01 -9.71835613e-01 -7.97967076e-01 -1.31989479e+00 2.56101936e-01 -2.18139961e-01 6.19579554e-01 5.87282479e-01 1.12800455e+00 -9.10542607e-01 6.40572250e-01 -6.49417222e-01 -4.40975070e-01 5.88083446e-01 7.86987126e-01 -1.98582470e-01 5.44617474e-01 -1.14001811e+00 6.42840147e-01 2.29502499e-01 2.74713516e-01 -7.85141706e-01 -4.93772089e-01 -3.94440323e-01 -7.85489753e-02 -2.01590344e-01 -6.46911323e-01 9.12176609e-01 -1.26201153e+00 -1.34494138e+00 8.16022635e-01 1.22777730e-01 -6.88318729e-01 4.14154053e-01 -4.41127509e-01 -5.18314838e-01 5.18870866e-03 -2.00647965e-01 -4.13459800e-02 7.16349065e-01 -4.72513795e-01 -5.63824058e-01 -5.22913158e-01 -4.90660518e-01 2.07494766e-01 -2.83027470e-01 2.60504484e-01 4.11324799e-02 -9.20573473e-01 9.08658467e-03 -8.85890484e-01 -1.67245567e-01 -2.96290219e-01 -1.07721843e-01 4.84453095e-03 7.07234085e-01 -8.81068408e-01 1.55597591e+00 -2.02399540e+00 -1.60928860e-01 2.30448127e-01 4.66563106e-01 8.31778526e-01 4.73402023e-01 4.15376842e-01 -4.66034114e-01 1.67222962e-01 -3.75828505e-01 3.66161801e-02 -5.22626996e-01 -1.95832506e-01 1.80171862e-01 6.55043900e-01 -3.36744674e-02 8.28540742e-01 -3.15822780e-01 -2.10317999e-01 3.22348714e-01 6.77318990e-01 -1.22143231e-01 -1.13418531e-02 7.25922883e-01 3.47702503e-01 -3.10754508e-01 8.06646526e-01 6.65731728e-01 1.59976691e-01 -1.65520608e-02 -4.53106940e-01 -6.51408732e-02 -1.32102683e-01 -1.29186976e+00 1.49773026e+00 -2.69337863e-01 5.85485756e-01 -4.75767225e-01 -1.28998029e+00 1.19440472e+00 9.42812741e-01 7.55010784e-01 -2.43740872e-01 4.58092034e-01 3.67691696e-01 4.23326999e-01 -6.77794456e-01 -3.30348611e-01 1.41671570e-02 1.24715092e-02 4.77135301e-01 4.13480736e-02 4.06047881e-01 -8.15057904e-02 -3.94956648e-01 1.10477078e+00 -1.48464084e-01 7.08277762e-01 -4.25963789e-01 5.11968672e-01 -3.20434511e-01 8.05397093e-01 8.21710229e-01 -5.18985152e-01 7.42225528e-01 3.46935093e-01 -1.32418132e+00 -8.58535528e-01 -7.13038087e-01 -8.53996053e-02 2.26516291e-01 -5.19610703e-01 -3.54522765e-01 -8.27127457e-01 -3.92776787e-01 -2.39594743e-01 -1.01994425e-01 -3.76177490e-01 5.77235222e-02 -8.52600694e-01 -1.12222421e+00 1.28035164e+00 6.51251793e-01 7.00475931e-01 -1.33245397e+00 -1.39402163e+00 5.74478626e-01 1.15949757e-01 -7.26994097e-01 -2.37992615e-04 4.71675396e-01 -1.27823853e+00 -1.02283728e+00 -8.16090167e-01 -8.28818798e-01 1.88759029e-01 -4.20143783e-01 1.03794575e+00 1.67937309e-01 -9.63996470e-01 -1.24568483e-02 -2.77457118e-01 -9.25800383e-01 7.61671290e-02 2.07517147e-01 2.24332079e-01 2.05885753e-01 4.41980660e-01 -6.59877002e-01 -7.84597993e-01 -2.09364578e-01 -3.41432840e-01 -2.28950426e-01 7.63311446e-01 9.31275249e-01 5.15992463e-01 2.91611850e-02 1.05671883e+00 -8.91623914e-01 9.44928229e-01 -2.48633981e-01 -2.89588094e-01 -1.46181658e-01 -8.33520412e-01 -6.81894541e-01 6.32351577e-01 -2.13509873e-01 -3.50087017e-01 3.79611671e-01 -3.90433609e-01 -3.69714856e-01 -4.11597759e-01 5.20618856e-01 1.83254033e-01 4.77221794e-02 7.38981366e-01 1.86195657e-01 -2.75788233e-02 -3.27408403e-01 -4.19036329e-01 9.84397054e-01 3.80247593e-01 -1.44738793e-01 2.70466119e-01 9.28228050e-02 1.72816351e-01 -1.12502468e+00 -1.06587321e-01 -3.13671172e-01 -7.48332381e-01 -1.94027364e-01 9.17427897e-01 -1.04316008e+00 -8.19342852e-01 8.82630944e-01 -1.07644629e+00 2.31218427e-01 4.97886129e-02 6.71384573e-01 -3.03955734e-01 2.46809676e-01 -6.16392434e-01 -1.17382014e+00 -1.30463278e+00 -6.85649574e-01 6.57945216e-01 2.14059874e-02 -5.43737769e-01 -5.91811240e-01 -2.82063372e-02 -1.00718088e-01 5.54366469e-01 9.62623358e-01 8.37835848e-01 -6.99863613e-01 6.07191250e-02 -6.22155666e-01 -1.59608312e-02 4.86474007e-01 3.25301230e-01 -6.55699670e-02 -1.03277242e+00 -3.37498277e-01 3.67653489e-01 1.75390430e-02 4.75755006e-01 7.20205307e-01 1.17269790e+00 1.70730188e-01 -1.54111803e-01 5.41988790e-01 1.57953548e+00 6.98305905e-01 6.61522985e-01 8.15504193e-02 6.60939753e-01 -1.39216095e-01 2.85796523e-01 6.66162193e-01 -8.60906541e-02 4.55288082e-01 1.05795294e-01 -6.20104849e-01 2.85977148e-03 5.61410546e-01 8.63001309e-03 8.79209518e-01 -6.52131081e-01 -2.48661786e-02 -1.21893990e+00 6.20994449e-01 -1.65803719e+00 -8.87690187e-01 -4.38908130e-01 2.29848218e+00 5.15433192e-01 2.29450807e-01 4.08391923e-01 9.68738019e-01 5.24243772e-01 -4.77843106e-01 -5.20694554e-01 -7.31534243e-01 -4.94570704e-03 8.46416414e-01 1.31164223e-01 7.10787103e-02 -1.27771819e+00 1.64787576e-01 5.77226782e+00 2.75393486e-01 -1.52136290e+00 8.28973278e-02 8.07357073e-01 1.13799740e-02 6.21919692e-01 -5.58536947e-01 -5.72487712e-01 4.27664965e-01 1.21469212e+00 1.96339205e-01 -5.17748557e-02 6.78436577e-01 2.73113281e-01 2.73481816e-01 -9.33723032e-01 1.67385972e+00 -2.17092317e-02 -1.22262394e+00 -2.71038413e-01 -1.19531617e-01 1.89085975e-01 -1.60847455e-01 -2.35705987e-01 3.06406558e-01 -1.00582385e+00 -1.14865613e+00 2.76718080e-01 5.10143042e-01 1.09996879e+00 -1.36837757e+00 1.36935651e+00 2.15549126e-01 -1.25399005e+00 -3.69531512e-01 -3.58372591e-02 -4.38290179e-01 -2.51098186e-01 9.62091923e-01 -8.15051854e-01 6.83557212e-01 1.02761793e+00 8.31334174e-01 -3.85276735e-01 1.03221738e+00 4.71887410e-01 9.72831964e-01 -1.78232476e-01 -1.79242000e-01 -1.10390209e-01 2.13324651e-01 5.07392108e-01 1.39255118e+00 4.66206729e-01 5.47744669e-02 -3.82114835e-02 3.49195302e-01 1.31806657e-01 3.01091760e-01 -7.98214614e-01 1.85624644e-01 1.78684786e-01 1.16221237e+00 -8.71789455e-01 -3.99800807e-01 -1.94402516e-01 7.77610302e-01 -1.22686177e-01 1.14137657e-01 -7.59114325e-01 -1.25371242e+00 3.13758790e-01 1.57906666e-01 4.02678065e-02 -3.94501239e-02 -7.74592161e-01 -7.48739362e-01 1.25201061e-01 -1.15507889e+00 3.38882774e-01 -2.49123976e-01 -8.60897243e-01 8.97733808e-01 -4.33808982e-01 -1.44310975e+00 -3.16301137e-01 -4.56048131e-01 -5.20581901e-01 1.14988351e+00 -9.60328698e-01 -8.25761676e-01 -4.49304640e-01 6.31580949e-01 6.31434500e-01 -5.02824783e-01 1.50079179e+00 8.43321621e-01 -5.14590740e-01 6.09002829e-01 -1.71680629e-01 4.17470396e-01 5.42940199e-01 -1.19731355e+00 3.23664099e-01 7.93283165e-01 8.12102389e-03 6.58324361e-01 2.56452113e-01 -4.70964432e-01 -1.20814836e+00 -9.22502160e-01 1.16849506e+00 -2.46178314e-01 -2.94055641e-01 -2.61881024e-01 -4.95453358e-01 1.38455808e-01 2.84379244e-01 4.25943546e-02 9.19444740e-01 5.11082336e-02 4.25038755e-01 -5.77843845e-01 -1.13496339e+00 2.68978715e-01 4.96538669e-01 -3.10926646e-01 -3.20238262e-01 -1.25158224e-02 -9.92419645e-02 -4.72962946e-01 -9.24413204e-01 7.84967065e-01 9.94929969e-01 -1.07090020e+00 8.06423128e-01 -3.22222561e-01 -9.58764479e-02 -4.21497822e-01 2.01727375e-01 -8.01849067e-01 -3.18158388e-01 -9.52521324e-01 -2.70278841e-01 6.61269724e-01 2.81882852e-01 -5.87067127e-01 6.45061672e-01 1.53869856e-02 -2.42010027e-01 -1.41510999e+00 -7.12621272e-01 -4.63031650e-01 -3.08268666e-01 -3.51342887e-01 3.01739961e-01 8.50388587e-01 -3.90833199e-01 4.36673164e-01 -4.99230415e-01 2.26136371e-02 4.28804159e-01 -4.23590168e-02 4.91290838e-01 -1.51045561e+00 -2.25238949e-01 -1.52368546e-01 -7.64263093e-01 -7.96764046e-02 -6.79063439e-01 -6.53086007e-01 -5.02946556e-01 -1.32106447e+00 -1.10901378e-01 -3.95984560e-01 -9.00912166e-01 6.29067302e-01 3.60675268e-02 5.57990789e-01 -2.36238718e-01 -3.50473374e-02 1.50997013e-01 -5.66193871e-02 6.30739033e-01 7.16421232e-02 -4.42755401e-01 4.13766503e-01 -5.21249056e-01 6.65376306e-01 1.09652758e+00 -4.80854154e-01 -5.28108060e-01 -8.42452347e-02 2.35620469e-01 2.50245482e-01 2.51697958e-01 -1.67952168e+00 -8.40607882e-02 6.74868405e-01 1.09933543e+00 -8.45068634e-01 1.24282077e-01 -6.55000567e-01 3.84813488e-01 9.46402848e-01 -5.41892946e-02 5.94161749e-01 2.96133697e-01 1.98606953e-01 -1.72001854e-01 -1.16943708e-02 7.32984960e-01 -1.73939839e-01 -1.77857667e-01 2.72348672e-01 -8.10284078e-01 -1.68953955e-01 1.16507077e+00 -4.42884028e-01 4.49805051e-01 -9.50488001e-02 -1.00176156e+00 -4.92429465e-01 -2.95307368e-01 1.85818031e-01 8.15732479e-01 -1.18464446e+00 -8.68539989e-01 3.49843264e-01 -1.30547083e-03 -1.08003892e-01 2.00136825e-01 9.03687954e-01 -1.16414464e+00 4.50483650e-01 -6.83338225e-01 -6.14968002e-01 -1.49772596e+00 1.26591384e-01 7.48157084e-01 -1.20253757e-01 -9.56991673e-01 7.15754211e-01 -5.58352411e-01 1.57986045e-01 4.97824788e-01 -4.69248742e-01 -4.68519688e-01 8.37244615e-02 5.15955746e-01 6.01829350e-01 7.25032866e-01 -1.64803818e-01 -6.88901544e-01 8.59788656e-01 1.07966512e-01 1.17414102e-01 1.38394260e+00 3.41331065e-01 -8.38652328e-02 5.57949305e-01 1.09341991e+00 -1.52481645e-01 -2.84587294e-01 4.47861522e-01 -2.70431578e-01 9.95235741e-02 7.10676461e-02 -1.03398228e+00 -1.06535006e+00 1.17815733e+00 1.58201659e+00 4.80540134e-02 1.45428538e+00 -9.89323795e-01 9.82682943e-01 5.77440679e-01 1.83549464e-01 -1.00162852e+00 -2.12592155e-01 1.97585151e-01 6.63063765e-01 -8.28683078e-01 4.11418714e-02 9.67279747e-02 -6.24939799e-01 1.44472790e+00 2.99668789e-01 -4.75545913e-01 1.17621446e+00 3.12067300e-01 3.91039759e-01 -3.48661065e-01 -4.28309739e-01 2.50388026e-01 6.36699274e-02 7.62273669e-01 9.29883897e-01 4.09323275e-02 -7.01788068e-01 8.85876060e-01 1.38174534e-01 5.55123031e-01 4.68918949e-01 1.11494529e+00 -1.53480813e-01 -9.27672744e-01 -1.21905677e-01 7.61446774e-01 -1.19085062e+00 -8.34641382e-02 -1.66136950e-01 5.14259815e-01 6.56701207e-01 8.86121631e-01 -2.48467982e-01 -3.30768347e-01 1.92040637e-01 3.00331235e-01 2.84394503e-01 -5.07661879e-01 -1.18572772e+00 1.39096845e-02 8.73012468e-02 -2.80284464e-01 -3.02778959e-01 -4.99593377e-01 -1.08780777e+00 1.75439313e-01 -1.20409220e-01 5.14628217e-02 8.39630961e-01 6.72684908e-01 6.56438529e-01 9.37567294e-01 5.85036099e-01 -5.10724485e-01 -1.92035049e-01 -1.10342634e+00 -7.46262789e-01 3.74650359e-02 5.37039399e-01 -3.52627516e-01 -1.16158463e-03 2.73802906e-01]	[14.224437713623047, 3.28597354888916]
3ae4a2a2-7a58-4e1a-91ff-1fc04c2a8b28	190407094	1904.07094	null	https://arxiv.org/abs/1904.07094v3	https://arxiv.org/pdf/1904.07094v3.pdf	CEDR: Contextualized Embeddings for Document Ranking	Although considerable attention has been given to neural ranking architectures recently, far less attention has been paid to the term representations that are used as input to these models. In this work, we investigate how two pretrained contextualized language models (ELMo and BERT) can be utilized for ad-hoc document ranking. Through experiments on TREC benchmarks, we find that several existing neural ranking architectures can benefit from the additional context provided by contextualized language models. Furthermore, we propose a joint approach that incorporates BERT's classification vector into existing neural models and show that it outperforms state-of-the-art ad-hoc ranking baselines. We call this joint approach CEDR (Contextualized Embeddings for Document Ranking). We also address practical challenges in using these models for ranking, including the maximum input length imposed by BERT and runtime performance impacts of contextualized language models.	['Nazli Goharian', 'Andrew Yates', 'Sean MacAvaney', 'Arman Cohan']	2019-04-15	null	null	null	null	['ad-hoc-information-retrieval']	['natural-language-processing']	[ 2.14282721e-01 -2.39871383e-01 -3.38365346e-01 -6.86611712e-01 -1.28052044e+00 -5.69833457e-01 9.67624545e-01 4.38757986e-01 -9.90255594e-01 4.35004324e-01 6.98557675e-01 -4.30016786e-01 -3.94604474e-01 -5.25361538e-01 -5.94812214e-01 -5.40003292e-02 -3.23300332e-01 6.43620729e-01 2.08789080e-01 -4.70178545e-01 4.90911722e-01 2.33132303e-01 -1.60014606e+00 7.57968605e-01 6.69097662e-01 7.86317170e-01 1.20966002e-01 7.92923927e-01 -1.43688545e-01 7.35516071e-01 -7.21990168e-01 -4.10140127e-01 -1.37148646e-03 1.80356055e-01 -9.06278074e-01 -7.96516240e-01 7.87976325e-01 -7.56040275e-01 -2.79205710e-01 5.81821620e-01 7.01640487e-01 5.35383940e-01 8.32796454e-01 -6.32914484e-01 -1.14405274e+00 9.55499411e-01 -1.28332213e-01 3.16028208e-01 -1.15258172e-02 -5.20314455e-01 1.53674102e+00 -1.20723677e+00 4.44477826e-01 1.23593545e+00 4.22625959e-01 6.70495927e-01 -1.04205048e+00 -3.69606763e-01 5.00384033e-01 1.25415042e-01 -1.14835703e+00 -3.47425640e-01 6.91475034e-01 -1.55655816e-01 1.35974610e+00 1.68312445e-01 1.15735129e-01 1.04972947e+00 -9.71910134e-02 9.58367527e-01 8.48043323e-01 -5.72074056e-01 7.50724673e-02 9.49171335e-02 8.76932442e-01 4.76267248e-01 3.78180742e-01 1.37440756e-01 -4.07576472e-01 -4.06375915e-01 1.65689051e-01 -9.21354219e-02 8.84464309e-02 -1.78530902e-01 -8.12933028e-01 8.35267961e-01 5.68632305e-01 3.63150597e-01 -6.98685646e-03 7.36867368e-01 7.87527680e-01 2.66023099e-01 8.24892402e-01 9.08290923e-01 -6.09049261e-01 3.29510495e-02 -1.01087940e+00 2.67244101e-01 2.98904896e-01 6.65894449e-01 4.87457544e-01 -1.25220299e-01 -6.06121242e-01 1.27601612e+00 3.58332634e-01 2.86744237e-01 6.22652411e-01 -6.93138480e-01 5.29285014e-01 3.97529572e-01 9.70745310e-02 -7.20080733e-01 -3.51705700e-01 -6.48581088e-01 -2.10470185e-01 -4.37160492e-01 -2.68937740e-02 5.79992048e-02 -9.41938400e-01 1.70753181e+00 -4.68596488e-01 6.56783357e-02 2.15989336e-01 6.89787507e-01 9.13765907e-01 6.79627538e-01 3.42397183e-01 3.09230328e-01 1.20893264e+00 -1.00105238e+00 -3.35758269e-01 -3.71447235e-01 9.63002682e-01 -5.81473947e-01 1.24132061e+00 2.15203315e-01 -1.01567209e+00 -4.29678828e-01 -1.14724541e+00 -4.90433842e-01 -8.21999729e-01 3.50385994e-01 8.84155810e-01 5.63878536e-01 -1.28402364e+00 6.33922338e-01 -7.09832489e-01 -3.29897314e-01 -2.12200675e-02 7.13362634e-01 -6.33937195e-02 -1.42279655e-01 -1.57715404e+00 1.15007436e+00 3.24110746e-01 2.87475139e-01 -9.45525527e-01 -3.01570892e-01 -5.88846266e-01 1.74894348e-01 1.18974820e-01 -5.56216121e-01 1.51434362e+00 -4.59311396e-01 -1.27940702e+00 5.72795510e-01 -2.82267302e-01 -4.48379785e-01 -1.74008273e-02 -6.73132300e-01 -4.24494684e-01 4.55065668e-02 -2.17021331e-01 8.04065049e-01 1.93924978e-01 -1.31216681e+00 -3.98529321e-01 -1.47126541e-01 4.44449276e-01 3.49210709e-01 -9.67624545e-01 3.85899067e-01 -6.14450455e-01 -5.53891301e-01 -4.70245183e-01 -9.47159171e-01 -2.79267669e-01 -4.81784940e-01 -1.98667660e-01 -6.24112189e-01 4.76522565e-01 -3.74441594e-01 1.63891315e+00 -1.69889784e+00 -1.16432033e-01 3.85206819e-01 -7.21968412e-02 3.61429274e-01 -7.14142442e-01 5.36807418e-01 1.86893851e-01 5.96189857e-01 2.57380217e-01 -5.13966560e-01 2.49342605e-01 1.60359278e-01 -5.16004145e-01 -9.33521390e-02 6.27430007e-02 1.05450130e+00 -1.02039802e+00 -4.01623428e-01 -1.17038585e-01 7.31895626e-01 -7.41105795e-01 1.26701757e-01 -1.96776465e-01 -3.44180405e-01 -3.50936025e-01 4.74342525e-01 3.27112705e-01 -1.86264038e-01 3.32955033e-01 -1.18402913e-02 1.88065410e-01 8.71480286e-01 -5.36016524e-01 1.56866741e+00 -7.88032472e-01 6.21337533e-01 -4.90654618e-01 -6.27149045e-01 8.45475137e-01 1.42440811e-01 1.34167429e-02 -8.02257121e-01 1.59773957e-02 4.54037070e-01 -1.20678738e-01 7.83979595e-02 1.30536830e+00 2.73664117e-01 -2.20710889e-01 6.27820432e-01 -1.70753673e-01 2.15308264e-01 4.93379384e-01 4.98313636e-01 1.15408111e+00 3.77507880e-02 -2.04878286e-01 -2.86331296e-01 3.89240265e-01 -1.11116961e-01 4.11026254e-02 1.12261248e+00 2.02790752e-01 5.98152995e-01 1.76898196e-01 -3.08444023e-01 -8.30040514e-01 -8.31934452e-01 -1.78459749e-01 1.94504046e+00 -1.17733464e-01 -6.30388319e-01 -3.98742110e-01 -8.59036386e-01 -9.57962424e-02 7.10644662e-01 -7.04988658e-01 -3.60905468e-01 -8.76573920e-01 -7.75343299e-01 7.31805861e-01 1.00710368e+00 -5.19666113e-02 -1.04056942e+00 -4.14564848e-01 2.81492114e-01 8.58459398e-02 -7.90182531e-01 -5.61049342e-01 7.24612594e-01 -1.06798387e+00 -6.21425211e-01 -8.09650481e-01 -8.00128043e-01 7.01373279e-01 3.55263382e-01 1.48610783e+00 2.44701207e-01 1.15006477e-01 5.49069881e-01 -5.46451867e-01 -3.01502109e-01 -1.65878683e-01 5.90380549e-01 1.30068501e-02 -5.74784517e-01 6.37632608e-01 -1.59840509e-01 -7.18580365e-01 2.40194798e-01 -1.18025541e+00 -1.42722145e-01 7.32656181e-01 9.37251151e-01 3.35079730e-01 -2.78000981e-01 7.04702437e-01 -1.13518870e+00 1.33161151e+00 -3.05757016e-01 -3.45579922e-01 5.36425173e-01 -8.71283531e-01 5.60510516e-01 5.70495427e-01 -5.22403479e-01 -8.11798453e-01 -3.83194089e-01 -7.01679885e-02 -7.98672140e-02 4.74132180e-01 1.05936944e+00 2.96394169e-01 2.04661578e-01 7.12280154e-01 -2.60140419e-01 -4.19350803e-01 -6.45406961e-01 6.19446754e-01 8.67637217e-01 2.42404759e-01 -1.15354657e+00 6.76534712e-01 8.94170702e-02 -4.02254641e-01 -3.84894013e-01 -1.15104687e+00 -5.15814900e-01 -3.86696219e-01 7.87556991e-02 5.35212576e-01 -9.43011463e-01 -9.67909247e-02 -1.05488963e-01 -1.28613603e+00 -1.44745097e-01 -4.37019244e-02 4.18089509e-01 -9.39934701e-02 1.41809776e-01 -8.52555215e-01 -7.16323018e-01 -5.85909903e-01 -1.17610896e+00 1.08876264e+00 -1.59906030e-01 -2.96623439e-01 -1.12306201e+00 2.87780732e-01 2.24230707e-01 7.98331976e-01 -3.06663424e-01 1.32260776e+00 -1.04227436e+00 -4.09520864e-01 -4.53349501e-01 -3.78100783e-01 5.14289081e-01 -3.16428274e-01 -1.92812517e-01 -1.12735033e+00 -3.17305565e-01 -9.47006285e-01 -6.43690288e-01 1.45775187e+00 2.68114805e-01 1.29418004e+00 -1.57125011e-01 -1.41189456e-01 1.86340049e-01 1.30039942e+00 1.29117697e-01 4.78755832e-01 5.57766795e-01 6.10082805e-01 5.56369841e-01 5.94820678e-01 -3.81694734e-02 2.85497069e-01 8.37745070e-01 2.05436096e-01 -6.43005595e-03 4.80684787e-02 -3.86627495e-01 6.26018703e-01 1.11384249e+00 -1.36993632e-01 -4.21553731e-01 -8.73564422e-01 6.16324782e-01 -1.85175335e+00 -7.50364363e-01 3.23604047e-01 2.26923466e+00 9.17021215e-01 3.26186627e-01 -2.66811728e-01 -1.48779675e-01 6.91546023e-01 3.59060436e-01 -4.56833333e-01 -9.56479192e-01 -2.99796294e-02 4.54599500e-01 5.11224508e-01 5.50089061e-01 -1.11913192e+00 1.08264077e+00 7.01780272e+00 7.82461047e-01 -8.49761784e-01 2.07384117e-02 5.56848645e-01 -3.07484299e-01 -5.93908906e-01 -4.65424620e-02 -1.02367902e+00 -4.24616644e-03 1.32473505e+00 -1.33708209e-01 3.78317654e-01 1.04656243e+00 -1.60934135e-01 3.50406349e-01 -1.51613271e+00 5.61215997e-01 2.01845184e-01 -1.07296598e+00 5.19021451e-01 1.97475448e-01 7.20736027e-01 3.40914994e-01 4.28539842e-01 9.82972741e-01 6.97319269e-01 -1.14496064e+00 4.36202914e-01 2.17062801e-01 1.00309634e+00 -8.72843444e-01 9.81565118e-01 -1.69628501e-01 -1.10802305e+00 -1.91585496e-01 -7.65767217e-01 -3.40541336e-03 -2.77967036e-01 4.99839514e-01 -8.99574220e-01 2.76037961e-01 3.76224816e-01 4.87033010e-01 -9.36640441e-01 7.94815660e-01 -2.18843833e-01 5.56295395e-01 -7.80869648e-02 -4.97452348e-01 5.49395442e-01 4.01230305e-01 8.01245272e-02 1.44662428e+00 1.72051072e-01 -3.46679956e-01 1.29416898e-01 2.83238679e-01 -5.30421615e-01 1.97734237e-01 -5.64884961e-01 -3.36765021e-01 4.70019996e-01 1.04050207e+00 -3.07965428e-01 -4.43723232e-01 -3.51727366e-01 6.79033279e-01 8.38215530e-01 5.62405169e-01 -6.27976477e-01 -5.61186016e-01 3.86032552e-01 -3.18116657e-02 3.58059928e-02 -2.69252330e-01 -1.75194871e-02 -1.06427193e+00 -8.08569118e-02 -6.90930068e-01 5.29395580e-01 -7.10321665e-01 -1.30692410e+00 8.65532696e-01 1.99610919e-01 -9.51955080e-01 -5.04072368e-01 -9.43068683e-01 -4.77513313e-01 7.54552901e-01 -1.86179435e+00 -1.00207710e+00 7.51630664e-02 1.50448814e-01 3.81287754e-01 -2.79722273e-01 9.86402690e-01 4.50035483e-01 -3.24111283e-01 7.97865093e-01 5.61557531e-01 2.17470869e-01 8.97378147e-01 -1.42366993e+00 4.28798884e-01 5.61895013e-01 3.69422138e-01 1.44475365e+00 3.91779572e-01 -3.10432166e-01 -1.17586422e+00 -1.29814160e+00 1.28994608e+00 -7.83276260e-01 5.81473708e-01 -3.25193942e-01 -6.62395418e-01 6.58831775e-01 2.13245153e-01 -1.79256618e-01 9.51145232e-01 8.13377321e-01 -8.10761213e-01 -1.89720809e-01 -5.44930041e-01 6.56153858e-01 8.96040440e-01 -8.49327505e-01 -8.46429825e-01 1.13336839e-01 9.22326267e-01 9.27895531e-02 -4.56629336e-01 5.42956650e-01 8.98280501e-01 -4.14276987e-01 1.24936593e+00 -9.05908883e-01 7.26866186e-01 -6.62886277e-02 -2.57890493e-01 -1.34282005e+00 -3.16053092e-01 4.54203002e-02 -2.35439822e-01 1.07121682e+00 6.27352059e-01 -3.85001183e-01 6.52283549e-01 5.90937674e-01 -1.69727534e-01 -9.91362631e-01 -6.26782656e-01 -8.92068267e-01 5.96747756e-01 -4.80972767e-01 5.26351035e-01 6.39495254e-01 -1.34734169e-01 5.38973510e-01 -3.78919661e-01 -1.58511758e-01 1.19910911e-01 -1.91222757e-01 4.25136179e-01 -1.29140484e+00 -2.30982050e-01 -5.51315665e-01 2.39244141e-02 -1.37901056e+00 3.48567069e-01 -1.36337614e+00 7.38250390e-02 -1.91955256e+00 4.58469361e-01 -4.99188006e-01 -1.20769358e+00 5.45900345e-01 -2.70326912e-01 4.43405777e-01 6.99623078e-02 1.91123977e-01 -1.10484159e+00 5.04995346e-01 6.13993824e-01 -2.57019758e-01 -1.34605676e-01 -4.93525237e-01 -1.10701621e+00 4.95989263e-01 6.98973477e-01 -5.70866227e-01 -5.90529680e-01 -1.17865670e+00 6.72357559e-01 -2.81935811e-01 1.22722015e-01 -7.79962301e-01 3.30857038e-01 1.62928551e-01 3.08401346e-01 -6.87547207e-01 3.56998980e-01 -6.79312229e-01 -7.18004942e-01 5.43588810e-02 -1.30006504e+00 4.31387186e-01 1.34684175e-01 4.90540326e-01 -3.44374776e-01 -5.08907378e-01 3.68279546e-01 -7.13374168e-02 -5.74744165e-01 1.19629100e-01 -4.39871788e-01 1.81554139e-01 2.17232853e-01 2.04691261e-01 -7.28321195e-01 -3.18580925e-01 -4.12756950e-01 3.73174131e-01 4.55585569e-02 6.12701952e-01 7.18254447e-01 -1.32600129e+00 -6.07005298e-01 -4.52665836e-01 5.66351116e-01 -3.94812584e-01 -1.69292524e-01 2.28969485e-01 -4.49856013e-01 1.01197898e+00 3.77610654e-01 -1.56278655e-01 -1.38148046e+00 3.82325917e-01 1.13378197e-01 -8.96517336e-01 -2.04960138e-01 7.86192119e-01 -4.55127694e-02 -7.68707335e-01 5.80446243e-01 -3.66409779e-01 -4.56844628e-01 8.98739249e-02 5.38715363e-01 2.63975918e-01 3.19766730e-01 -2.72081941e-01 -4.11927491e-01 5.23610055e-01 -7.52233565e-01 -3.52820605e-01 1.31821454e+00 1.87152535e-01 4.28300053e-02 5.49640596e-01 1.54747486e+00 2.01577440e-01 -4.63194430e-01 -4.02375042e-01 6.12493396e-01 -1.54613018e-01 4.37109947e-01 -1.28778684e+00 -5.33291638e-01 1.16009188e+00 5.66702783e-01 -8.08049887e-02 9.50669050e-01 -2.23989636e-01 8.12569082e-01 1.14151669e+00 3.08942378e-01 -1.24540329e+00 1.77718684e-01 9.56974447e-01 7.85397768e-01 -9.64010656e-01 7.33722299e-02 1.82522327e-01 -5.25176108e-01 9.73999202e-01 5.50760627e-01 -2.96322167e-01 3.49110931e-01 -1.00779556e-01 1.13181554e-01 -1.50713399e-01 -1.21424901e+00 -2.99378633e-01 8.27693999e-01 1.78057745e-01 9.74126458e-01 -6.17277138e-02 -5.43876827e-01 6.51669025e-01 -1.40778691e-01 -9.88652110e-02 2.78229386e-01 1.03301084e+00 -5.32602966e-01 -1.49190283e+00 8.88296217e-02 6.76910877e-01 -7.51674771e-01 -8.60842109e-01 -5.63075721e-01 4.77100372e-01 -2.73639053e-01 9.16225135e-01 -7.10025877e-02 -5.25807321e-01 2.17314467e-01 2.90701151e-01 1.97978228e-01 -1.02833581e+00 -8.80767226e-01 -1.34514853e-01 5.34143090e-01 -2.97940403e-01 -2.46877819e-01 -1.07091114e-01 -1.02001405e+00 2.20306575e-01 -5.51355302e-01 6.49278522e-01 9.28474009e-01 6.48806870e-01 4.78423715e-01 6.07850611e-01 3.65671605e-01 -6.93368077e-01 -7.73699522e-01 -1.00819921e+00 -2.88535804e-01 1.81350186e-01 2.65655875e-01 -5.30892491e-01 -5.76373816e-01 -4.99600559e-01]	[11.433893203735352, 7.659843444824219]
8ed142f3-84c5-483d-8777-ac871ff501db	a-real-time-speaker-diarization-system-based	2107.09321	null	https://arxiv.org/abs/2107.09321v1	https://arxiv.org/pdf/2107.09321v1.pdf	A Real-time Speaker Diarization System Based on Spatial Spectrum	In this paper we describe a speaker diarization system that enables localization and identification of all speakers present in a conversation or meeting. We propose a novel systematic approach to tackle several long-standing challenges in speaker diarization tasks: (1) to segment and separate overlapping speech from two speakers; (2) to estimate the number of speakers when participants may enter or leave the conversation at any time; (3) to provide accurate speaker identification on short text-independent utterances; (4) to track down speakers movement during the conversation; (5) to detect speaker change incidence real-time. First, a differential directional microphone array-based approach is exploited to capture the target speakers' voice in far-field adverse environment. Second, an online speaker-location joint clustering approach is proposed to keep track of speaker location. Third, an instant speaker number detector is developed to trigger the mechanism that separates overlapped speech. The results suggest that our system effectively incorporates spatial information and achieves significant gains.	['Zhijie Yan', 'Jinwei Feng', 'Hongbin Suo', 'Xianliang Wang', 'Weilong Huang', 'Siqi Zheng']	2021-07-20	null	null	null	null	['speaker-identification']	['speech']	[ 2.31069610e-01 -1.77297279e-01 1.77737832e-01 -3.41778636e-01 -1.48942757e+00 -6.62987113e-01 3.51837665e-01 1.98105186e-01 -5.91782890e-02 2.42473468e-01 3.61105770e-01 -2.40405485e-01 7.53147751e-02 -1.18172325e-01 -1.39952406e-01 -9.52315450e-01 -3.61729652e-01 5.77867270e-01 2.12352768e-01 6.66110739e-02 3.52481008e-01 7.95431495e-01 -1.60999548e+00 -2.41248067e-02 6.53629303e-01 7.80815303e-01 3.70880008e-01 1.25486553e+00 -1.18276216e-01 3.78382266e-01 -1.09179759e+00 6.51967287e-01 -1.64454356e-01 -3.82917851e-01 -4.81766284e-01 3.00615549e-01 3.21559943e-02 -2.24244997e-01 1.85235724e-01 7.53096640e-01 9.11645353e-01 2.04040214e-01 6.69915259e-01 -1.06610167e+00 3.85206610e-01 7.28501260e-01 -7.91556478e-01 6.21138215e-01 6.32130325e-01 -2.63300508e-01 4.15269405e-01 -9.88850474e-01 -8.22908953e-02 1.29005921e+00 4.23363090e-01 5.18293560e-01 -9.14129257e-01 -8.35470676e-01 2.38903329e-01 -8.93431827e-02 -2.04296088e+00 -1.15158176e+00 8.88609588e-01 -4.20568377e-01 6.23529017e-01 6.71118319e-01 1.76191360e-01 6.56069875e-01 -1.28219858e-01 5.46825111e-01 5.27093112e-01 -7.87213683e-01 3.39370340e-01 2.87854642e-01 2.82640219e-01 1.70664996e-01 -4.28706080e-01 -3.03530008e-01 -7.70140886e-01 -4.93062198e-01 3.19858640e-01 -1.71101734e-01 -2.93323845e-01 3.31041604e-01 -1.04166782e+00 5.23318827e-01 -1.74641013e-01 6.45718813e-01 -4.81117219e-01 -3.72506142e-01 2.51179248e-01 3.59231629e-03 6.03261888e-01 1.10644111e-02 7.05056414e-02 -3.56828541e-01 -1.07265234e+00 1.28951833e-01 9.17682052e-01 9.67873275e-01 5.34706533e-01 7.57010579e-02 -8.24874118e-02 9.73533571e-01 4.74675894e-01 7.11419344e-01 4.62106377e-01 -7.03531682e-01 6.33210838e-01 2.13381454e-01 2.65439332e-01 -7.80889630e-01 -2.82081217e-01 -3.17965686e-01 -6.03076398e-01 -1.07655466e-01 3.06040138e-01 -5.33971071e-01 -4.83113974e-01 1.57643223e+00 6.45677626e-01 3.77026111e-01 3.81471291e-02 6.66675806e-01 4.66996461e-01 8.09087038e-01 -4.19945478e-01 -5.08910835e-01 1.60414088e+00 -5.04913688e-01 -8.74011755e-01 -2.71394163e-01 2.46313438e-01 -9.81568396e-01 4.96533453e-01 3.68521422e-01 -1.04217720e+00 -4.57663804e-01 -8.65243018e-01 5.88777006e-01 -2.00999886e-01 9.08739567e-02 2.30553020e-02 1.05618775e+00 -1.24270427e+00 -3.71187627e-01 -8.93777847e-01 -2.55058497e-01 -2.18291968e-01 5.68690240e-01 9.13022608e-02 2.36415789e-01 -8.88181627e-01 2.56594837e-01 -3.87138635e-01 3.84798855e-01 -8.49677145e-01 -2.34764889e-01 -7.05240965e-01 1.84702262e-01 -7.58657530e-02 -3.94190215e-02 1.52527595e+00 -9.87442374e-01 -1.60830688e+00 5.95092475e-01 -1.17320716e+00 -2.11765304e-01 1.93391412e-01 1.15385771e-01 -9.09200072e-01 1.54940069e-01 2.64117092e-01 3.07833701e-01 9.17225659e-01 -1.20539618e+00 -1.10107327e+00 -6.78662121e-01 -6.55446291e-01 7.28311062e-01 -3.25772226e-01 5.01400948e-01 -6.16863906e-01 -5.05200326e-01 5.01055956e-01 -8.65679562e-01 7.72568882e-02 -6.20788097e-01 -8.33323717e-01 -2.09983498e-01 1.10188019e+00 -8.12015712e-01 1.40111113e+00 -2.27461886e+00 -2.15671822e-01 4.51458663e-01 1.06441721e-01 1.74066126e-01 2.90174544e-01 4.88108486e-01 3.95894460e-02 -3.44369948e-01 5.78257851e-02 -7.86158204e-01 -2.67342597e-01 -3.85791928e-01 -2.40283504e-01 5.23072541e-01 -3.81200194e-01 8.45481455e-02 -4.27554369e-01 -5.04701495e-01 2.23853528e-01 5.17179072e-01 -2.03580379e-01 2.92524666e-01 5.76464415e-01 6.52888298e-01 -3.74556422e-01 7.23876178e-01 8.74084175e-01 3.86070818e-01 2.57131159e-02 2.12242261e-01 -5.35622060e-01 6.49031579e-01 -1.72627938e+00 1.09636545e+00 -5.21971107e-01 9.52645779e-01 1.11142540e+00 -8.88108432e-01 8.58949363e-01 8.77602875e-01 4.67958808e-01 -2.08187789e-01 1.08716786e-01 1.38516828e-01 -1.87732443e-01 -3.05186182e-01 5.24322569e-01 1.03225529e-01 -2.03364432e-01 5.85298657e-01 -5.17165005e-01 3.18018466e-01 -2.35443652e-01 4.29743493e-04 9.57204521e-01 -8.57531726e-01 1.06866591e-01 -3.89528066e-01 8.64083171e-01 -5.44294477e-01 4.52419758e-01 6.10295892e-01 -6.27426744e-01 4.01874453e-01 -3.01486522e-01 2.78257638e-01 -1.45691842e-01 -1.18432367e+00 9.01470426e-03 1.31746423e+00 1.73005968e-01 1.82932377e-01 -1.07677305e+00 -1.27558053e-01 -3.23048621e-01 6.61837041e-01 -1.53207541e-01 2.10489362e-01 -6.93884373e-01 -3.16206723e-01 6.32557333e-01 3.62076432e-01 2.42602676e-01 -6.29403532e-01 -2.99741894e-01 3.57828796e-01 -7.17809141e-01 -7.89700150e-01 -1.22559607e+00 4.59977925e-01 -4.46774930e-01 -4.78325665e-01 -7.35361755e-01 -1.18057430e+00 6.56368256e-01 8.45708549e-01 4.03319210e-01 -4.24972683e-01 -1.19252443e-01 5.50870359e-01 -3.53924260e-02 -6.44156754e-01 -6.08912885e-01 -5.16375676e-02 4.53936130e-01 4.63636011e-01 6.25891864e-01 -5.41976690e-01 -5.77464879e-01 8.23798716e-01 -3.28598320e-01 -6.18158579e-01 5.01956083e-02 8.81076157e-02 1.76840976e-01 5.56937814e-01 9.11095142e-01 -1.87037796e-01 6.61978245e-01 -3.02225024e-01 -4.32726562e-01 1.68427810e-01 -8.60636756e-02 -3.88563544e-01 2.29087308e-01 -5.08577287e-01 -1.24170840e+00 2.19779208e-01 -3.98705482e-01 1.10425271e-01 -5.65735579e-01 7.88561925e-02 -6.32697582e-01 2.57041901e-01 6.49155438e-01 5.06369710e-01 -3.11866645e-02 -5.59845865e-01 1.12985790e-01 1.71910584e+00 6.38431847e-01 -5.31082153e-02 5.80791354e-01 5.87384880e-01 -6.73689127e-01 -1.56928682e+00 -5.68917999e-03 -1.35540700e+00 -6.57518268e-01 -2.29810506e-01 7.13003933e-01 -1.23756969e+00 -8.69464219e-01 7.13522613e-01 -1.11599016e+00 -3.91491689e-02 2.26095214e-01 6.92189634e-01 -1.46786213e-01 3.86059105e-01 -5.10245800e-01 -1.57254553e+00 -4.27273840e-01 -1.07135236e+00 1.33643961e+00 2.31375501e-01 -4.75477517e-01 -1.02140510e+00 2.55278535e-02 4.99526531e-01 2.37686217e-01 -2.41150454e-01 1.03045538e-01 -7.41613328e-01 -2.99462289e-01 -3.52609605e-01 2.36955211e-01 2.00753324e-02 8.10462832e-01 -1.93890974e-01 -1.29726851e+00 -4.88279104e-01 2.43774801e-01 4.92597789e-01 2.30295971e-01 9.14693415e-01 5.92220843e-01 -3.32215458e-01 -8.82215083e-01 1.57506526e-01 6.34550095e-01 7.63148785e-01 3.02359819e-01 -2.71985054e-01 5.20739436e-01 8.24527085e-01 5.28736353e-01 5.05289972e-01 4.79656905e-01 9.45188761e-01 7.29611143e-02 -6.53354451e-02 5.29579408e-02 7.52501190e-02 6.12769127e-01 1.02785122e+00 5.18509626e-01 -6.06940567e-01 -7.49817371e-01 8.23984146e-01 -1.36060381e+00 -1.04106522e+00 -1.40835613e-01 2.42020798e+00 5.49901545e-01 1.85639188e-02 6.38554633e-01 3.51628065e-01 1.55783224e+00 -6.89039305e-02 -3.81460905e-01 -2.95625806e-01 2.47139513e-01 -3.90441358e-01 4.18288946e-01 8.58774602e-01 -1.01914918e+00 5.22887290e-01 6.44031334e+00 7.04012752e-01 -1.34307587e+00 8.80165026e-02 4.12353009e-01 -6.12778254e-02 1.11672446e-01 -4.42926079e-01 -1.19161499e+00 5.56647897e-01 1.13159811e+00 -1.83351021e-02 1.84621423e-01 6.32516086e-01 7.43376017e-01 -2.58890927e-01 -1.08568645e+00 1.15263128e+00 3.68560612e-01 -7.97362506e-01 -5.34874856e-01 3.38617384e-01 2.31953546e-01 -8.98125842e-02 -1.21196456e-01 -1.51696712e-01 7.08941296e-02 -6.34373605e-01 7.04353273e-01 1.61984250e-01 5.79175472e-01 -9.59422052e-01 2.80993700e-01 6.98301435e-01 -1.79296839e+00 -1.71505451e-01 1.44873515e-01 1.90631878e-02 5.54142416e-01 6.76203609e-01 -1.47900546e+00 1.85389712e-01 5.89427412e-01 1.90893433e-03 2.89382748e-02 1.02967072e+00 1.58809528e-01 1.03491950e+00 -5.72343051e-01 1.17209656e-02 -1.14432350e-01 1.83859780e-01 9.45091963e-01 1.30806589e+00 5.71653485e-01 -4.26609963e-02 1.92175463e-01 4.58234459e-01 3.27383310e-01 -2.01693699e-02 -4.20262367e-01 3.87978256e-01 1.14078593e+00 1.01755416e+00 -9.42246556e-01 -5.25825210e-02 2.82198358e-02 1.09416175e+00 -3.83390725e-01 4.76312250e-01 -6.98672473e-01 -7.39389420e-01 7.25976706e-01 2.40164950e-01 4.43240941e-01 -2.61534303e-01 -6.70370534e-02 -6.14816487e-01 1.42460346e-01 -5.74819148e-01 2.59161025e-01 -3.60585570e-01 -7.50166237e-01 5.14232874e-01 -2.76087701e-01 -1.29829907e+00 -6.49033368e-01 1.17328338e-01 -1.11836076e+00 1.24133563e+00 -1.13250339e+00 -6.30668163e-01 -6.58121705e-02 7.36168802e-01 8.49572420e-01 -1.13486648e-01 8.77062917e-01 6.65017188e-01 -7.03679383e-01 9.19924796e-01 4.55254555e-01 2.30201766e-01 6.92216039e-01 -1.06953812e+00 4.82400894e-01 8.60044599e-01 -7.20184073e-02 7.54658043e-01 7.23003387e-01 -4.18147802e-01 -1.21255565e+00 -1.01560748e+00 1.26253104e+00 -4.17260170e-01 9.16067511e-02 -8.65187585e-01 -7.87990272e-01 5.31687200e-01 -4.09407690e-02 -5.42269289e-01 9.48532462e-01 1.40860751e-01 1.57153100e-01 -3.97845179e-01 -1.06972134e+00 3.98718596e-01 3.60378474e-01 -6.21054888e-01 -4.39160764e-01 1.82243273e-01 4.19422090e-01 -2.96649903e-01 -2.29996875e-01 -3.92863125e-01 4.98059064e-01 -8.23348820e-01 8.41061473e-01 4.86372739e-01 -7.17703342e-01 -4.97653991e-01 -1.40467077e-01 -1.12464094e+00 -1.13010541e-01 -1.13870299e+00 1.59376889e-01 1.80529296e+00 5.65948784e-01 -8.60751510e-01 7.53787398e-01 4.56549972e-01 -1.37313470e-01 -7.48744830e-02 -1.29606867e+00 -6.66804790e-01 -5.87399781e-01 -3.67444307e-01 5.82355917e-01 6.31842136e-01 2.07447723e-01 4.60434914e-01 -2.51136541e-01 7.61992931e-01 5.06152511e-01 -8.00748169e-02 6.36143684e-01 -1.13998938e+00 -8.10963437e-02 -3.51713121e-01 -9.54831541e-02 -1.51200557e+00 -7.32531250e-02 -3.13920110e-01 7.23579764e-01 -1.42577708e+00 -2.18305469e-01 -4.66992050e-01 -7.39043728e-02 -1.98388845e-01 -1.44708052e-01 -1.85494900e-01 -5.05204439e-01 2.81656921e-01 -4.24550474e-01 2.57709861e-01 3.06829453e-01 -6.81056604e-02 -7.76285768e-01 9.56157982e-01 -7.45684505e-01 6.64772391e-01 6.47853434e-01 -3.40866089e-01 -5.54335415e-01 -1.33000582e-01 -6.18506253e-01 5.32398760e-01 1.39842525e-01 -1.02666128e+00 5.68290353e-01 1.17466077e-01 4.83923443e-02 -1.00449479e+00 5.53251505e-01 -8.32684994e-01 -2.04727784e-01 3.16790938e-01 -1.90736741e-01 -4.87331487e-02 1.20798774e-01 6.61799014e-01 -2.16821447e-01 -1.16158493e-01 7.13507891e-01 3.11034590e-01 -2.40754068e-01 -1.16442084e-01 -1.19007051e+00 -3.32437456e-01 9.77256835e-01 -3.76479119e-01 1.69233039e-01 -8.08630943e-01 -6.69098496e-01 3.14989507e-01 -6.20983168e-02 4.14170682e-01 3.32410067e-01 -1.04269898e+00 -5.55428207e-01 3.20118189e-01 2.26945821e-02 -4.28221002e-02 4.52815533e-01 7.80811489e-01 -1.76502407e-01 6.06916130e-01 5.34405291e-01 -9.57032084e-01 -1.91885424e+00 2.12598637e-01 3.65927190e-01 1.38946190e-01 -3.32109600e-01 1.28750539e+00 2.71634579e-01 -3.02959263e-01 8.26272011e-01 -2.14325100e-01 -2.88995296e-01 2.71264225e-01 1.05895662e+00 5.22105753e-01 2.97319353e-01 -1.07188880e+00 -7.76964486e-01 3.44026178e-01 -6.58289269e-02 -6.51789904e-01 7.65473425e-01 -1.02292573e+00 1.99567676e-01 6.68500125e-01 1.18403101e+00 4.98754442e-01 -1.24798405e+00 -3.39749753e-01 -3.02035678e-02 -2.15429187e-01 1.58592984e-01 -5.43761075e-01 -5.66504478e-01 9.27592397e-01 9.07206833e-01 4.71327752e-01 1.11372209e+00 8.11214149e-02 6.93380296e-01 5.00777289e-02 1.31918326e-01 -1.20849776e+00 -2.59261668e-01 2.55622327e-01 5.79266906e-01 -1.02570772e+00 -5.10620475e-01 -3.85839343e-01 -4.93561983e-01 8.01599860e-01 2.51334667e-01 6.79774523e-01 8.86477053e-01 5.56743979e-01 4.37350214e-01 -1.06288910e-01 -3.84467274e-01 -1.17932059e-01 1.95122987e-01 8.98782730e-01 3.87112170e-01 1.74140930e-01 4.07090694e-01 4.40025777e-01 -2.87577569e-01 -7.46211469e-01 2.93142140e-01 1.00136137e+00 -9.56494987e-01 -7.71861315e-01 -1.14711177e+00 4.79321703e-02 -4.20957953e-01 7.14279339e-02 -5.49898207e-01 -2.65389644e-02 -2.04618752e-01 1.85268533e+00 2.46346205e-01 -1.14221126e-01 2.60627240e-01 3.34377319e-01 -1.06875144e-01 -6.45607173e-01 -3.73459309e-01 8.24748218e-01 1.01713948e-01 -2.71123145e-02 -2.28746191e-01 -9.37697351e-01 -1.27730250e+00 -1.84189379e-01 -7.24500954e-01 7.60947287e-01 1.06523573e+00 9.56144869e-01 5.12026966e-01 6.79715812e-01 1.20916033e+00 -1.13206100e+00 -3.83429915e-01 -1.08906198e+00 -1.02540445e+00 -3.03259820e-01 8.08730841e-01 -2.73816139e-01 -7.22323537e-01 9.95741263e-02]	[14.812801361083984, 5.87849235534668]
f7d425cf-8517-4c35-a126-1a8392b54f7a	influence-guided-data-augmentation-for-neural	2108.10248	null	https://arxiv.org/abs/2108.10248v1	https://arxiv.org/pdf/2108.10248v1.pdf	Influence-guided Data Augmentation for Neural Tensor Completion	How can we predict missing values in multi-dimensional data (or tensors) more accurately? The task of tensor completion is crucial in many applications such as personalized recommendation, image and video restoration, and link prediction in social networks. Many tensor factorization and neural network-based tensor completion algorithms have been developed to predict missing entries in partially observed tensors. However, they can produce inaccurate estimations as real-world tensors are very sparse, and these methods tend to overfit on the small amount of data. Here, we overcome these shortcomings by presenting a data augmentation technique for tensors. In this paper, we propose DAIN, a general data augmentation framework that enhances the prediction accuracy of neural tensor completion methods. Specifically, DAIN first trains a neural model and finds tensor cell importances with influence functions. After that, DAIN aggregates the cell importance to calculate the importance of each entity (i.e., an index of a dimension). Finally, DAIN augments the tensor by weighted sampling of entity importances and a value predictor. Extensive experimental results show that DAIN outperforms all data augmentation baselines in terms of enhancing imputation accuracy of neural tensor completion on four diverse real-world tensors. Ablation studies of DAIN substantiate the effectiveness of each component of DAIN. Furthermore, we show that DAIN scales near linearly to large datasets.	['Srijan Kumar', 'Ryan A. Rossi', 'Sungchul Kim', 'Sejoon Oh']	2021-08-23	null	null	null	null	['video-restoration']	['computer-vision']	[-1.37972012e-01 -1.89730361e-01 -4.02845412e-01 -2.99180835e-01 -2.88372815e-01 -3.46762151e-01 1.73168018e-01 -1.38451010e-01 -7.72444680e-02 7.75863290e-01 9.03223634e-01 -2.05918267e-01 -4.96691346e-01 -6.93829417e-01 -8.48904431e-01 -5.68159223e-01 -2.23998845e-01 5.50117671e-01 -3.96118492e-01 -1.98823124e-01 -7.31959380e-03 1.82037845e-01 -1.07751083e+00 5.70885301e-01 8.29939246e-01 1.12141252e+00 -3.25921237e-01 2.51600116e-01 -2.55515218e-01 1.17803979e+00 -2.08026111e-01 -6.96505964e-01 2.77967095e-01 3.17018330e-01 -9.71959651e-01 1.59270450e-01 5.04751921e-01 -7.64959395e-01 -6.05322540e-01 6.93457067e-01 6.33651763e-02 2.01787800e-02 4.61493611e-01 -1.57899153e+00 -8.84370923e-01 1.11176419e+00 -5.88344753e-01 4.21490567e-03 3.38729136e-02 -1.11731343e-01 1.34690487e+00 -1.40155959e+00 5.22771358e-01 1.09021175e+00 9.26027596e-01 2.09814951e-01 -1.43109131e+00 -5.93160450e-01 1.63178161e-01 1.47456422e-01 -9.47302163e-01 -2.03892365e-01 9.28624690e-01 -6.17045879e-01 6.12137377e-01 3.02398860e-01 6.78043306e-01 1.14917600e+00 -3.22960943e-01 1.18274581e+00 7.68890858e-01 3.03440243e-01 -1.43554151e-01 -5.90254426e-01 2.55460262e-01 5.03513873e-01 4.66857612e-01 -2.57212788e-01 -7.72594094e-01 -4.28291678e-01 8.84466290e-01 5.88879406e-01 -9.89871752e-03 -3.27479422e-01 -2.08761883e+00 4.46118772e-01 6.14316106e-01 1.44888014e-01 -8.85285020e-01 4.12440479e-01 5.01449764e-01 3.92585456e-01 8.70265603e-01 4.56593692e-01 -7.07888246e-01 -2.51594692e-01 -5.67048728e-01 4.06808108e-01 6.12083137e-01 8.27700138e-01 6.03645444e-01 2.73878962e-01 -4.58072692e-01 1.06917727e+00 1.38741070e-02 3.06866795e-01 1.54517218e-01 -1.20356929e+00 9.18137193e-01 9.71774995e-01 5.87977655e-02 -1.12282300e+00 -3.31073403e-01 -5.74140131e-01 -1.36123514e+00 -5.42501211e-01 6.04512751e-01 -2.74071902e-01 -6.81687832e-01 1.55844104e+00 4.90064591e-01 3.83350700e-01 -1.87171116e-01 1.07777715e+00 6.99241221e-01 4.60228801e-01 -1.63163140e-01 1.20860912e-01 1.26456499e+00 -8.59811366e-01 -8.28033268e-01 1.46809012e-01 8.75962853e-01 -7.30873525e-01 8.74502420e-01 4.92536873e-01 -9.30449009e-01 -1.99144155e-01 -4.64645565e-01 -3.89496803e-01 3.06896791e-02 2.75362492e-01 1.53472507e+00 1.37742132e-01 -8.51936936e-01 6.84785068e-01 -8.58673275e-01 1.97543025e-01 5.20406187e-01 4.39500898e-01 -6.01606250e-01 -5.82733154e-01 -9.67658758e-01 2.25363076e-01 2.84816679e-02 4.90316570e-01 -7.22875178e-01 -1.20935082e+00 -5.97344279e-01 9.66250449e-02 3.89774710e-01 -1.00223351e+00 9.11492109e-01 -5.09623110e-01 -7.88592279e-01 7.78107494e-02 -2.42297485e-01 -3.71436357e-01 1.39309347e-01 -3.51429254e-01 -1.94210798e-01 -2.27621675e-01 2.89654970e-01 4.82023090e-01 6.88849211e-01 -1.03131354e+00 -3.99858773e-01 -4.15343106e-01 3.42978001e-01 -4.39736918e-02 -9.17069316e-01 -2.80621529e-01 -4.94063079e-01 -1.04361618e+00 6.04630888e-01 -8.26679766e-01 -3.41968238e-01 4.37930003e-02 -7.15370834e-01 -3.11247319e-01 5.83106935e-01 -9.17859793e-01 1.13580167e+00 -2.01562428e+00 5.17730057e-01 2.98962444e-01 8.85306120e-01 -3.14096719e-01 -5.11978865e-01 4.25502568e-01 -2.66575456e-01 1.33229017e-01 -9.30289030e-02 -5.76002479e-01 -6.54577911e-02 4.97654468e-01 -5.29760480e-01 8.75059664e-02 1.62732661e-01 9.51631308e-01 -9.76731539e-01 -1.80099040e-01 -2.58119673e-01 6.84296727e-01 -9.69321668e-01 -3.26256305e-02 -1.99112728e-01 5.26583970e-01 -5.55804133e-01 1.06623197e+00 6.52326703e-01 -5.34868002e-01 1.60743937e-01 -8.04506481e-01 1.26435801e-01 3.34624708e-01 -9.99275267e-01 1.68663669e+00 -2.39497244e-01 3.62794459e-01 -1.39001295e-01 -8.84446621e-01 6.27114534e-01 2.92482048e-01 1.18546891e+00 -3.02365333e-01 -8.25337097e-02 2.16126800e-01 1.40990376e-01 -4.18275803e-01 8.58381748e-01 2.65321285e-01 2.91921794e-01 7.53804028e-01 4.72629769e-03 4.47169811e-01 4.43503946e-01 6.70626283e-01 1.23140514e+00 -8.63861069e-02 -5.86616158e-01 2.16645405e-01 1.43139720e-01 -7.98437297e-02 8.44000816e-01 2.45484054e-01 3.26800704e-01 5.47634661e-01 9.67584074e-01 -9.06806707e-01 -1.42665005e+00 -6.66167617e-01 1.34847924e-01 1.19246924e+00 -4.06460762e-01 -6.50878787e-01 -5.07418096e-01 -6.49310589e-01 3.79911840e-01 2.62882590e-01 -7.97681272e-01 1.24116577e-01 -5.56641519e-01 -1.10049999e+00 3.43559563e-01 6.56376064e-01 1.57495260e-01 -4.74548161e-01 7.33325064e-01 1.43370241e-01 -8.27548623e-01 -1.42040491e+00 -6.39255524e-01 -3.79646599e-01 -1.38023496e+00 -1.03293812e+00 -5.97977698e-01 -3.96992296e-01 1.05986953e+00 6.63339615e-01 1.15808845e+00 4.18639123e-01 4.11270261e-01 2.47267365e-01 -3.48293543e-01 3.49019691e-02 4.23406288e-02 2.63785243e-01 4.62675303e-01 5.75930774e-01 2.56578743e-01 -9.26636755e-01 -6.52990282e-01 4.82800066e-01 -9.57848310e-01 2.01070786e-01 7.14414358e-01 9.22206581e-01 5.48390567e-01 -1.64848357e-01 3.10781300e-01 -8.46892297e-01 8.64190340e-01 -7.57858813e-01 -2.30008885e-01 5.16660400e-02 -6.29606247e-01 3.11521679e-01 4.66154933e-01 -5.70779383e-01 -5.92860162e-01 -1.36135221e-01 2.07460061e-01 -7.69281983e-01 5.60181558e-01 1.07382059e+00 1.59331352e-01 3.58208157e-02 3.79179358e-01 5.70151359e-02 1.42457724e-01 -9.51795638e-01 2.32326657e-01 1.59388170e-01 2.43420064e-01 -9.29368913e-01 9.92787421e-01 5.14267266e-01 1.84917837e-01 -4.68934000e-01 -1.02962458e+00 -2.80280292e-01 -5.85005641e-01 -1.17422186e-01 2.55658597e-01 -1.28528523e+00 -9.41452205e-01 4.64685410e-01 -1.19895363e+00 1.08709987e-02 -4.01274681e-01 8.29035997e-01 9.66250971e-02 4.28796589e-01 -8.95777166e-01 -4.47937965e-01 -2.23283902e-01 -9.48511064e-01 9.28353906e-01 -4.30433303e-01 8.95303935e-02 -8.80458891e-01 -1.65963694e-01 1.00128925e+00 3.59038979e-01 1.75315678e-01 9.02439296e-01 -3.34732801e-01 -1.11274183e+00 -2.71569788e-01 -4.86141056e-01 4.53873575e-01 -2.56781392e-02 -2.89162695e-02 -6.78646863e-01 -9.64910537e-02 -4.85834509e-01 -2.47858658e-01 1.00554013e+00 3.03233296e-01 1.56688654e+00 -7.82837570e-01 -3.40033881e-02 7.77524769e-01 8.54322672e-01 -5.99179745e-01 5.04785478e-01 5.69081604e-02 1.42511988e+00 5.27772784e-01 3.34360808e-01 6.20157540e-01 9.68957961e-01 4.76669699e-01 6.92831278e-01 -1.02585055e-01 -3.25475112e-02 -2.55553991e-01 2.58864433e-01 1.52683258e+00 -7.82556713e-01 2.64191478e-01 -9.14787114e-01 7.43743658e-01 -2.03108430e+00 -7.71635830e-01 -6.26562834e-01 2.02186275e+00 9.24889207e-01 -8.48644450e-02 2.19553575e-01 1.52748451e-01 3.55515093e-01 7.20439032e-02 -6.27531290e-01 1.45127982e-01 -3.11656654e-01 -2.66007274e-01 5.69248021e-01 2.48703450e-01 -7.86995947e-01 6.41475618e-01 5.86687183e+00 4.67968315e-01 -7.29984224e-01 3.53449583e-01 5.15063226e-01 -3.25840503e-01 -7.97366381e-01 3.00817732e-02 -4.14967656e-01 3.49424869e-01 5.33420503e-01 1.09359652e-01 8.69065046e-01 6.51914358e-01 2.46572390e-01 4.09398228e-01 -1.07143474e+00 8.65841806e-01 -1.52367756e-01 -1.55290079e+00 4.37136382e-01 5.04812956e-01 1.06195199e+00 3.42246532e-01 1.44971594e-01 3.20985883e-01 4.95979339e-01 -7.84108222e-01 3.31807405e-01 8.32100749e-01 5.42430878e-01 -5.23454428e-01 7.62782216e-01 7.31253922e-02 -9.03918326e-01 -1.93338096e-01 -4.96616304e-01 -3.13937247e-01 1.14822805e-01 1.31562352e+00 -9.31360781e-01 5.05311430e-01 6.52197838e-01 1.10387206e+00 -5.13166904e-01 1.00411344e+00 -6.81287795e-02 8.24005127e-01 -3.65405440e-01 2.32451230e-01 2.22465232e-01 -4.08528596e-01 4.60974842e-01 5.18450975e-01 3.18485498e-01 -9.94647965e-02 1.19620509e-01 7.64732659e-01 -7.14364469e-01 1.87202897e-02 -4.46602315e-01 -2.91258335e-01 3.63239050e-01 1.35412467e+00 -1.22667275e-01 -2.70702481e-01 -5.38286448e-01 6.30198717e-01 4.55076337e-01 6.96201146e-01 -5.76561570e-01 1.61037624e-01 1.09620452e+00 1.65649101e-01 4.23116796e-02 -5.12086332e-01 -6.28018737e-01 -1.65217769e+00 4.31444108e-01 -7.90383995e-01 2.11986691e-01 -9.10647035e-01 -1.59648967e+00 4.41691846e-01 -1.60121918e-01 -1.44905841e+00 -1.36237413e-01 -5.73015869e-01 -1.20517008e-01 6.61731362e-01 -1.29679811e+00 -1.52212536e+00 -3.49979043e-01 7.30898619e-01 4.32110541e-02 -2.96924472e-01 4.89143461e-01 7.60649741e-01 -8.02876055e-01 4.36793000e-01 3.29759151e-01 6.12229943e-01 4.54398572e-01 -1.14767444e+00 5.55249572e-01 8.38766158e-01 1.34153664e-01 8.36600125e-01 3.60396773e-01 -7.74496675e-01 -1.87999320e+00 -1.27531421e+00 9.50612605e-01 -6.46890640e-01 1.10049152e+00 -3.10670108e-01 -1.00188386e+00 8.93882573e-01 -2.77430922e-01 4.28134739e-01 7.42729366e-01 9.34506118e-01 -7.18957484e-01 -4.70344633e-01 -7.34967172e-01 6.67178214e-01 1.23250556e+00 -6.00468636e-01 -1.45799918e-02 7.62368619e-01 1.03025270e+00 -2.80444592e-01 -1.57510686e+00 4.30692047e-01 7.10636616e-01 -7.10046709e-01 1.25303054e+00 -1.04978132e+00 8.75236869e-01 -3.30738634e-01 -2.75029004e-01 -1.26271212e+00 -5.22254825e-01 -4.26721007e-01 -7.34445989e-01 1.10884249e+00 4.85461712e-01 -4.34022516e-01 1.00913775e+00 9.29145932e-01 -1.08863480e-01 -8.43069136e-01 -7.64047027e-01 -4.39366609e-01 -2.98016757e-01 -6.70376122e-01 1.08634126e+00 1.48659301e+00 -2.46271074e-01 3.74505699e-01 -9.21151638e-01 4.00798209e-02 9.38264966e-01 -6.06587082e-02 9.60080862e-01 -1.36078155e+00 -8.49189535e-02 -6.52629733e-02 -1.78667903e-01 -9.42960680e-01 -9.20771882e-02 -9.76996541e-01 -7.55557001e-01 -1.59957051e+00 3.33139420e-01 -6.92301691e-01 -3.73103887e-01 8.32008362e-01 -9.14892405e-02 4.24578071e-01 1.82434395e-01 7.39907324e-01 -4.71335441e-01 6.90610647e-01 1.70418727e+00 -4.61775899e-01 3.90822738e-02 -8.72253105e-02 -8.65397036e-01 5.45743167e-01 5.67491293e-01 -4.25672799e-01 -3.41650814e-01 -1.06361318e+00 8.73477399e-01 1.01057917e-01 4.75927025e-01 -6.43667996e-01 2.63392806e-01 -1.71636820e-01 4.31633890e-01 -8.12239647e-01 4.25908357e-01 -8.80473971e-01 2.37929791e-01 4.95096222e-02 -2.75869787e-01 2.20650956e-01 -3.29820514e-01 5.30356228e-01 -3.00967008e-01 2.60678500e-01 -1.81988925e-01 1.29008099e-01 -3.29957098e-01 8.66348445e-01 1.41072348e-01 -1.52100667e-01 3.06700468e-01 -9.48687717e-02 -4.24108058e-01 -3.30262423e-01 -5.92710376e-01 3.93669188e-01 7.04460889e-02 5.76183140e-01 7.61550248e-01 -1.83703113e+00 -9.83354211e-01 1.98750943e-01 1.43016115e-01 2.26050094e-01 4.60449159e-01 1.42646909e+00 -1.75441787e-01 1.19662546e-01 -5.75533397e-02 -5.39964139e-01 -8.37597489e-01 5.11000156e-01 -8.43290165e-02 -5.04616261e-01 -2.71422029e-01 6.57605231e-01 5.28933816e-02 -7.60898948e-01 2.39826158e-01 -8.47261310e-01 -1.53203741e-01 1.50956303e-01 4.91047919e-01 4.41693157e-01 1.01282112e-01 -5.41761339e-01 1.86676648e-03 2.17161134e-01 -3.17277670e-01 2.78368920e-01 1.80532753e+00 3.42325009e-02 -7.79776871e-01 2.66789496e-01 1.05281281e+00 -1.19221970e-01 -1.12802172e+00 -7.03672290e-01 -2.11924553e-01 -6.44988179e-01 1.63726553e-01 -7.07477570e-01 -1.62904716e+00 6.09088182e-01 -8.91511589e-02 9.74739864e-02 1.01811671e+00 -2.54865974e-01 1.09178162e+00 6.97857261e-01 1.58817157e-01 -7.50165343e-01 2.00855002e-01 6.83059871e-01 1.12260890e+00 -1.08162963e+00 2.23619461e-01 -4.19451743e-01 -6.76914275e-01 8.57398689e-01 4.94336218e-01 1.29454091e-01 7.25144506e-01 -7.14956895e-02 -3.40946883e-01 -3.15433979e-01 -1.08566058e+00 4.56367061e-02 5.11759162e-01 3.89216036e-01 4.66883183e-01 2.06712231e-01 -2.59921923e-02 4.25733835e-01 -2.68141001e-01 2.61617333e-01 6.15217268e-01 4.36865866e-01 1.75067455e-01 -1.09186304e+00 -6.64757490e-01 9.98259246e-01 -5.04104435e-01 -4.44209099e-01 -2.88484454e-01 2.22540185e-01 -3.09954118e-02 5.64224839e-01 -5.66100068e-02 -8.35569978e-01 2.74560660e-01 -1.70357272e-01 6.24545291e-02 -1.46742105e-01 -5.85392594e-01 -3.35811116e-02 3.31089586e-01 -6.90379977e-01 -4.72744256e-01 -7.64800251e-01 -7.90999830e-01 -9.09922183e-01 -2.25141062e-03 3.81502360e-02 7.62771070e-01 8.06647062e-01 6.82876408e-01 5.62033653e-01 6.50070608e-01 -6.65130973e-01 -3.69483650e-01 -1.12584925e+00 -5.45083284e-01 6.84325039e-01 3.55962217e-01 -6.99516892e-01 -4.40976731e-02 -7.04864040e-02]	[7.167637348175049, 4.6819658279418945]
59520f5d-a4af-4a00-a507-fa88a1fce0af	tcam-temporal-class-activation-maps-for	2208.14542	null	https://arxiv.org/abs/2208.14542v2	https://arxiv.org/pdf/2208.14542v2.pdf	TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos	Weakly supervised video object localization (WSVOL) allows locating object in videos using only global video tags such as object class. State-of-art methods rely on multiple independent stages, where initial spatio-temporal proposals are generated using visual and motion cues, then prominent objects are identified and refined. Localization is done by solving an optimization problem over one or more videos, and video tags are typically used for video clustering. This requires a model per-video or per-class making for costly inference. Moreover, localized regions are not necessary discriminant because of unsupervised motion methods like optical flow, or because video tags are discarded from optimization. In this paper, we leverage the successful class activation mapping (CAM) methods, designed for WSOL based on still images. A new Temporal CAM (TCAM) method is introduced to train a discriminant deep learning (DL) model to exploit spatio-temporal information in videos, using an aggregation mechanism, called CAM-Temporal Max Pooling (CAM-TMP), over consecutive CAMs. In particular, activations of regions of interest (ROIs) are collected from CAMs produced by a pretrained CNN classifier to build pixel-wise pseudo-labels for training the DL model. In addition, a global unsupervised size constraint, and local constraint such as CRF are used to yield more accurate CAMs. Inference over single independent frames allows parallel processing of a clip of frames, and real-time localization. Extensive experiments on two challenging YouTube-Objects datasets for unconstrained videos, indicate that CAM methods (trained on independent frames) can yield decent localization accuracy. Our proposed TCAM method achieves a new state-of-art in WSVOL accuracy, and visual results suggest that it can be adapted for subsequent tasks like visual object tracking and detection. Code is publicly available.	['Eric Granger', 'Luke McCaffrey', 'Ismail Ben Ayed', 'Soufiane Belharbi']	2022-08-30	null	null	null	null	['visual-object-tracking']	['computer-vision']	[-9.55423992e-03 -3.58954757e-01 -5.75994134e-01 -2.87042469e-01 -8.91659200e-01 -6.07063413e-01 4.43773627e-01 -9.20272619e-02 -6.25463665e-01 5.74057937e-01 -1.43914744e-01 1.69383839e-01 1.78623885e-01 -4.40725267e-01 -1.00767446e+00 -8.34723473e-01 -3.11022699e-01 -4.07813899e-02 7.08365262e-01 3.96190375e-01 1.67776421e-01 5.85970640e-01 -1.40675700e+00 5.04911125e-01 4.75367248e-01 1.42353356e+00 5.09071112e-01 5.30124128e-01 -5.99534139e-02 1.13937366e+00 -4.63931024e-01 -8.08511768e-03 4.70909685e-01 -3.72365415e-01 -7.00506568e-01 3.28179687e-01 6.41019344e-01 -5.34541726e-01 -3.38535398e-01 1.01046741e+00 7.58681893e-02 4.94310379e-01 5.64762592e-01 -1.36921704e+00 -4.38130647e-01 3.60040903e-01 -5.36303520e-01 3.21722537e-01 2.22151950e-01 1.97029859e-01 8.27215970e-01 -1.19982517e+00 6.60952210e-01 1.09158874e+00 6.88777328e-01 5.53228378e-01 -1.17982340e+00 -5.87739170e-01 4.02171046e-01 2.97973931e-01 -1.70488513e+00 -5.45344591e-01 7.06401706e-01 -5.81266463e-01 7.34565616e-01 1.23966940e-01 7.21653283e-01 9.25056696e-01 1.29243180e-01 1.02932310e+00 8.13612163e-01 -2.01061308e-01 3.83540630e-01 1.76183341e-04 -1.88814178e-01 1.06297708e+00 -3.16357389e-02 -8.17118511e-02 -6.98586524e-01 -3.75398397e-02 1.01206267e+00 3.38854164e-01 -3.75128388e-01 -4.66493666e-01 -1.34319794e+00 6.90173507e-01 5.42524695e-01 2.59307027e-01 -3.44822496e-01 2.71893948e-01 2.35296786e-01 -5.51765151e-02 5.17424703e-01 1.89320564e-01 -5.01395881e-01 -2.30917218e-03 -1.47911644e+00 -9.20557380e-02 4.13577110e-01 9.77660537e-01 9.96540606e-01 5.58897629e-02 -3.62514675e-01 6.06494069e-01 3.66417557e-01 3.02631021e-01 5.50996900e-01 -1.31408024e+00 2.38853738e-01 4.73374605e-01 9.55226272e-02 -1.10153723e+00 -2.94905126e-01 -1.06719799e-01 -6.33332551e-01 2.10938051e-01 4.43328083e-01 1.55299395e-01 -1.04481542e+00 1.68519938e+00 3.01301122e-01 6.88624024e-01 -2.41592273e-01 1.18805587e+00 6.45699382e-01 7.46108234e-01 2.85418093e-01 -3.46421301e-01 1.19387400e+00 -1.11957574e+00 -4.85307664e-01 -9.77599397e-02 5.62652528e-01 -5.28281569e-01 7.93342292e-01 2.26660252e-01 -1.11567855e+00 -8.37919891e-01 -7.07639754e-01 -5.83049245e-02 -3.29828650e-01 5.37456036e-01 4.08577740e-01 2.42780909e-01 -1.11692286e+00 4.66104388e-01 -1.20077074e+00 -4.55346376e-01 7.97593713e-01 4.92297560e-01 -5.30002356e-01 -5.33441342e-02 -7.48169303e-01 4.32525158e-01 4.45547014e-01 3.26901436e-01 -1.32024801e+00 -4.87834513e-01 -9.38961446e-01 2.15269048e-02 4.58562374e-01 -4.41260815e-01 7.03498960e-01 -1.32426190e+00 -1.42119718e+00 7.80398428e-01 -3.94421160e-01 -5.72066367e-01 4.43856359e-01 -2.42662817e-01 -1.33435294e-01 6.80072904e-01 3.45199168e-01 1.11212242e+00 1.28280056e+00 -1.15217721e+00 -7.67831802e-01 -3.57931224e-03 1.41126767e-01 -1.19183138e-01 -4.55214262e-01 1.82474017e-01 -1.03661048e+00 -8.20229292e-01 9.93236527e-02 -9.79950786e-01 -2.10566536e-01 2.88301229e-01 -2.10668549e-01 -3.57838988e-01 1.07577002e+00 -7.09513426e-01 1.28035498e+00 -2.14545727e+00 7.88000450e-02 3.90712433e-02 2.35258684e-01 2.69496202e-01 -2.57282376e-01 -1.76988661e-01 2.34658778e-01 7.52140656e-02 -2.46124581e-01 -5.31725168e-01 -3.30888838e-01 2.06362739e-01 -2.07108691e-01 7.38093019e-01 4.83946681e-01 9.74376202e-01 -8.11837792e-01 -9.39041078e-01 4.34990436e-01 3.41900289e-01 -6.95774078e-01 3.28003645e-01 -3.34104538e-01 5.56039929e-01 -4.00288582e-01 1.07440448e+00 5.61995149e-01 -5.15249908e-01 1.41293034e-02 -5.09745657e-01 -2.48083025e-01 -1.58322811e-01 -9.57578838e-01 1.84527230e+00 -1.45415947e-01 7.34978378e-01 3.07040401e-02 -1.25336719e+00 6.21238947e-01 1.57315418e-01 8.61572683e-01 -3.55995834e-01 1.38582364e-01 5.86271510e-02 -3.66573662e-01 -7.01124668e-01 3.27162176e-01 4.34453100e-01 1.76943824e-01 1.03479542e-01 4.63681012e-01 3.22022796e-01 4.31647629e-01 1.38569713e-01 1.09328103e+00 5.98344982e-01 1.22101493e-01 -2.20519230e-01 6.44863248e-01 5.88982962e-02 9.77564454e-01 8.36622894e-01 -4.02082950e-01 9.22463000e-01 2.71333843e-01 -6.32068157e-01 -9.34262097e-01 -8.85145247e-01 -1.34842470e-01 1.09595907e+00 4.32416022e-01 -4.91847217e-01 -7.28219390e-01 -1.06390703e+00 -1.77185521e-01 1.56094478e-02 -5.85441053e-01 1.72709882e-01 -8.74550700e-01 -5.05447984e-01 3.58530283e-01 7.80289948e-01 4.62042958e-01 -9.97247934e-01 -6.67108476e-01 3.31020117e-01 -1.89366609e-01 -1.57028234e+00 -5.83880007e-01 7.39551559e-02 -8.37718427e-01 -1.13073528e+00 -9.08754408e-01 -8.84686410e-01 8.47085476e-01 3.86169851e-01 6.77032292e-01 1.52457833e-01 -2.22995594e-01 4.23856467e-01 -3.71539712e-01 3.90476257e-01 7.67473802e-02 -1.44665405e-01 2.83442140e-01 4.04473454e-01 3.08794677e-01 -2.66796619e-01 -7.82456577e-01 5.85621893e-01 -8.18684995e-01 -9.06651169e-02 6.28158331e-01 8.57327580e-01 7.74082124e-01 -1.00209221e-01 2.56118089e-01 -3.72597724e-01 -1.90514013e-01 -4.50488895e-01 -7.63623059e-01 3.06575298e-01 -1.24552399e-01 -1.73792526e-01 6.22269690e-01 -7.69633949e-01 -8.11062455e-01 4.59998965e-01 1.37686446e-01 -1.21904886e+00 -2.55652070e-01 3.23229998e-01 -2.47573275e-02 -3.90151471e-01 3.77484500e-01 3.30437630e-01 -7.25419894e-02 -2.64322877e-01 2.94978887e-01 4.44498420e-01 5.31182170e-01 -4.94021714e-01 6.18106067e-01 6.60378873e-01 -1.26611024e-01 -7.54848897e-01 -8.12460303e-01 -6.37871742e-01 -9.44195449e-01 -4.61127460e-01 1.30695105e+00 -1.11784863e+00 -6.74722672e-01 3.14513773e-01 -1.22657073e+00 -4.79099423e-01 -2.23821718e-02 8.59277308e-01 -4.56673980e-01 4.14831012e-01 -6.97978377e-01 -6.69577301e-01 6.05366305e-02 -1.18963397e+00 1.21299410e+00 3.29673201e-01 -1.03693061e-01 -9.34134543e-01 -3.47628951e-01 3.28054070e-01 2.19125241e-01 9.61973220e-02 3.26763481e-01 -4.32654917e-01 -1.12960410e+00 -2.01946363e-01 -3.62259328e-01 5.32531679e-01 3.47944945e-02 1.55711383e-01 -9.28250551e-01 -3.68075758e-01 -2.22636521e-01 -2.73433506e-01 1.11419129e+00 7.54298806e-01 1.52819335e+00 -3.74067515e-01 -6.39179289e-01 8.26255560e-01 1.24737513e+00 2.17981264e-01 3.47538471e-01 2.69048393e-01 1.05840325e+00 2.67311215e-01 8.43077838e-01 3.67433786e-01 2.38617226e-01 8.43763292e-01 2.97943205e-01 -2.12500721e-01 -2.26750076e-01 -9.41715315e-02 7.70774484e-01 5.37408352e-01 -3.69513571e-01 -2.09038138e-01 -5.90685785e-01 4.53191400e-01 -2.02396607e+00 -1.03919339e+00 1.41944200e-01 2.17712379e+00 5.60829878e-01 -8.05617403e-03 1.54209003e-01 -3.27181458e-01 8.34807992e-01 2.11857781e-01 -4.12356675e-01 4.42008287e-01 -1.24806732e-01 1.16189243e-02 6.51529074e-01 2.96472043e-01 -1.55774629e+00 1.17748976e+00 5.41281843e+00 1.01850200e+00 -1.30012560e+00 3.48158300e-01 7.75938749e-01 -1.95246309e-01 3.05942178e-01 9.94819477e-02 -8.73444974e-01 7.09403694e-01 4.73762393e-01 4.54498589e-01 2.47965083e-01 1.02343631e+00 3.67702305e-01 -2.85400718e-01 -1.08485508e+00 1.13471484e+00 2.88179398e-01 -1.56019962e+00 -2.65157372e-02 -3.57746854e-02 8.18643570e-01 7.15112239e-02 -5.54185137e-02 2.23649010e-01 -1.51071966e-01 -7.03602910e-01 9.69011009e-01 6.38986528e-01 7.00089514e-01 -4.35659617e-01 6.43269122e-01 8.47529173e-02 -1.62203348e+00 -3.43313158e-01 -5.14334023e-01 3.06911111e-01 1.78238556e-01 3.65425795e-01 -5.36896408e-01 2.78793365e-01 1.06527317e+00 1.18524492e+00 -5.77751458e-01 1.06375599e+00 -1.00916743e-01 6.91499412e-01 -4.23129112e-01 2.16701314e-01 3.58786225e-01 -1.43279389e-01 4.94196594e-01 1.31792212e+00 4.25955564e-01 2.18464881e-01 6.50781155e-01 1.02736723e+00 -4.78354134e-02 -1.32292405e-01 -3.01119298e-01 -1.12369023e-02 4.22580898e-01 1.60216808e+00 -1.16104972e+00 -5.34789622e-01 -5.39601088e-01 1.07947814e+00 2.77724534e-01 7.02520847e-01 -1.07840991e+00 3.98409814e-02 5.43299258e-01 1.18976340e-01 5.54810822e-01 -4.93332922e-01 1.08907469e-01 -1.43130100e+00 1.21848872e-02 -4.56041783e-01 4.23049331e-01 -6.08442962e-01 -1.04021990e+00 5.63357115e-01 -2.55166013e-02 -1.72995758e+00 -8.46751854e-02 -6.48620486e-01 -5.38546205e-01 2.98033059e-01 -1.43478000e+00 -1.23926067e+00 -4.20386672e-01 8.08886647e-01 8.13817441e-01 -1.96798310e-01 3.83994490e-01 5.31268001e-01 -7.98437357e-01 4.79700536e-01 -2.09306806e-01 4.64325070e-01 7.06522584e-01 -9.21796381e-01 -2.49294892e-01 1.16872776e+00 3.92679751e-01 5.83083868e-01 1.63328230e-01 -5.79276085e-01 -1.36241329e+00 -1.50018859e+00 5.26871860e-01 -4.64981079e-01 5.19512475e-01 -3.90362233e-01 -9.38407183e-01 5.85270047e-01 -7.83605501e-02 7.86598682e-01 3.31195801e-01 -4.37210768e-01 3.32950614e-02 -1.53063282e-01 -8.80771041e-01 2.80584782e-01 1.04647398e+00 -5.39957881e-01 -2.12245643e-01 3.46756697e-01 6.67362392e-01 -3.12840343e-01 -7.08547473e-01 4.65738982e-01 4.37878221e-01 -8.02811503e-01 1.02001309e+00 -3.30345094e-01 2.04566196e-01 -7.89374173e-01 -1.93819717e-01 -6.95768893e-01 -3.35333556e-01 -6.13836884e-01 -4.82653111e-01 1.20589375e+00 1.20214134e-01 -1.82638749e-01 8.21101248e-01 5.96050858e-01 -2.69158572e-01 -6.91841841e-01 -1.00974941e+00 -8.68817627e-01 -6.22596085e-01 -5.17286122e-01 9.13674757e-02 1.09276223e+00 -2.59748310e-01 -1.76562220e-01 -4.40402567e-01 3.60935479e-01 6.64629757e-01 2.34724339e-02 6.76112652e-01 -9.27916110e-01 -2.04335108e-01 -3.21605563e-01 -7.16175020e-01 -1.40150952e+00 4.51178342e-01 -7.52525091e-01 2.13106722e-01 -1.17484510e+00 1.41632661e-01 -5.12742817e-01 -5.64958990e-01 7.78233707e-01 -9.26182568e-02 7.98023760e-01 2.99773782e-01 5.82193613e-01 -1.17235684e+00 5.57668090e-01 9.42793190e-01 -3.03367883e-01 -2.83956677e-01 -1.07014738e-01 1.18396841e-01 8.88311267e-01 5.27489483e-01 -5.55697322e-01 -6.16406910e-02 -2.83720702e-01 -3.21939856e-01 1.12813510e-01 7.54713356e-01 -1.19423878e+00 4.12045777e-01 -2.26069495e-01 7.84267128e-01 -5.93314290e-01 5.52895665e-01 -8.27749491e-01 -2.17314988e-01 2.88175493e-01 -1.58003226e-01 -1.68022007e-01 -1.87461302e-02 6.17761374e-01 -4.67993170e-01 -5.34562580e-02 7.64998138e-01 -1.60631258e-02 -1.14250708e+00 6.45342290e-01 -3.56514215e-01 -2.36284465e-01 1.25808990e+00 -3.54515225e-01 -2.20211111e-02 -8.83479938e-02 -7.86689222e-01 1.38203904e-01 4.16504323e-01 4.04323995e-01 7.72340596e-01 -1.38801098e+00 -4.17015702e-01 2.09615275e-01 1.08746709e-02 4.90553007e-02 2.15140313e-01 1.27299726e+00 -4.78811085e-01 3.27719867e-01 -4.31889147e-02 -1.14416909e+00 -1.25888848e+00 6.97511852e-01 2.16439098e-01 2.98869818e-01 -6.65179670e-01 9.25368309e-01 4.56511587e-01 1.86291233e-01 2.98325658e-01 -6.04002297e-01 -1.54854938e-01 1.08168386e-01 5.36952376e-01 1.69997782e-01 -2.35094294e-01 -8.61433327e-01 -5.21600366e-01 7.91191757e-01 6.72244653e-02 1.04836963e-01 1.17538607e+00 -3.34013045e-01 -9.23097506e-02 2.18715951e-01 1.35028899e+00 -9.96911898e-02 -1.79684770e+00 -2.17295274e-01 -1.08987093e-01 -6.61010206e-01 1.02050290e-01 -2.85893142e-01 -1.39997709e+00 7.24880636e-01 6.46512032e-01 2.40447372e-02 1.12232375e+00 2.00704113e-01 7.60568559e-01 2.29940534e-01 4.07513499e-01 -1.01696014e+00 3.62170041e-01 3.12024802e-01 5.21010220e-01 -1.44452345e+00 -2.16857806e-01 -2.20538348e-01 -5.38694441e-01 1.27701163e+00 8.19319546e-01 -2.09367245e-01 5.04273295e-01 2.11107433e-01 -5.32646812e-02 9.90032777e-02 -4.61574584e-01 -2.77173936e-01 5.02559960e-01 4.29070741e-01 2.15487137e-01 -2.90451765e-01 -2.48791352e-02 4.82194006e-01 5.50809145e-01 3.73605639e-03 1.48344576e-01 8.74894381e-01 -4.27716017e-01 -7.81445205e-01 -3.91152054e-01 2.73526102e-01 -5.11251569e-01 -5.39669171e-02 7.48469168e-03 6.93120599e-01 4.54101652e-01 8.50561321e-01 2.88565367e-01 -3.94082099e-01 -3.41337979e-01 -1.40664458e-01 4.52741772e-01 -4.06116515e-01 -1.97269797e-01 4.26125050e-01 -3.62799495e-01 -1.00257146e+00 -9.11453843e-01 -6.00749075e-01 -1.40107810e+00 1.05299152e-01 -4.54433858e-01 1.04882747e-01 3.65796477e-01 9.73370492e-01 3.94245416e-01 2.59643584e-01 6.34135604e-01 -1.39246750e+00 1.24056846e-01 -7.93917596e-01 -4.01248485e-01 4.09010053e-01 4.68073338e-01 -8.76648724e-01 -3.38014603e-01 6.10330403e-01]	[9.112367630004883, -0.020607739686965942]
01621f73-aafe-47e2-a10d-4d4d902b92e7	generalized-classification-of-satellite-image	2203.09175	null	https://arxiv.org/abs/2203.09175v2	https://arxiv.org/pdf/2203.09175v2.pdf	Generalized Classification of Satellite Image Time Series with Thermal Positional Encoding	Large-scale crop type classification is a task at the core of remote sensing efforts with applications of both economic and ecological importance. Current state-of-the-art deep learning methods are based on self-attention and use satellite image time series (SITS) to discriminate crop types based on their unique growth patterns. However, existing methods generalize poorly to regions not seen during training mainly due to not being robust to temporal shifts of the growing season caused by variations in climate. To this end, we propose Thermal Positional Encoding (TPE) for attention-based crop classifiers. Unlike previous positional encoding based on calendar time (e.g. day-of-year), TPE is based on thermal time, which is obtained by accumulating daily average temperatures over the growing season. Since crop growth is directly related to thermal time, but not calendar time, TPE addresses the temporal shifts between different regions to improve generalization. We propose multiple TPE strategies, including learnable methods, to further improve results compared to the common fixed positional encodings. We demonstrate our approach on a crop classification task across four different European regions, where we obtain state-of-the-art generalization results.	['Ira Assent', 'Charlotte Pelletier', 'Joachim Nyborg']	2022-03-17	null	null	null	null	['crop-classification']	['miscellaneous']	[ 3.11149985e-01 -6.69511616e-01 -1.79219931e-01 -4.17498440e-01 -1.78157523e-01 -8.45648527e-01 3.83623779e-01 4.47812140e-01 -2.71372557e-01 6.58465266e-01 1.01968022e-02 -6.12288117e-01 -3.11351389e-01 -1.27500188e+00 -1.03844833e+00 -8.08309495e-01 -3.95232916e-01 -1.56786174e-01 -1.20302670e-01 -6.00228250e-01 -1.25040570e-02 5.03841102e-01 -1.66954160e+00 1.10663772e-01 1.17830110e+00 9.21995521e-01 6.36202872e-01 5.18069088e-01 -5.95718063e-02 -5.17846830e-02 -4.81744468e-01 3.23046595e-01 2.70314425e-01 -4.23187196e-01 -4.72919434e-01 -1.09337062e-01 2.91877896e-01 -1.14412725e-01 -7.48413280e-02 1.02562726e+00 2.36045823e-01 1.98467135e-01 6.01212204e-01 -1.24903548e+00 -1.15593660e+00 5.44277966e-01 -6.41497374e-01 2.29198456e-01 -2.57304937e-01 -1.00016184e-02 9.20354664e-01 -3.78572941e-01 1.65407658e-01 8.68942499e-01 1.03253889e+00 1.14696272e-01 -1.24855494e+00 -6.75041437e-01 7.70709395e-01 3.55998009e-01 -1.19400430e+00 1.06084958e-01 6.87544584e-01 -5.63596964e-01 9.97851431e-01 3.08643103e-01 7.19751179e-01 8.90404820e-01 4.07204330e-01 7.05836713e-01 1.16832137e+00 -2.24633887e-01 4.28106546e-01 -4.40382063e-01 1.21745534e-01 1.00924537e-01 6.30387524e-03 1.52143538e-01 -1.67916209e-01 1.13336153e-01 6.88687146e-01 2.34812826e-01 -4.87580717e-01 -1.62489831e-01 -1.10974693e+00 8.43078375e-01 1.29122949e+00 4.67632830e-01 -8.48256469e-01 1.60623506e-01 3.33162129e-01 2.48671025e-01 9.53341484e-01 5.51019371e-01 -1.11250067e+00 1.89741254e-01 -1.09247446e+00 2.65234053e-01 3.29462767e-01 6.90233767e-01 8.86212587e-01 2.05108359e-01 -1.68713972e-01 8.57663572e-01 5.66482544e-04 8.56653512e-01 5.70367455e-01 -4.82609481e-01 4.59445007e-02 6.17494345e-01 1.23998344e-01 -9.51516926e-01 -6.62799060e-01 -6.47768915e-01 -1.17431593e+00 9.13351849e-02 2.98410803e-01 -1.90346628e-01 -1.28809929e+00 2.09896708e+00 -1.03511095e-01 3.09860498e-01 1.56428173e-01 8.18543315e-01 3.42086524e-01 8.51699591e-01 4.01608825e-01 -1.45769164e-01 1.41063964e+00 -5.80890238e-01 -5.97815871e-01 -5.22676051e-01 7.09526956e-01 -2.35671401e-01 9.16326046e-01 -1.49778100e-02 -2.24492595e-01 -5.90249598e-01 -1.02482295e+00 4.29311931e-01 -1.24325418e+00 3.22464645e-01 8.68640423e-01 3.68584067e-01 -1.02635920e+00 8.58798742e-01 -9.70512152e-01 -7.32952595e-01 2.78931528e-01 -1.06779203e-01 -1.89744323e-01 1.11958034e-01 -1.52337480e+00 9.18844342e-01 4.54488367e-01 6.94393396e-01 -5.28003037e-01 -9.76741552e-01 -8.29906046e-01 3.24518293e-01 8.62225145e-02 -2.92488158e-01 9.88685429e-01 -1.25767970e+00 -1.24810779e+00 6.15444541e-01 -2.80316263e-01 -6.78091884e-01 -3.17663960e-02 -2.37659797e-01 -3.99780512e-01 -2.29536861e-01 1.91102192e-01 7.20931232e-01 6.48504972e-01 -1.09535182e+00 -6.27401888e-01 -5.78519940e-01 1.21899769e-01 2.30903223e-01 -4.66148376e-01 -1.76150769e-01 2.57051557e-01 -7.74122477e-01 3.12549144e-01 -1.21059108e+00 -2.80915201e-01 2.27463641e-03 9.37707573e-02 -8.04124102e-02 1.07696939e+00 -8.64132166e-01 1.15039849e+00 -2.06560373e+00 2.39928871e-01 -2.10934341e-01 -3.61914396e-01 3.85996133e-01 -3.04815203e-01 2.89631337e-01 -2.27436632e-01 2.84543216e-01 -8.19553137e-01 2.64719516e-01 -5.69518059e-02 5.52992344e-01 -4.79403496e-01 3.05108041e-01 5.66755533e-01 9.23217654e-01 -1.00950015e+00 2.95104980e-01 2.90463477e-01 3.58758479e-01 3.87086459e-02 3.71754356e-02 -4.51962948e-01 2.75649518e-01 -2.37789601e-01 7.26657927e-01 1.03373265e+00 -3.04140393e-02 -5.02295606e-02 -6.66291565e-02 -5.09456873e-01 2.17442145e-03 -5.76523960e-01 1.63231850e+00 -6.50413394e-01 7.41652608e-01 -7.79466778e-02 -1.24051261e+00 1.02106202e+00 2.85190165e-01 4.40475643e-01 -6.23394728e-01 -3.17126274e-01 2.25990310e-01 2.71390863e-02 -9.47693512e-02 6.78698182e-01 2.66601562e-01 -2.58512571e-02 2.57777393e-01 -1.52923465e-01 -2.63702460e-02 6.99291676e-02 -3.84727150e-01 6.80783451e-01 5.89855731e-01 3.14621240e-01 -6.40954435e-01 1.28123656e-01 1.14809573e-01 7.29215741e-01 6.51216149e-01 -3.96592587e-01 6.85733557e-01 3.86740804e-01 -7.40793824e-01 -1.03326809e+00 -6.97419941e-01 -4.87880200e-01 1.43037593e+00 -1.72285475e-02 -9.79687832e-03 -5.00602901e-01 -5.11989415e-01 1.67081639e-01 8.49646747e-01 -1.21451521e+00 -1.11411229e-01 -3.66578996e-01 -1.42488563e+00 4.01496589e-01 1.04978645e+00 8.40235889e-01 -1.24551022e+00 -1.13336349e+00 5.78219235e-01 -2.08319783e-01 -7.33424246e-01 -1.22616217e-01 7.77060986e-01 -7.83745766e-01 -6.99787915e-01 -1.08355749e+00 -3.11032772e-01 2.57803679e-01 4.96886432e-01 1.16662633e+00 -2.20834523e-01 -1.20213903e-01 4.42800075e-02 -7.38463283e-01 -7.92736590e-01 2.38025431e-02 5.98860145e-01 -2.03419581e-01 -7.58437365e-02 5.17430544e-01 -5.94058931e-01 -6.92723870e-01 1.80932760e-01 -9.58065271e-01 -9.88306180e-02 5.54291904e-01 9.45600033e-01 4.25624013e-01 9.48480293e-02 5.99513590e-01 -5.22631049e-01 1.73154071e-01 -9.99208808e-01 -6.50281131e-01 5.30390799e-01 -5.62445402e-01 8.26049130e-03 4.26778853e-01 -5.49472511e-01 -9.72619176e-01 1.23061053e-01 2.12327346e-01 -1.61454216e-01 -4.32923257e-01 1.01525486e+00 6.88407794e-02 1.88860953e-01 5.16575396e-01 4.77476567e-01 -3.10491800e-01 -2.73804039e-01 1.43475994e-01 6.15596890e-01 4.77444559e-01 -3.72494280e-01 3.28077644e-01 1.23882808e-01 -7.31260478e-02 -9.76458788e-01 -8.23786080e-01 -3.96815658e-01 -8.42605352e-01 -1.90795198e-01 8.25613439e-01 -1.02283287e+00 -2.66916066e-01 9.74752247e-01 -1.00936830e+00 -7.25191832e-01 9.62642729e-02 4.49396789e-01 -2.87324101e-01 -1.60195425e-01 -2.59839773e-01 -7.66510546e-01 -4.86681521e-01 -8.59747827e-01 1.16026938e+00 3.49481940e-01 1.47424608e-01 -1.18986118e+00 -1.69080310e-02 -5.26668191e-01 9.28201616e-01 6.60782516e-01 9.77087438e-01 -5.49038872e-02 -1.85374454e-01 1.10555198e-02 -4.46375370e-01 2.70847797e-01 5.65601289e-01 1.25374332e-01 -1.11864972e+00 -3.30056518e-01 -2.79022723e-01 -7.82905053e-03 1.17526615e+00 9.31862831e-01 1.20060945e+00 -3.99246886e-02 -3.42717499e-01 8.91124547e-01 1.61701238e+00 4.27434027e-01 5.93762577e-01 6.95587635e-01 6.41008139e-01 5.59427559e-01 6.23282433e-01 3.93791020e-01 4.23289955e-01 4.25872713e-01 7.95785129e-01 -3.74269634e-01 1.86639622e-01 6.80304766e-02 2.27106586e-01 2.26238444e-01 -1.34527668e-01 -3.08547407e-01 -1.15198386e+00 1.01754534e+00 -2.04897666e+00 -1.02361691e+00 -1.60524383e-01 2.15952253e+00 5.80274999e-01 -3.06532085e-01 -2.73252398e-01 1.09335646e-01 5.95155120e-01 5.97939610e-01 -1.02883577e+00 -3.22591186e-01 -5.60994744e-01 1.89929813e-01 1.09255981e+00 8.38453397e-02 -1.49751508e+00 1.09020150e+00 5.95202112e+00 3.39326888e-01 -1.64780843e+00 -1.04252473e-01 5.54298341e-01 3.99954200e-01 -4.37952727e-02 -5.79000786e-02 -5.02984166e-01 3.64618480e-01 9.01502013e-01 -4.02431376e-02 3.79992425e-01 7.64630973e-01 6.59572333e-02 -1.16780736e-01 -7.77601779e-01 2.37205118e-01 -2.73745477e-01 -8.16010416e-01 -2.66289353e-01 -1.03727192e-01 7.90897250e-01 2.71366268e-01 1.97005585e-01 5.12634754e-01 3.51144463e-01 -7.83379078e-01 5.53383172e-01 3.28683406e-01 6.38958991e-01 -4.73773599e-01 7.57357419e-01 1.56847075e-01 -1.67762601e+00 -3.18918914e-01 -4.77310568e-01 -1.81591675e-01 -2.91922480e-01 5.66415846e-01 -3.71782780e-01 9.75100219e-01 1.12390113e+00 1.28508008e+00 -6.76815629e-01 6.90084755e-01 -1.76761657e-01 8.41702878e-01 -5.43512821e-01 1.60220534e-01 6.25703871e-01 -1.91892028e-01 2.94469148e-01 1.00535047e+00 7.32727885e-01 8.72534961e-02 8.38907361e-02 8.57978225e-01 2.16572791e-01 -1.12861253e-01 -6.44825399e-01 4.53753434e-02 4.65974480e-01 9.70498860e-01 -6.90736771e-01 -6.17705025e-02 -2.54551321e-01 1.07639217e+00 1.35653019e-01 6.02039576e-01 -6.60251379e-01 -4.33395207e-01 9.02350903e-01 -3.50461334e-01 6.04079366e-01 -3.65491420e-01 -2.76756614e-01 -1.04112554e+00 1.31818399e-01 -6.29220665e-01 1.98357329e-01 -9.50602531e-01 -1.16261065e+00 6.36087418e-01 1.03565328e-01 -1.17709124e+00 -7.36631677e-02 -6.49906039e-01 -7.47560561e-01 1.10822582e+00 -1.93450880e+00 -1.48084855e+00 -6.39288127e-01 1.83118597e-01 5.92025101e-01 1.27945036e-01 1.33858967e+00 -1.70878887e-01 -4.96335030e-01 2.93764561e-01 5.38448691e-01 -5.56114577e-02 6.90284669e-01 -1.41718996e+00 8.39033127e-01 1.00310779e+00 -1.77088976e-01 2.82739192e-01 5.29339135e-01 -4.09086853e-01 -9.72127855e-01 -1.51757109e+00 9.00622249e-01 -3.28192860e-02 7.12745965e-01 -2.15519190e-01 -1.38613188e+00 6.16765559e-01 1.47384390e-01 1.53385997e-01 4.82321560e-01 3.91318083e-01 -5.97385228e-01 -4.71319824e-01 -9.39040303e-01 2.92832077e-01 8.46682727e-01 -5.18606663e-01 -2.70511508e-01 3.48991424e-01 6.95062757e-01 -2.05447823e-01 -8.36767375e-01 7.15844274e-01 6.70883715e-01 -5.54397702e-01 6.02935672e-01 -5.21640778e-01 3.94554943e-01 -3.09781820e-01 -4.05213624e-01 -2.16245532e+00 -7.83855140e-01 -6.38920665e-02 3.70887935e-01 1.05574095e+00 3.79014313e-01 -7.24583328e-01 4.18381006e-01 2.69049257e-01 -2.54846692e-01 -4.18391258e-01 -6.97358847e-01 -9.21642423e-01 5.30627549e-01 -1.03251234e-01 9.35349524e-01 1.24149740e+00 -3.13696504e-01 -1.96647421e-01 -1.77416787e-01 7.23065376e-01 1.99582264e-01 5.47721028e-01 2.49678716e-01 -1.34657741e+00 1.47226289e-01 -6.96876824e-01 -3.63691211e-01 -5.92391431e-01 2.53708988e-01 -5.48743725e-01 3.64080399e-01 -1.43401742e+00 -3.57190445e-02 -5.17428577e-01 -7.27692723e-01 1.01571476e+00 -5.83207905e-01 3.43534932e-03 1.09037101e-01 -5.70483692e-02 1.86141670e-01 6.19554520e-01 7.41769254e-01 -4.02890295e-01 -3.45904261e-01 -6.26327321e-02 -3.39408100e-01 3.15805823e-01 1.14490736e+00 -3.42542320e-01 -1.91417664e-01 -8.47973764e-01 9.34131220e-02 -1.38074577e-01 3.26100379e-01 -1.19571233e+00 -1.95104808e-01 -4.89302188e-01 3.99846762e-01 -7.51077354e-01 -1.74097382e-02 -8.00652921e-01 1.18362613e-01 5.21779835e-01 -3.12169701e-01 2.99348980e-01 7.08822668e-01 4.96411562e-01 -1.95020974e-01 9.13795307e-02 4.93826360e-01 -7.79369622e-02 -1.03061950e+00 4.03789371e-01 -5.07114589e-01 -5.95497370e-01 8.76415133e-01 1.19054459e-01 -4.11273032e-01 -9.27007645e-02 -4.64959025e-01 4.75763649e-01 3.31381470e-01 8.23525548e-01 7.13637844e-02 -1.18970525e+00 -1.06974947e+00 3.12034935e-01 4.92892206e-01 -1.34665802e-01 4.45257634e-01 5.40587544e-01 -3.69901270e-01 4.43646938e-01 -5.68490922e-01 -7.99762666e-01 -1.05121243e+00 6.40655220e-01 5.30410707e-01 -1.63124666e-01 -2.44767323e-01 7.16342568e-01 1.70444518e-01 -5.18713892e-01 -3.57808545e-02 -7.71394849e-01 -3.16792905e-01 4.10241991e-01 3.46076369e-01 -1.15363501e-01 3.79854977e-01 -4.94086474e-01 -3.95297080e-01 6.87839389e-01 1.49660334e-01 2.66105175e-01 1.55578351e+00 -1.46340178e-02 5.99543890e-03 7.70985603e-01 9.91262138e-01 -8.76811445e-01 -1.47686434e+00 -3.31459373e-01 1.66155342e-02 -2.60042667e-01 4.83547121e-01 -1.04892159e+00 -1.29127288e+00 8.63537729e-01 1.17313766e+00 4.25944448e-01 1.58192122e+00 -5.92503726e-01 5.34743607e-01 3.97399038e-01 2.46038899e-01 -9.33874309e-01 -7.19751537e-01 7.54718661e-01 1.03396153e+00 -1.57072294e+00 -2.24622309e-01 3.45736668e-02 -4.10666853e-01 1.05550504e+00 4.47242558e-01 -1.04017220e-02 8.71819735e-01 1.44715413e-01 2.09805652e-01 2.81737119e-01 -6.93823934e-01 -5.99427581e-01 1.78473309e-01 7.33531654e-01 6.57913387e-01 5.60678422e-01 -1.96569040e-01 2.32063234e-01 1.36088058e-02 8.28638859e-03 1.72531158e-01 1.14530039e+00 -1.90881565e-01 -8.39698195e-01 -4.07726854e-01 4.41364050e-01 -1.76393524e-01 -2.17939869e-01 -2.29504973e-01 6.15251541e-01 1.71677962e-01 8.33273172e-01 4.08131450e-01 -3.78313988e-01 2.61233807e-01 1.67670444e-01 2.24191293e-01 -3.77870709e-01 -7.09565222e-01 -3.44177842e-01 -4.49285358e-01 -3.46451670e-01 -6.30311251e-01 -8.91289413e-01 -6.59682095e-01 -2.53779978e-01 -4.17627841e-01 -1.60768896e-01 9.97583449e-01 7.15379000e-01 5.11059225e-01 6.83090866e-01 7.87609577e-01 -1.20786881e+00 -3.74911815e-01 -1.37323439e+00 -6.63182080e-01 3.31158042e-01 6.95843756e-01 -6.55838251e-01 -1.52360663e-01 3.30860447e-03]	[9.432027816772461, -1.5780121088027954]
643a3aab-67f1-4724-8a83-eab7f044de5e	task-formulation-for-extracting-social	2301.11386	null	https://arxiv.org/abs/2301.11386v1	https://arxiv.org/pdf/2301.11386v1.pdf	Task formulation for Extracting Social Determinants of Health from Clinical Narratives	Objective: The 2022 n2c2 NLP Challenge posed identification of social determinants of health (SDOH) in clinical narratives. We present three systems that we developed for the Challenge and discuss the distinctive task formulation used in each of the three systems. Materials and Methods: The first system identifies target pieces of information independently using machine learning classifiers. The second system uses a large language model (LLM) to extract complete structured outputs per document. The third system extracts candidate phrases using machine learning and identifies target relations with hand-crafted rules. Results: The three systems achieved F1 scores of 0.884, 0.831, and 0.663 in the Subtask A of the Challenge, which are ranked third, seventh, and eighth among the 15 participating teams. The review of the extraction results from our systems reveals characteristics of each approach and those of the SODH extraction task. Discussion: Phrases and relations annotated in the task is unique and diverse, not conforming to the conventional event extraction task. These annotations are difficult to model with limited training data. The system that extracts information independently, ignoring the annotated relations, achieves the highest F1 score. Meanwhile, LLM with its versatile capability achieves the high F1 score, while respecting the annotated relations. The rule-based system tackling relation extraction obtains the low F1 score, while it is the most explainable approach. Conclusion: The F1 scores of the three systems vary in this challenge setting, but each approach has advantages and disadvantages in a practical application. The selection of the approach depends not only on the F1 score but also on the requirements in the application.	['Daniel S. Zisook', 'Elly W. Yang', 'Paul Wang', 'Son Doan', 'Ian M. Finn', 'Manabu Torii']	2023-01-26	null	null	null	null	['event-extraction']	['natural-language-processing']	[ 4.62974489e-01 8.38908195e-01 -4.70533490e-01 5.86324325e-03 -1.22683811e+00 -6.40954614e-01 5.40587127e-01 7.72535622e-01 -5.65374136e-01 9.18658614e-01 4.61777568e-01 -5.74742317e-01 -6.85147047e-01 -3.24066252e-01 -3.32183063e-01 -5.47941267e-01 5.10520360e-04 6.15781486e-01 1.64455608e-01 -1.57639667e-01 1.58682942e-01 1.72690600e-01 -9.49306190e-01 8.17541301e-01 5.89295328e-01 8.08096886e-01 -2.24916991e-02 8.32349181e-01 -2.11496070e-01 1.26324904e+00 -5.70565641e-01 -6.25704825e-01 -2.09069505e-01 -6.36774063e-01 -1.24271297e+00 -4.83026296e-01 -1.79132357e-01 2.96125501e-01 8.79675820e-02 5.29854059e-01 6.14940703e-01 -4.95507181e-01 6.82894349e-01 -8.78432095e-01 -4.01349068e-02 9.61681008e-01 -1.60833016e-01 3.75289828e-01 8.62708449e-01 -2.57503688e-01 1.16788661e+00 -7.70414889e-01 1.18887305e+00 8.76314700e-01 9.87919509e-01 6.23484552e-01 -1.24967134e+00 -5.94709754e-01 -1.41026676e-01 -3.04250028e-02 -1.35696471e+00 -4.15898532e-01 2.09472999e-01 -6.61949873e-01 1.31931388e+00 5.00466406e-01 5.12131453e-01 1.06591082e+00 5.97305357e-01 5.02524674e-01 1.05330002e+00 -4.57690626e-01 9.60139483e-02 4.17515874e-01 3.97391438e-01 6.08468950e-01 4.19694215e-01 -1.70339420e-01 -8.39910328e-01 -7.64958262e-01 2.61815578e-01 -3.37909997e-01 -3.37415785e-01 4.51345772e-01 -1.34517598e+00 6.32075131e-01 -1.67702720e-01 5.64673245e-01 -6.01015031e-01 -3.17981482e-01 5.58809221e-01 1.51013229e-02 3.74025494e-01 7.49802411e-01 -8.04134727e-01 -2.57033616e-01 -9.37704802e-01 2.67802417e-01 1.23725855e+00 9.60029066e-01 -2.40566880e-02 -6.43996418e-01 -3.99061978e-01 6.16303742e-01 1.12497769e-01 2.43736859e-02 3.47437024e-01 -6.85778677e-01 5.86111128e-01 6.34925306e-01 -3.37806530e-02 -1.08899498e+00 -9.52860355e-01 -3.20897162e-01 -6.60656512e-01 -3.88042837e-01 5.54510295e-01 -4.46469843e-01 -6.15692139e-01 1.50736690e+00 8.07050020e-02 -4.14182216e-01 3.94294024e-01 3.28915328e-01 1.30430400e+00 3.51959467e-01 5.73013306e-01 -5.67355692e-01 1.89081573e+00 -6.25448108e-01 -1.32558465e+00 -2.27833942e-01 8.35334778e-01 -1.01682281e+00 3.67644846e-01 5.64675868e-01 -1.10072112e+00 -3.52774486e-02 -7.67213106e-01 9.11036730e-02 -3.54892969e-01 1.12125441e-01 3.97238940e-01 5.48054159e-01 -8.97609591e-01 3.68376225e-01 -7.53587782e-01 -5.04917979e-01 2.25126222e-01 6.04876041e-01 -4.38997328e-01 3.28249037e-01 -1.37705994e+00 1.28934145e+00 5.79460502e-01 -1.25300914e-01 -3.46584797e-01 -8.87468874e-01 -7.65800357e-01 2.56045461e-02 4.26833868e-01 -5.78596175e-01 1.17357266e+00 -3.15213740e-01 -1.00847530e+00 1.00131440e+00 -3.28642845e-01 -4.85973746e-01 4.71596420e-01 -2.36326575e-01 -4.80012894e-01 3.37947458e-01 3.19949329e-01 3.21402103e-01 -5.89312427e-02 -8.35861504e-01 -7.99730539e-01 1.94212720e-02 -1.54031277e-01 3.54896039e-02 -1.10489756e-01 6.16296649e-01 -1.66112468e-01 -4.86987084e-01 -1.05224743e-01 -7.62533724e-01 -5.15972018e-01 -6.52164817e-01 -6.58195317e-01 -4.08816308e-01 2.20968261e-01 -8.16448510e-01 1.81910908e+00 -1.86672103e+00 -1.37391838e-03 1.35693789e-01 4.69590604e-01 1.05631746e-01 3.33584785e-01 9.18510497e-01 -2.84063131e-01 5.62769234e-01 -1.25415027e-01 -1.18457489e-01 -2.88320363e-01 1.27688691e-01 -1.04230158e-01 3.88088450e-02 5.60946047e-01 8.86958599e-01 -1.08276713e+00 -1.05591917e+00 -3.98486316e-01 3.76913726e-01 -5.12107372e-01 8.82816166e-02 1.61874160e-01 3.65744144e-01 -6.08961701e-01 5.44332743e-01 1.28158212e-01 -4.35439467e-01 7.47022450e-01 -1.85783118e-01 -1.21692166e-01 6.83663785e-01 -1.03932226e+00 1.20269358e+00 -8.07884485e-02 3.76953840e-01 -2.20972314e-01 -7.96138227e-01 8.52312148e-01 1.09751749e+00 8.44609201e-01 -1.36403397e-01 -1.46307260e-01 5.40324032e-01 1.87709779e-01 -9.28578019e-01 1.83849260e-01 -3.41666609e-01 -3.13852787e-01 1.87585264e-01 2.89560795e-01 9.45717096e-02 3.02779675e-01 3.77488136e-01 1.46182191e+00 -7.33096749e-02 1.20894468e+00 -3.51169676e-01 5.24581254e-01 2.68023401e-01 8.55043054e-01 7.43640602e-01 -1.31213307e-01 5.79290450e-01 1.17263138e+00 -5.09401858e-01 -5.69712222e-01 -5.04965961e-01 -5.18706739e-01 6.23749673e-01 -4.19353306e-01 -9.82985795e-01 -5.89325368e-01 -9.72093105e-01 -3.76797944e-01 4.85255688e-01 -7.68552125e-01 1.84121341e-01 -7.35922396e-01 -1.01806152e+00 9.40757275e-01 2.93420553e-01 -1.36575460e-01 -1.23238814e+00 -6.95392191e-01 5.68401992e-01 -7.31846690e-01 -1.43456197e+00 -1.23844795e-01 4.63959426e-01 -5.05125880e-01 -1.48380923e+00 -3.38410795e-01 -7.15160787e-01 5.39801955e-01 -5.93174160e-01 1.21073163e+00 -4.78330515e-02 -9.01165083e-02 1.50922000e-01 -5.08753240e-01 -8.37078691e-01 -7.26268649e-01 4.37238097e-01 -1.68892846e-01 -3.29447359e-01 7.55086243e-01 -4.16761041e-02 -3.36549848e-01 9.37819183e-02 -8.27923834e-01 3.33358985e-05 7.53348827e-01 7.84336984e-01 6.21325076e-01 1.32936835e-02 8.48336935e-01 -1.43746865e+00 8.31621885e-01 -7.39673853e-01 1.15178250e-01 1.71052381e-01 -9.04334664e-01 -2.24149421e-01 4.17910665e-01 -2.67331511e-01 -6.94543481e-01 1.76251858e-01 -3.10229897e-01 5.74712038e-01 -1.20047018e-01 7.53658831e-01 6.87373951e-02 3.84600550e-01 8.95244718e-01 -2.01982275e-01 -1.36526108e-01 -4.31738406e-01 -1.79285675e-01 6.10887825e-01 1.68361336e-01 -3.18685919e-01 3.61029148e-01 1.38305977e-01 -1.44059300e-01 -4.35049444e-01 -1.21100748e+00 -6.15707517e-01 -5.57389975e-01 7.24684168e-03 1.19639206e+00 -5.91962039e-01 -6.88187063e-01 1.29262728e-04 -1.47457504e+00 -1.51158003e-02 -4.02036667e-01 7.18373299e-01 -3.15829158e-01 3.44576463e-02 -8.23551714e-01 -7.65034258e-01 -6.83697939e-01 -1.09495485e+00 1.06210196e+00 -9.79948565e-02 -1.13896275e+00 -1.05835962e+00 2.46283278e-01 4.36762691e-01 1.86283048e-02 6.88165724e-01 1.04295838e+00 -1.37892163e+00 9.61871445e-02 -2.33960241e-01 -1.04415014e-01 -1.11746453e-01 3.16128492e-01 -1.88404515e-01 -7.44565845e-01 2.33750120e-01 1.65407464e-01 -1.24481440e-01 6.31685436e-01 3.93523455e-01 6.09596372e-01 -6.01398945e-01 -7.32479155e-01 4.49487604e-02 1.21125948e+00 4.35598791e-01 4.92960274e-01 4.56074148e-01 3.53572100e-01 9.29630280e-01 6.02767766e-01 1.31857038e-01 3.82284373e-01 5.02956808e-01 -1.38722956e-01 -4.10939790e-02 4.28746641e-02 -1.26594990e-01 3.81669730e-01 7.41845787e-01 -3.10559094e-01 2.47214567e-02 -1.41149485e+00 6.04265332e-01 -1.92619169e+00 -8.01230550e-01 -4.09432888e-01 1.50725245e+00 1.41235983e+00 4.33762521e-01 9.84207615e-02 3.40085238e-01 2.31890932e-01 -1.08252726e-01 1.03311814e-01 -5.72587550e-01 -6.25498742e-02 4.41004962e-01 2.40586847e-01 5.10297060e-01 -1.06060576e+00 5.79387605e-01 6.96049595e+00 7.99007297e-01 -4.81251270e-01 1.85950443e-01 4.91774589e-01 -1.56328864e-02 -7.41194114e-02 -5.08119725e-02 -1.26006854e+00 2.95026034e-01 1.56010664e+00 -1.86439574e-01 -2.62746185e-01 3.84274393e-01 3.05363804e-01 -9.81614515e-02 -1.15147185e+00 5.19609928e-01 4.67758663e-02 -1.61562502e+00 -8.69995430e-02 2.36113131e-01 4.80325192e-01 -1.95705131e-01 -3.81562203e-01 2.16700763e-01 2.02262744e-01 -1.16939938e+00 5.27421474e-01 7.01392412e-01 6.20630980e-01 -4.13486183e-01 1.27638471e+00 3.37989092e-01 -9.90173995e-01 -2.53446046e-02 1.96265563e-01 4.42781076e-02 3.34735185e-01 7.75701284e-01 -1.25512362e+00 7.52610326e-01 6.33813679e-01 4.85052407e-01 -2.85641611e-01 6.86560214e-01 -3.33061337e-01 8.73474121e-01 -1.21767595e-01 -3.86136286e-02 7.73767531e-02 3.87095153e-01 6.49437308e-01 1.94895983e+00 6.62526712e-02 4.84229654e-01 1.55954674e-01 3.80786628e-01 1.19011857e-01 5.27956903e-01 -5.72927177e-01 -1.57661378e-01 3.52077752e-01 1.30293322e+00 -6.78440332e-01 -2.92497993e-01 -2.44443431e-01 2.21556798e-01 3.41579057e-02 1.04010306e-01 -6.76093459e-01 -3.28152686e-01 9.90690738e-02 3.06574255e-01 -5.06820045e-02 2.15273142e-01 -5.38237512e-01 -7.19796181e-01 -1.15021661e-01 -1.18354213e+00 9.13192153e-01 -1.87335894e-01 -1.10544944e+00 1.03575420e+00 1.89888701e-01 -1.03201377e+00 -4.84250516e-01 -5.85339904e-01 -8.03676024e-02 8.28360200e-01 -1.26252949e+00 -1.14953673e+00 5.96350208e-02 1.60947651e-01 3.72579545e-01 -6.91496655e-02 1.24646175e+00 5.08785129e-01 -4.79159951e-01 5.00784397e-01 -4.00585741e-01 3.70981842e-01 8.98677886e-01 -1.23991776e+00 2.77601704e-02 4.09281075e-01 -1.96035922e-01 7.30753064e-01 5.19882619e-01 -8.40164304e-01 -7.97070861e-01 -8.97347450e-01 2.02631664e+00 -8.46767664e-01 6.89717472e-01 -1.34374335e-01 -8.01410913e-01 7.43088841e-01 1.49371982e-01 -3.37756157e-01 1.35162449e+00 2.32137993e-01 -1.39758632e-01 2.53384441e-01 -1.15254021e+00 2.68836498e-01 6.88163936e-01 -4.72352892e-01 -7.80853987e-01 6.36084139e-01 7.58228064e-01 -5.51528275e-01 -1.34054542e+00 5.00977337e-01 6.83469772e-01 -5.14449239e-01 8.11235666e-01 -1.01882243e+00 7.68487394e-01 -7.00202286e-02 -9.64445174e-02 -6.84054315e-01 -2.67355263e-01 -7.29211271e-01 -1.51029453e-01 1.32051909e+00 1.26380479e+00 -6.29402936e-01 5.12580156e-01 8.47293317e-01 1.76786125e-01 -1.29448116e+00 -7.70185947e-01 -4.02781248e-01 1.34662632e-02 -4.37397510e-01 2.19225168e-01 1.05725348e+00 5.20759046e-01 6.42028689e-01 -1.42279118e-01 3.18468958e-02 2.43425325e-01 -1.96654364e-01 3.25247079e-01 -1.24799216e+00 -3.79916757e-01 -3.43944043e-01 -1.18320815e-01 -2.20536232e-01 -2.01186433e-01 -9.12805378e-01 -1.50741950e-01 -1.71880174e+00 5.33324242e-01 -3.83761555e-01 -3.73967648e-01 7.56079614e-01 -4.06257391e-01 9.98906121e-02 6.81874284e-04 3.01844478e-01 -3.28894049e-01 -4.16257948e-01 7.95774698e-01 3.51868346e-02 -4.35262054e-01 8.22934136e-02 -1.29511273e+00 9.59418118e-01 7.66769886e-01 -9.84336913e-01 -1.37519151e-01 -7.50772730e-02 6.26763165e-01 1.79645240e-01 5.88680096e-02 -4.36566561e-01 4.34214383e-01 -2.30507076e-01 1.33940265e-01 -4.73425120e-01 2.57931612e-02 -5.49465597e-01 3.75413954e-01 7.06298172e-01 -5.60675681e-01 -2.31530834e-02 2.61007339e-01 2.66058266e-01 -2.61517435e-01 -4.99747574e-01 5.27957380e-01 -1.95340097e-01 -7.12523013e-02 -2.82909334e-01 -6.16361320e-01 2.35291034e-01 8.81715298e-01 -1.56252217e-02 -3.41382623e-01 -2.38924667e-01 -1.09916651e+00 8.35185871e-02 -3.96428585e-01 1.40151769e-01 4.09491599e-01 -8.61466765e-01 -1.13142383e+00 -3.09379756e-01 -1.51282754e-02 -2.47850157e-02 -7.77421445e-02 1.39730704e+00 -2.66472876e-01 6.84612155e-01 2.64403075e-01 -3.16801041e-01 -1.41578352e+00 3.71190190e-01 2.98036575e-01 -1.37500322e+00 -5.43262362e-01 6.08338773e-01 1.18198499e-01 -2.31303334e-01 6.55102078e-03 -2.95551866e-01 -7.51735210e-01 5.45472264e-01 6.71986520e-01 2.32574895e-01 3.16669077e-01 -5.03269017e-01 -7.72682488e-01 3.51389915e-01 -2.37700865e-01 -6.48984686e-02 1.46489620e+00 2.32975706e-01 -2.55488276e-01 3.64010513e-01 9.42376435e-01 3.15164238e-01 -1.58085734e-01 -1.29135996e-01 6.10455573e-01 3.50807816e-01 -2.59513646e-01 -1.01668012e+00 -4.30986494e-01 3.96187484e-01 -7.09386468e-02 4.89984363e-01 9.60699916e-01 1.90983012e-01 6.67214215e-01 1.22647747e-01 1.19960435e-01 -8.12042356e-01 -2.83020198e-01 4.79858667e-01 9.17128265e-01 -7.93839753e-01 1.72719374e-01 -6.59950435e-01 -8.20100427e-01 1.09280491e+00 1.99016258e-01 3.51714998e-01 7.42364347e-01 6.20451272e-01 1.47955477e-01 -6.14004016e-01 -9.39639688e-01 5.40851541e-02 5.31421423e-01 3.12314391e-01 8.39955270e-01 2.25489046e-02 -1.03028214e+00 1.25860775e+00 -3.85417432e-01 4.46870625e-02 3.80015939e-01 8.94324124e-01 -7.15441396e-03 -1.33037186e+00 -2.88810968e-01 5.15409529e-01 -1.23072875e+00 -3.15501750e-01 -7.73310721e-01 9.64410603e-01 4.09458160e-01 1.12499428e+00 -4.44814384e-01 -3.49377751e-01 6.52623296e-01 3.25316668e-01 -1.17213530e-02 -7.84612060e-01 -1.22838724e+00 2.14689016e-01 8.57155859e-01 -5.16157985e-01 -6.95694268e-01 -8.69461656e-01 -1.45064521e+00 1.23072937e-01 -3.49968582e-01 5.95643222e-01 2.53609121e-01 9.75234509e-01 3.74552906e-01 6.35598660e-01 1.48416564e-01 -1.51494876e-01 -2.75481403e-01 -9.67028797e-01 -2.65251726e-01 2.14865386e-01 2.92680234e-01 -3.52000266e-01 -1.44230053e-01 3.90135527e-01]	[8.52079963684082, 8.835460662841797]
e2a93470-578c-4b44-8ad0-23756b7d1bc9	causal-effect-estimation-recent-advances	2302.00848	null	https://arxiv.org/abs/2302.00848v1	https://arxiv.org/pdf/2302.00848v1.pdf	Causal Effect Estimation: Recent Advances, Challenges, and Opportunities	Causal inference has numerous real-world applications in many domains, such as health care, marketing, political science, and online advertising. Treatment effect estimation, a fundamental problem in causal inference, has been extensively studied in statistics for decades. However, traditional treatment effect estimation methods may not well handle large-scale and high-dimensional heterogeneous data. In recent years, an emerging research direction has attracted increasing attention in the broad artificial intelligence field, which combines the advantages of traditional treatment effect estimation approaches (e.g., propensity score, matching, and reweighing) and advanced machine learning approaches (e.g., representation learning, adversarial learning, and graph neural networks). Although the advanced machine learning approaches have shown extraordinary performance in treatment effect estimation, it also comes with a lot of new topics and new research questions. In view of the latest research efforts in the causal inference field, we provide a comprehensive discussion of challenges and opportunities for the three core components of the treatment effect estimation task, i.e., treatment, covariates, and outcome. In addition, we showcase the promising research directions of this topic from multiple perspectives.	['Sheng Li', 'Wei Chu', 'Ruopeng Li', 'Jianmin Huang', 'Zhixuan Chu']	2023-02-02	null	null	null	null	['marketing']	['miscellaneous']	[ 5.81298053e-01 2.61325333e-02 -9.77904260e-01 -3.96155179e-01 -7.53439844e-01 -1.06686726e-01 5.80339372e-01 5.54714382e-01 -1.30173773e-01 1.04498637e+00 7.57272661e-01 -4.15716738e-01 -5.07038057e-01 -9.70633209e-01 -5.26044965e-01 -7.97770917e-01 -1.19990245e-01 3.23471665e-01 -2.01922745e-01 6.52118400e-02 3.00089955e-01 2.49067932e-01 -1.02846229e+00 -1.41867757e-01 1.29171300e+00 5.55747569e-01 -4.67422217e-01 -9.28062052e-02 1.51966810e-01 5.72532475e-01 -2.20894873e-01 -8.15122068e-01 -3.38989645e-01 -3.80017519e-01 -5.66428542e-01 -3.68903130e-01 3.72440159e-01 -2.48546958e-01 -6.55521214e-01 1.09020734e+00 6.81735218e-01 -3.00143342e-02 7.54490852e-01 -1.45070982e+00 -8.25380027e-01 8.67774904e-01 -9.60840404e-01 1.05047598e-01 4.48411882e-01 -5.93328103e-02 1.18652332e+00 -4.30700153e-01 4.93305564e-01 1.62605608e+00 5.08442700e-01 2.83848166e-01 -1.37269557e+00 -1.12653780e+00 3.71168315e-01 4.73421603e-01 -9.35407579e-01 -1.72781140e-01 8.12590957e-01 -6.55383289e-01 -1.16327703e-02 3.08983386e-01 5.96807718e-01 1.38786995e+00 5.02303839e-01 1.02671385e+00 1.40486598e+00 -2.03053519e-01 3.85760963e-01 -2.14380115e-01 2.14963868e-01 3.39968264e-01 2.79901445e-01 6.83218777e-01 -1.82371154e-01 -6.98918521e-01 8.51993442e-01 3.62923265e-01 -3.02564263e-01 -4.25295532e-01 -1.21875632e+00 1.46288002e+00 6.24382079e-01 3.01217008e-02 -5.75123966e-01 1.31737798e-01 4.56095785e-01 -1.71773862e-02 7.13633716e-01 1.00812063e-01 -3.11883420e-01 2.41865426e-01 -6.14949763e-01 5.65974891e-01 5.76795876e-01 6.28994524e-01 3.37358296e-01 -8.42519701e-02 -4.71925676e-01 7.50396788e-01 2.63579249e-01 6.61275446e-01 1.02899827e-01 -5.40111303e-01 5.33984005e-01 4.85846192e-01 -6.50683865e-02 -1.25859344e+00 -4.20671940e-01 -3.40661824e-01 -1.50937712e+00 -1.62175730e-01 4.65065062e-01 -3.10814321e-01 -5.13266325e-01 1.91485703e+00 7.43421197e-01 6.55130625e-01 -3.46794337e-01 8.68680298e-01 8.20641160e-01 3.98080498e-01 7.05759108e-01 -5.66421330e-01 1.42856753e+00 -5.52813351e-01 -1.10136235e+00 -3.76906127e-01 3.81448895e-01 -5.93763649e-01 5.81927955e-01 1.15448512e-01 -9.27003086e-01 -6.31889850e-02 -5.85452914e-01 1.23830959e-01 -1.10422164e-01 -3.50804269e-01 1.35890687e+00 5.15300393e-01 -4.12607342e-01 4.96946514e-01 -4.77054775e-01 -4.30739135e-01 7.25942731e-01 4.07507300e-01 -3.25120091e-01 -5.79786777e-01 -1.65367222e+00 6.51061416e-01 -5.94761409e-03 -1.09584443e-01 -7.46207058e-01 -1.01560652e+00 -8.89155567e-01 2.01033190e-01 6.67735755e-01 -1.00778246e+00 1.08378303e+00 -6.00550115e-01 -1.21435308e+00 4.99827564e-01 -9.85004008e-02 -2.59459108e-01 3.31943691e-01 -1.92547575e-01 -5.55137634e-01 -3.94990981e-01 6.04284443e-02 8.19385275e-02 6.25730753e-01 -8.82448673e-01 -7.12632239e-01 -1.00473702e+00 -1.06889732e-01 1.07113265e-01 -2.42418975e-01 2.41653547e-01 1.95536509e-01 -9.02294099e-01 -1.19666727e-02 -8.28923047e-01 -7.53930271e-01 -2.69837916e-01 -5.83724618e-01 -4.03319836e-01 4.33531880e-01 -4.63134885e-01 1.41595888e+00 -1.94605410e+00 3.40143174e-01 1.30537421e-01 4.71290857e-01 -5.22431508e-02 1.07140601e-01 4.59879071e-01 -4.14641708e-01 1.85954019e-01 -1.92803025e-01 2.05199748e-01 -1.06630705e-01 -2.56225467e-01 -3.62272680e-01 7.47012854e-01 -1.64539605e-01 1.05383813e+00 -1.20923293e+00 -5.36545753e-01 3.12073231e-01 3.20154339e-01 -7.24509060e-01 2.13369310e-01 -1.06611326e-01 6.60461009e-01 -9.70363379e-01 5.19288182e-01 7.24476874e-01 -3.26784968e-01 4.60159183e-01 -4.03060243e-02 3.39382552e-02 1.51756182e-01 -1.09762752e+00 1.30736315e+00 -3.32703620e-01 1.94008455e-01 2.01518238e-02 -1.53487539e+00 5.52776217e-01 5.37093878e-01 6.69106126e-01 -5.45056701e-01 1.74841851e-01 1.96393222e-01 2.24693254e-01 -6.22428715e-01 1.25846952e-01 -5.64414918e-01 -3.74862552e-01 3.25109571e-01 -4.38117921e-01 2.44493306e-01 -1.71140105e-01 8.49054083e-02 1.04020858e+00 -4.11816061e-01 8.25961232e-01 -2.59147473e-02 2.80201316e-01 -1.29388601e-01 6.91522896e-01 6.29002273e-01 -2.89370984e-01 2.23208547e-01 5.97928762e-01 -3.14311504e-01 -5.87943673e-01 -9.39247608e-01 -3.42404783e-01 9.60973442e-01 1.40796974e-01 -1.48110501e-02 -5.43056011e-01 -7.67598271e-01 4.68418837e-01 6.39858007e-01 -8.48443210e-01 -3.70546132e-01 -6.13261104e-01 -1.24437916e+00 2.96984792e-01 5.53712010e-01 2.77530789e-01 -1.00621486e+00 5.04611015e-01 3.71795982e-01 -3.02036196e-01 -6.41795039e-01 -4.97426838e-01 -3.73044223e-01 -1.25134706e+00 -1.19002581e+00 -6.99565649e-01 -5.66831052e-01 3.92599225e-01 2.93864131e-01 1.21405864e+00 -1.26200944e-01 -1.60811767e-01 -4.91522346e-03 -4.25678343e-02 -5.06780565e-01 -1.98780462e-01 -4.53803651e-02 -1.32715628e-02 -4.61640069e-03 5.78349054e-01 -7.01347530e-01 -9.14817452e-01 3.19427520e-01 -7.27250993e-01 -2.49683231e-01 8.96173477e-01 1.13583398e+00 3.90379012e-01 -4.27203327e-02 1.10688078e+00 -1.49787569e+00 7.27519155e-01 -1.02931869e+00 -5.42614043e-01 2.04754114e-01 -8.04926455e-01 -1.39227003e-01 4.01505768e-01 -5.35752654e-01 -1.29562891e+00 -3.85641783e-01 -1.75011143e-01 -2.86848024e-02 -2.92259216e-01 9.09807265e-01 -4.38331604e-01 2.61517644e-01 5.82837462e-01 -2.66934603e-01 8.32795259e-03 -3.71683687e-01 5.17138481e-01 7.04611182e-01 5.02163693e-02 -3.70521963e-01 7.09671557e-01 3.73870790e-01 1.58052444e-01 -1.22103401e-01 -1.10484993e+00 -2.83378720e-01 -2.00081065e-01 1.73976570e-02 8.97783697e-01 -8.24120522e-01 -1.04093635e+00 4.56297904e-01 -1.00425911e+00 8.26567411e-02 7.31050670e-02 8.79130065e-01 -2.26897836e-01 1.41460255e-01 -5.61753392e-01 -6.04079008e-01 -9.89456326e-02 -1.14760959e+00 8.78126204e-01 3.87842298e-01 -1.10639557e-01 -1.43381894e+00 8.72448534e-02 6.34383500e-01 1.52038902e-01 4.71396267e-01 1.40205312e+00 -4.76998270e-01 -6.18826151e-01 -4.34227198e-01 -3.20661455e-01 -2.91471094e-01 2.39232808e-01 -2.46460751e-01 -6.39052689e-01 -1.74270824e-01 -1.94878772e-01 -1.36487871e-01 7.55795181e-01 1.12257838e+00 1.31059587e+00 -2.67930210e-01 -9.20182943e-01 2.36430362e-01 1.22928631e+00 4.40406442e-01 6.51029229e-01 -9.33346599e-02 7.29172528e-01 7.20737338e-01 6.69671118e-01 4.06768531e-01 4.86356914e-01 8.52172434e-01 4.76322949e-01 -4.47602808e-01 2.73541331e-01 -5.40041566e-01 -1.69540599e-01 3.68730068e-01 -7.18223080e-02 -3.10275614e-01 -6.79502964e-01 2.60630280e-01 -2.15301800e+00 -1.18369937e+00 -4.74039525e-01 2.40041924e+00 8.07743490e-01 -1.00523457e-01 1.20259658e-01 -7.65470862e-02 1.13484192e+00 2.17946842e-01 -6.52874053e-01 -2.44640976e-01 1.24588795e-01 1.71308666e-01 4.77706522e-01 2.13395461e-01 -1.17266655e+00 7.26763666e-01 6.48604488e+00 9.75252509e-01 -7.43940532e-01 1.82766557e-01 8.70266616e-01 4.11166549e-01 -5.30189037e-01 2.25668952e-01 -4.89034295e-01 6.16532981e-01 5.26270926e-01 -3.69936526e-01 3.06428134e-01 6.07167959e-01 5.61452568e-01 -6.41408190e-02 -1.16924322e+00 6.90474391e-01 -1.52068764e-01 -1.32644343e+00 -1.70403719e-01 3.91765088e-01 9.82792616e-01 -3.97841364e-01 1.57262683e-01 5.32765031e-01 5.77383041e-01 -1.19755554e+00 -1.49822325e-01 3.10543478e-01 7.60052860e-01 -7.27132797e-01 8.29178929e-01 2.11882994e-01 -7.62486219e-01 -2.41810381e-01 -2.90098369e-01 -2.85307258e-01 4.58012581e-01 1.23799872e+00 -2.11263463e-01 7.63654828e-01 3.98794830e-01 9.37709272e-01 3.25366259e-02 1.26269341e+00 -4.44031417e-01 9.86877501e-01 1.63308278e-01 -1.81283746e-02 -7.36149997e-02 -4.18576717e-01 3.03218544e-01 6.32096350e-01 1.31961793e-01 3.76372218e-01 2.23230615e-01 6.01672649e-01 -2.23295048e-01 3.51840436e-01 -6.41865015e-01 1.04472479e-02 5.32972693e-01 9.64696229e-01 -1.92661852e-01 -2.43542343e-01 -6.21723652e-01 2.52666175e-01 2.82837301e-01 3.09881479e-01 -8.92569125e-01 2.87885331e-02 7.15710342e-01 1.94982618e-01 -3.70342880e-01 3.58122647e-01 -5.17050207e-01 -1.12972462e+00 -4.51674074e-01 -1.00629771e+00 8.64767730e-01 -3.54405552e-01 -1.60328341e+00 -2.74770409e-01 1.88327298e-01 -1.15395010e+00 -2.55127788e-01 -2.88691550e-01 -7.03552604e-01 8.34251165e-01 -1.20595622e+00 -9.12757695e-01 -7.23995492e-02 4.74836171e-01 2.40044668e-01 5.61635569e-02 7.80524552e-01 5.78853250e-01 -8.35973382e-01 4.70231086e-01 4.26923037e-01 1.06919348e-01 9.76947010e-01 -1.16088486e+00 8.40436071e-02 3.71485889e-01 -2.85966754e-01 6.16216183e-01 5.86147547e-01 -8.19286704e-01 -1.38078272e+00 -1.00585830e+00 1.02041304e+00 -1.14785559e-01 9.11980987e-01 -2.12898195e-01 -7.93473244e-01 7.31554210e-01 1.02178194e-01 -1.05859891e-01 7.77313650e-01 9.26960945e-01 -2.82665581e-01 -1.79917127e-01 -1.09955072e+00 8.35034847e-01 9.73685741e-01 -5.86003438e-02 -3.65653962e-01 6.20573103e-01 5.62475741e-01 -3.33875626e-01 -1.10630465e+00 5.73182106e-01 4.25920695e-01 -7.09563434e-01 1.17634916e+00 -1.05382061e+00 8.75166178e-01 2.42665425e-01 3.33079129e-01 -1.60775971e+00 -6.94551170e-01 -3.44849020e-01 -4.02325671e-03 1.26977932e+00 1.69553563e-01 -7.58645654e-01 8.34001482e-01 7.13889480e-01 1.56727567e-01 -8.36841643e-01 -8.92304897e-01 -2.53079236e-01 3.83461982e-01 -1.34372562e-01 6.58529341e-01 1.27565122e+00 1.63590968e-01 7.30051517e-01 -7.73271501e-01 8.07733834e-02 9.37869012e-01 5.38434386e-01 6.90851092e-01 -1.66134906e+00 -1.35652006e-01 -3.96209121e-01 -3.18609089e-01 -9.67369854e-01 3.60394061e-01 -8.57356369e-01 -2.45348811e-01 -1.71013165e+00 8.03878009e-01 -5.83978593e-01 -3.49616498e-01 1.98608890e-01 -9.53966200e-01 -2.57383913e-01 -2.85984129e-01 9.70091522e-02 -1.22570068e-01 5.99039912e-01 1.60634112e+00 -3.17319363e-01 -2.25513466e-02 4.73245054e-01 -9.68552709e-01 6.25458837e-01 7.52590477e-01 -7.44335949e-01 -4.11581099e-01 -1.32000327e-01 6.91559091e-02 6.59559011e-01 4.89011288e-01 -1.70665473e-01 4.37020361e-02 -7.85718143e-01 1.39628738e-01 -2.30467692e-01 -4.43322398e-02 -7.78397262e-01 2.51517087e-01 6.50124431e-01 -5.03505051e-01 -1.88780576e-02 -2.42286161e-01 9.52475488e-01 -2.75810868e-01 3.35777514e-02 6.45805299e-01 9.03782174e-02 -4.82498437e-01 7.50540376e-01 -1.81771189e-01 2.49327719e-01 9.87206936e-01 2.67239392e-01 -6.35716558e-01 -4.82876182e-01 -5.30234218e-01 4.11659032e-01 -1.30909204e-01 5.06629765e-01 3.51020187e-01 -1.50238514e+00 -1.13378537e+00 -2.38600194e-01 1.41936123e-01 -2.90599138e-01 7.02796876e-01 1.19195831e+00 4.43087339e-01 3.51143837e-01 1.44811049e-01 -2.77784854e-01 -1.07237411e+00 9.07477617e-01 -1.07347518e-01 -5.79109251e-01 -4.37775731e-01 3.26808363e-01 7.07640350e-01 -3.09024721e-01 1.69624507e-01 1.45255446e-01 -4.45161015e-01 5.17902523e-02 4.61819470e-01 5.17942011e-01 -3.05986911e-01 -2.27799788e-01 -3.46894979e-01 2.50924438e-01 -1.07130364e-01 3.05515587e-01 1.34774411e+00 1.20358028e-01 -3.14564973e-01 1.33493811e-01 1.10577130e+00 1.00497179e-01 -6.74864292e-01 -4.39488977e-01 5.59319034e-02 -6.34663045e-01 2.66776830e-01 -8.27910602e-01 -1.19091189e+00 7.60632336e-01 4.27501619e-01 2.99607843e-01 1.03105390e+00 8.98499042e-02 5.65345407e-01 -2.57902652e-01 3.82496864e-01 -8.19367588e-01 -1.44306928e-01 6.87682405e-02 8.09680223e-01 -1.57038331e+00 2.18566567e-01 -8.31504822e-01 -2.28279680e-01 4.74022120e-01 3.90631557e-01 -6.71651289e-02 8.03109348e-01 1.39999136e-01 -2.31673181e-01 -1.63438678e-01 -4.78706479e-01 5.47828414e-02 4.29962873e-01 5.31036437e-01 8.41300905e-01 4.58982915e-01 -8.78840923e-01 6.68331027e-01 1.08350419e-01 1.66719347e-01 1.40236869e-01 3.55371743e-01 -8.76714475e-03 -1.30745304e+00 -4.19967115e-01 1.04294038e+00 -6.23627245e-01 -3.18482161e-01 -9.63643342e-02 9.61310327e-01 -1.26820326e-01 1.06283581e+00 -1.79770350e-01 -1.13303401e-01 4.72981870e-01 -2.77668029e-01 2.25394234e-01 -3.36875528e-01 -4.36052561e-01 -3.90699133e-02 -2.16321088e-02 -4.83418405e-01 -5.87547481e-01 -9.20391500e-01 -7.12864161e-01 -7.57845879e-01 -5.05976081e-01 2.86951691e-01 4.32116300e-01 9.70714152e-01 7.03370869e-02 5.78623474e-01 7.68841684e-01 -3.50668967e-01 -7.10514903e-01 -8.94002914e-01 -5.89123309e-01 4.89092499e-01 2.58307531e-02 -9.98175561e-01 -2.73444206e-01 -2.74763167e-01]	[8.0391206741333, 5.387927055358887]
1c94a224-ff62-4d90-8d7d-4759d4326c71	data-driven-optimal-power-flow-a-physics	2006.00544	null	https://arxiv.org/abs/2006.00544v1	https://arxiv.org/pdf/2006.00544v1.pdf	Data-driven Optimal Power Flow: A Physics-Informed Machine Learning Approach	This paper proposes a data-driven approach for optimal power flow (OPF) based on the stacked extreme learning machine (SELM) framework. SELM has a fast training speed and does not require the time-consuming parameter tuning process compared with the deep learning algorithms. However, the direct application of SELM for OPF is not tractable due to the complicated relationship between the system operating status and the OPF solutions. To this end, a data-driven OPF regression framework is developed that decomposes the OPF model features into three stages. This not only reduces the learning complexity but also helps correct the learning bias. A sample pre-classification strategy based on active constraint identification is also developed to achieve enhanced feature attractions. Numerical results carried out on IEEE and Polish benchmark systems demonstrate that the proposed method outperforms other alternatives. It is also shown that the proposed method can be easily extended to address different test systems by adjusting only a few hyperparameters.	['Junbo Zhao', 'Juan Yu', 'Hongxin Yu', 'Xingyu Lei', 'Qian Gao', 'Zhifang Yang']	2020-05-31	null	null	null	null	['physics-informed-machine-learning']	['graphs']	[-1.15042947e-01 -1.41817763e-01 -4.73047495e-01 -3.50899369e-01 -3.58475685e-01 -1.71775818e-01 2.68681735e-01 6.83373809e-02 2.21776776e-03 7.39804983e-01 -4.98554945e-01 -4.35499430e-01 -8.26379478e-01 -5.57829320e-01 -2.87719041e-01 -9.76117313e-01 -2.18636811e-01 3.06149989e-01 -2.12404922e-01 -1.72294632e-01 5.64775586e-01 5.55547953e-01 -1.57241154e+00 -3.66527885e-01 1.47434044e+00 1.10291576e+00 4.39985275e-01 2.72183329e-01 -8.68762508e-02 5.18540025e-01 -7.25535154e-01 7.24238530e-02 2.89251328e-01 -2.86543638e-01 -2.85996467e-01 1.80856541e-01 -1.55383468e-01 -3.01481877e-02 5.07914871e-02 9.39498842e-01 5.30299127e-01 1.81489632e-01 7.72140026e-01 -1.65807092e+00 -1.01437606e-01 3.46846491e-01 -6.64432228e-01 1.47242144e-01 6.65263906e-02 -1.66410506e-01 9.63330448e-01 -9.68933880e-01 -3.42728458e-02 8.62959802e-01 5.31530142e-01 2.00164959e-01 -1.16108215e+00 -6.65828228e-01 1.09162010e-01 4.95071083e-01 -1.40770590e+00 4.35556956e-02 1.19679129e+00 -5.13267040e-01 1.16355991e+00 2.25511014e-01 7.71975279e-01 3.32797557e-01 5.52781582e-01 6.88868225e-01 1.00439548e+00 -7.00829208e-01 6.60128355e-01 3.66154164e-01 3.00817996e-01 6.63812459e-01 3.24158698e-01 8.00774321e-02 -2.52308011e-01 -2.46068045e-01 3.14318299e-01 -1.82645306e-01 -3.20548266e-01 -7.98349082e-01 -4.17643398e-01 9.37661648e-01 4.43474650e-01 3.60534996e-01 -1.59968853e-01 -1.40761435e-01 2.70690471e-01 3.00274134e-01 2.71029949e-01 7.03665078e-01 -5.53734601e-01 7.76006877e-02 -1.13791668e+00 -1.94807223e-03 8.02100658e-01 7.67050087e-01 6.41729414e-01 6.39434576e-01 1.78663373e-01 9.11394775e-01 4.33616549e-01 1.73283696e-01 3.95138741e-01 -7.46674240e-01 5.82232654e-01 9.43085372e-01 1.84366584e-01 -9.20336068e-01 -6.13992989e-01 -7.05921650e-01 -8.41184378e-01 5.97030103e-01 1.53092146e-01 -4.08079952e-01 -6.57589436e-01 1.32059622e+00 7.40628913e-02 -9.24776793e-02 1.40672728e-01 7.36028373e-01 2.39382938e-01 8.84241760e-01 -1.05465658e-01 -4.88551736e-01 9.71549988e-01 -7.39698112e-01 -9.84360516e-01 -9.26555023e-02 5.83776474e-01 -4.87406284e-01 8.67280543e-01 5.38187087e-01 -9.82650936e-01 -5.01547873e-01 -1.70243299e+00 3.92268091e-01 -5.22057533e-01 4.83535916e-01 7.08585203e-01 9.22331631e-01 -7.37681866e-01 6.60148919e-01 -6.27290666e-01 -5.80203980e-02 3.79626364e-01 8.16265047e-01 2.08906874e-01 3.86698723e-01 -1.18455791e+00 1.13693833e+00 7.71611929e-01 6.66425467e-01 -4.74355072e-01 -7.90219724e-01 -7.83351123e-01 4.11251783e-01 5.49143136e-01 -4.46404606e-01 7.93236911e-01 -9.35972512e-01 -2.07091260e+00 -2.32640114e-02 1.13174945e-01 -3.57440710e-01 3.48077208e-01 -9.89698097e-02 -3.30437571e-01 -7.17841089e-02 -4.88527983e-01 4.78729792e-03 1.05813873e+00 -1.10256767e+00 -6.47057772e-01 -8.64015892e-02 1.03658903e-02 1.74121574e-01 -7.04844892e-01 -3.49368423e-01 -1.09743677e-01 -4.71244425e-01 3.60484608e-02 -6.67069852e-01 -3.99247319e-01 -2.80861020e-01 -3.07563275e-01 -2.61088997e-01 1.06678379e+00 -3.40925455e-01 1.45673478e+00 -1.98869610e+00 4.27017450e-01 7.66692102e-01 -5.81170209e-02 4.61629063e-01 3.13812941e-01 5.01296520e-01 -3.40363026e-01 -1.90728620e-01 -2.75860429e-01 -2.93007549e-02 2.83289701e-01 1.33290410e-01 -1.10042773e-01 5.10910094e-01 3.58118385e-01 4.20326561e-01 -4.91220325e-01 -5.30103445e-01 7.36737788e-01 3.31426620e-01 -6.23596966e-01 1.66748405e-01 6.71351925e-02 1.46282718e-01 -4.38925713e-01 4.87901300e-01 6.65311515e-01 -1.55970052e-01 3.66748422e-01 -1.59007311e-01 -2.24613383e-01 -2.55029291e-01 -1.59880888e+00 1.17648077e+00 -9.33407247e-01 4.88754362e-01 1.79501638e-01 -1.57596731e+00 1.33622468e+00 2.96767801e-01 6.71434581e-01 -6.06158316e-01 4.50208783e-01 4.43153650e-01 1.56023830e-01 -5.37569344e-01 2.01611176e-01 8.62376764e-02 -1.57587677e-01 1.53439581e-01 3.30040336e-01 -5.17025292e-02 4.56021547e-01 -2.60356128e-01 2.49262646e-01 7.33068064e-02 5.92812479e-01 -8.81164730e-01 1.20962191e+00 -1.57946855e-01 1.11468160e+00 3.77463967e-01 5.59961498e-02 -1.24482594e-01 5.96753776e-01 -3.65872145e-01 -8.44277859e-01 -8.44910324e-01 -5.01754940e-01 6.03076398e-01 2.93980062e-01 -2.61217475e-01 -6.75968945e-01 -6.05490446e-01 1.03728391e-01 9.30597007e-01 -3.86586040e-01 -4.17521477e-01 -4.09641176e-01 -1.22066402e+00 -1.29490003e-01 5.43856859e-01 4.77605194e-01 -5.66183269e-01 -6.86767340e-01 1.95789635e-01 3.16121936e-01 -6.08222544e-01 1.24630064e-01 6.37142718e-01 -1.05985188e+00 -9.71751392e-01 -6.76339626e-01 -9.36580658e-01 8.56512845e-01 -3.85168999e-01 7.73842871e-01 1.59023300e-01 -2.44236827e-01 1.94407590e-02 -1.94238588e-01 -4.56142634e-01 -2.54063815e-01 2.28465959e-01 1.87356830e-01 1.07312419e-01 3.94298553e-01 -5.40925920e-01 -2.38774002e-01 2.78928846e-01 -2.72787064e-01 -9.97977890e-03 8.10806930e-01 1.19206929e+00 3.73204589e-01 7.25403786e-01 1.05205190e+00 -7.00072765e-01 5.50162017e-01 -4.42687035e-01 -1.33017719e+00 3.50945145e-01 -1.24760449e+00 1.39697328e-01 1.15773249e+00 -2.81901687e-01 -1.33317661e+00 1.48177519e-01 1.48744211e-01 -4.09511834e-01 1.10552989e-01 3.99838477e-01 -4.55961317e-01 -2.52191365e-01 6.81803897e-02 2.86366250e-02 -1.21080063e-01 -4.60739136e-01 -1.64648563e-01 8.44213307e-01 2.71825463e-01 -4.38733935e-01 1.04765832e+00 5.96596533e-03 4.06742811e-01 -8.19268405e-01 -3.85837406e-01 -6.69301674e-02 -7.34341383e-01 -4.76160318e-01 4.35391933e-01 -5.51350057e-01 -9.98375416e-01 3.37609291e-01 -6.00947440e-01 -2.82602534e-02 -1.43642917e-01 5.65685749e-01 -7.50360191e-01 2.08955124e-01 -2.81704575e-01 -1.11099386e+00 -5.14724016e-01 -1.24591100e+00 3.84468108e-01 5.80283284e-01 -8.17181990e-02 -1.20483005e+00 -3.11785728e-01 2.73428798e-01 2.89262503e-01 2.53583342e-01 1.41029203e+00 -5.03373682e-01 -3.87219906e-01 -2.60710597e-01 2.75942594e-01 4.03442174e-01 -6.40528575e-02 3.63849729e-01 -6.76134348e-01 -6.98602200e-01 3.19782615e-01 -2.81522777e-02 3.11486840e-01 5.01693189e-01 9.86653328e-01 1.06027104e-01 -3.06217849e-01 6.55375540e-01 1.88603079e+00 5.94694078e-01 4.59866405e-01 4.81066138e-01 3.33719105e-01 5.44029295e-01 9.42869842e-01 5.95231593e-01 -4.38304804e-02 5.48668146e-01 4.26371485e-01 -3.96025658e-01 4.74962234e-01 8.71778131e-02 1.38498813e-01 7.91999519e-01 1.21195100e-01 -1.30841732e-01 -8.58865499e-01 3.80283564e-01 -1.82671702e+00 -5.88856459e-01 -1.49282709e-01 2.02887797e+00 1.89766720e-01 3.92643780e-01 -1.06286667e-01 9.83851731e-01 7.80834377e-01 -1.06345147e-01 -6.39590561e-01 -8.43902111e-01 1.59101859e-01 2.77170449e-01 3.72151285e-01 7.28194714e-01 -1.02922523e+00 2.04992458e-01 6.00578737e+00 8.18368435e-01 -1.10641408e+00 -2.51846194e-01 4.06640530e-01 -1.11406885e-01 1.38086438e-01 -5.01507781e-02 -7.30992496e-01 5.92875361e-01 8.45086753e-01 -5.99125087e-01 3.10898036e-01 1.03906870e+00 4.96657997e-01 -3.56686711e-01 -9.89751041e-01 1.06182587e+00 -6.99076578e-02 -1.05063426e+00 -3.26470166e-01 -2.71451604e-02 7.60246038e-01 -5.37768543e-01 -4.14660238e-02 4.10171032e-01 -3.14309955e-01 -6.81816101e-01 5.89787543e-01 4.20789570e-01 2.86206633e-01 -1.27424502e+00 1.03893340e+00 4.99588817e-01 -1.11769140e+00 -1.04066026e+00 -2.55056262e-01 -2.54418761e-01 -4.94927764e-02 6.43629491e-01 -7.52267659e-01 9.45720673e-01 6.76087856e-01 5.78599632e-01 -5.80577195e-01 1.10947728e+00 1.41277313e-02 3.89815569e-01 -3.97796780e-01 -4.01664734e-01 6.10035891e-03 -4.00162190e-01 5.00726879e-01 6.88527107e-01 3.95036697e-01 -3.59229475e-01 1.50156274e-01 9.71903503e-01 4.65247005e-01 2.37811506e-01 -2.57761747e-01 1.64557278e-01 5.22821844e-01 1.41475904e+00 -6.73267365e-01 6.80942694e-03 -4.83254433e-01 3.49601984e-01 9.86903906e-02 4.36437130e-01 -8.79595459e-01 -7.87208080e-01 3.56112808e-01 -1.29871801e-01 2.73903519e-01 -4.95601408e-02 -4.64707494e-01 -9.37841952e-01 4.51556146e-02 -4.91676092e-01 4.76372927e-01 -2.96673864e-01 -1.02734447e+00 4.13527161e-01 2.84836382e-01 -1.57744730e+00 -6.95528984e-01 -6.92266285e-01 -6.46465242e-01 1.02405131e+00 -1.68233526e+00 -5.67313313e-01 -1.36974812e-01 4.86710876e-01 5.60180128e-01 -4.82651711e-01 6.95354462e-01 4.07933116e-01 -1.30673313e+00 6.77457750e-01 5.40436089e-01 -2.45294020e-01 -5.17742336e-02 -1.38932693e+00 -3.62280607e-01 9.65010643e-01 -3.92685175e-01 2.83031970e-01 9.39433336e-01 -2.10767627e-01 -1.44702399e+00 -6.80935383e-01 6.20798349e-01 2.48239651e-01 4.91720766e-01 -5.75907528e-01 -7.06616163e-01 1.94829866e-01 2.94790000e-01 -2.03899499e-02 6.69826806e-01 -2.36280560e-02 4.09225464e-01 -5.10714352e-01 -1.18561733e+00 3.93700600e-01 2.11365834e-01 -1.28316283e-01 -6.18660390e-01 1.31422341e-01 -1.45780489e-01 -1.72213852e-01 -1.16213405e+00 6.60477221e-01 2.11159840e-01 -8.95372152e-01 7.03454554e-01 -2.23030046e-01 -1.53298900e-01 -5.85842192e-01 3.30713950e-02 -1.37544858e+00 -3.53348017e-01 -8.04550946e-01 -5.35126507e-01 1.41429865e+00 3.52826506e-01 -7.95481980e-01 8.44449580e-01 5.24593651e-01 -1.06660880e-01 -1.20059597e+00 -1.06914794e+00 -8.97357285e-01 5.13716638e-02 -1.11557461e-01 4.76936549e-01 7.77269661e-01 3.01096052e-01 3.11649352e-01 -1.87607348e-01 4.12814051e-01 6.84036255e-01 4.65709239e-01 3.78496408e-01 -1.43856239e+00 -3.71161461e-01 -4.00558680e-01 -3.47218841e-01 -3.82182717e-01 4.23937947e-01 -7.65128076e-01 -2.07573116e-01 -1.15166414e+00 -7.86111653e-02 -5.91432571e-01 -5.56110799e-01 2.39510536e-01 -7.45274499e-02 -6.45737872e-02 1.90882847e-01 -5.45550287e-02 -9.78577659e-02 7.98897922e-01 8.48841250e-01 5.44019155e-02 -3.64879221e-01 1.77073181e-01 -2.28116885e-01 8.07355702e-01 1.06456554e+00 -2.50357509e-01 -7.74826765e-01 -5.01969159e-02 -7.38367736e-02 2.92899430e-01 -8.61579105e-02 -1.29773366e+00 1.61703601e-01 2.18976662e-02 5.23508966e-01 -7.68273056e-01 1.87479779e-01 -1.34099114e+00 8.62336084e-02 8.34994078e-01 -3.84225994e-02 -8.56324360e-02 1.86549023e-01 4.14726973e-01 -1.88412711e-01 -6.07242823e-01 9.80260670e-01 4.08445865e-01 -7.14187443e-01 -2.18597889e-01 -5.34226358e-01 -3.19425732e-01 1.32737815e+00 -4.22996134e-01 1.00580715e-01 -1.42856017e-01 -6.12632692e-01 6.68884099e-01 5.97264767e-02 4.68273550e-01 2.80592710e-01 -1.38632786e+00 -1.84106544e-01 5.19100130e-01 -1.77256450e-01 -2.89816976e-01 2.90319890e-01 8.30342948e-01 -4.32535738e-01 7.21909046e-01 -2.77386039e-01 -6.85337245e-01 -1.11271238e+00 6.94041073e-01 6.36882842e-01 -2.91674018e-01 -5.73329747e-01 1.83963224e-01 -4.49412942e-01 -2.34430000e-01 4.35837239e-01 -8.60039815e-02 -4.41529125e-01 2.00927973e-01 2.58333623e-01 7.08874226e-01 2.30734482e-01 -4.76044744e-01 -4.14791673e-01 7.71104038e-01 7.72727728e-02 3.15741658e-01 1.33614969e+00 -2.10649356e-01 1.82450041e-01 4.27987576e-01 1.17143178e+00 -4.47804213e-01 -1.31705809e+00 1.64576769e-01 2.60717601e-01 -3.85514617e-01 6.33214593e-01 -6.38359845e-01 -1.56695449e+00 7.21347034e-01 7.67330348e-01 2.15511635e-01 1.56437671e+00 -6.76971138e-01 4.34633255e-01 4.89203811e-01 4.21981335e-01 -1.60313404e+00 -2.35617042e-01 1.26123443e-01 7.24032819e-01 -8.34917545e-01 2.24248290e-01 -5.11986911e-01 -3.42184603e-02 1.50957406e+00 7.94421017e-01 -2.18678415e-01 7.70792544e-01 6.17086470e-01 -8.29206929e-02 6.41316846e-02 -6.94539726e-01 2.18282029e-01 6.98229745e-02 4.12530661e-01 2.22069457e-01 -2.73517221e-01 -7.41017520e-01 6.30459785e-01 -3.09643894e-02 9.97275710e-02 5.84541619e-01 1.06458986e+00 -2.51806170e-01 -1.02898228e+00 -5.76882064e-01 4.96129364e-01 -3.48279804e-01 4.44561273e-01 6.20843982e-03 1.14402330e+00 1.39504403e-01 1.01059389e+00 1.01195753e-01 -3.09971333e-01 3.61369461e-01 1.15965270e-01 4.07577068e-01 -1.50143504e-01 -4.26221371e-01 2.19632443e-02 -8.06320384e-02 -4.75921243e-01 -2.01398775e-01 -5.83218873e-01 -1.32662189e+00 -3.27314101e-02 -8.18086624e-01 4.74678755e-01 6.56066835e-01 9.16139305e-01 6.65960312e-02 7.48442948e-01 1.18202484e+00 -9.23629940e-01 -6.22026145e-01 -7.18492925e-01 -7.25139439e-01 -5.18319421e-02 1.36610791e-01 -1.21511793e+00 -5.46180785e-01 -5.28887689e-01]	[5.881826877593994, 2.906022310256958]
f421bbb0-fc98-4a9f-bf3d-d8e6578445d4	project-then-transfer-effective-two-stage	null	null	https://aclanthology.org/2021.eacl-main.221	https://aclanthology.org/2021.eacl-main.221.pdf	Project-then-Transfer: Effective Two-stage Cross-lingual Transfer for Semantic Dependency Parsing	This paper describes the first report on cross-lingual transfer for semantic dependency parsing. We present the insight that there are twodifferent kinds of cross-linguality, namely sur-face level and mantic level, and try to cap-ture both kinds of cross-linguality by combin-ing annotation projection and model transferof pre-trained language models. Our exper-iments showed that the performance of our graph-based semantic dependency parser almost achieved the approximated upper bound.	['Toshinori Miyoshi', 'Terufumi Morishita', 'Gaku Morio', 'Hiroaki Ozaki']	2021-04-01	null	null	null	eacl-2021-2	['semantic-dependency-parsing']	['natural-language-processing']	[-6.00790143e-01 5.90845108e-01 -5.62823415e-01 -6.22278690e-01 -1.25149286e+00 -7.45863497e-01 5.23009896e-01 7.23682344e-03 -3.49482000e-01 8.11461270e-01 3.20584804e-01 -5.92689693e-01 4.84764606e-01 -5.55946887e-01 -7.73605525e-01 -1.57234803e-01 -1.02381252e-01 4.96638298e-01 4.23611879e-01 -3.87187988e-01 -1.14905983e-01 2.18663394e-01 -8.66815209e-01 5.80536366e-01 8.14355075e-01 3.89344186e-01 -1.31958323e-02 5.42903960e-01 -6.40456557e-01 4.37773705e-01 -4.90717441e-01 -8.76420140e-01 -8.83096904e-02 -6.06852651e-01 -1.05604231e+00 -1.33531526e-01 3.03158879e-01 3.79939526e-01 1.11176535e-01 1.21383440e+00 1.20743811e-01 -3.54713559e-01 5.25024891e-01 -1.00694644e+00 -9.37947929e-01 1.01494348e+00 -5.92864692e-01 2.70676613e-01 3.72064948e-01 -5.18280864e-01 1.18865073e+00 -5.36361098e-01 8.05655420e-01 1.67107952e+00 8.15560699e-01 7.31317818e-01 -1.03287053e+00 -6.56048238e-01 6.51522100e-01 -2.66340878e-02 -1.03367579e+00 -3.41838181e-01 7.28201747e-01 -2.48633146e-01 1.29811394e+00 -3.09823692e-01 2.66090751e-01 9.30428028e-01 3.72096121e-01 6.22126162e-01 1.47893667e+00 -8.84754539e-01 -1.68705910e-01 1.63227484e-01 4.66272384e-01 9.43607628e-01 2.35396370e-01 -9.05909091e-02 -6.00953937e-01 2.02926978e-01 7.57203996e-01 -8.40517342e-01 3.93829569e-02 -3.81864868e-02 -7.57704854e-01 8.58535707e-01 3.69519979e-01 7.45224178e-01 1.40050948e-01 1.13467149e-01 6.97919130e-01 4.67057973e-01 5.54066896e-01 1.96846202e-01 -1.05948102e+00 1.79540694e-01 -3.19566876e-01 -5.60862124e-01 9.87632155e-01 1.11662889e+00 7.09279060e-01 1.45847663e-01 3.44803661e-01 9.29941356e-01 4.99015808e-01 2.47298777e-01 5.77851057e-01 -4.12761778e-01 8.91757786e-01 3.78655404e-01 -3.36024433e-01 -4.01551843e-01 -3.72830868e-01 6.95525715e-03 -2.00844541e-01 -3.90118770e-02 4.35720921e-01 -5.00145316e-01 -1.14070392e+00 1.98582447e+00 9.57161263e-02 3.87772433e-02 4.32395697e-01 5.51423132e-01 7.60969937e-01 4.44677949e-01 1.00805008e+00 1.63028929e-02 1.77514589e+00 -1.03530610e+00 -8.21119606e-01 -4.21199530e-01 1.35621309e+00 -8.51179183e-01 1.14608932e+00 -1.26628369e-01 -1.02957451e+00 -6.75896645e-01 -1.06480718e+00 -2.48063639e-01 -8.16093504e-01 -7.10155964e-02 8.86223376e-01 7.44166613e-01 -1.33070266e+00 3.79106224e-01 -9.27293718e-01 -7.22781420e-01 9.56885442e-02 7.52899945e-02 -7.82926142e-01 -1.15620933e-01 -1.24516308e+00 1.12170982e+00 6.11038089e-01 -2.82183051e-01 -4.70677197e-01 -5.46923757e-01 -1.08567619e+00 -2.29772121e-01 -6.62562845e-04 -4.39654022e-01 1.23097169e+00 -1.01730704e+00 -1.38355851e+00 1.54255140e+00 -1.32238701e-01 -3.63386758e-02 3.56364548e-02 -3.53470027e-01 -6.81641400e-01 -2.14161530e-01 2.59920537e-01 5.10423243e-01 3.01293343e-01 -1.20627582e+00 -4.77983564e-01 -6.06532216e-01 2.93985546e-01 3.14041615e-01 -2.16728449e-01 6.43306255e-01 -7.49662638e-01 -6.22001350e-01 1.25737563e-01 -8.73979032e-01 3.52163389e-02 -5.97861171e-01 -2.52632111e-01 -5.83263218e-01 7.72525191e-01 -7.72550046e-01 9.05027628e-01 -2.02873826e+00 7.43985921e-02 -3.37889820e-01 -5.14893770e-01 2.96717376e-01 -4.03388947e-01 6.40125990e-01 -5.62387645e-01 4.19377536e-01 -1.16993353e-01 -5.15926003e-01 -7.75370970e-02 6.93107903e-01 -2.77024321e-02 8.51974860e-02 2.25280643e-01 1.03988385e+00 -9.34460282e-01 -7.40800560e-01 -6.45118207e-02 3.95845503e-01 -4.80500340e-01 4.59485024e-01 -3.09503347e-01 4.59893823e-01 -5.70556521e-01 5.81256449e-01 3.84088486e-01 1.43137693e-01 7.88049877e-01 -2.36449227e-01 -1.28209382e-01 8.18855584e-01 -5.12538314e-01 2.21086359e+00 -9.42913532e-01 1.00748897e-01 3.18529218e-01 -9.38910365e-01 7.31506169e-01 5.67758739e-01 2.95643974e-02 -4.81950402e-01 1.57195777e-01 3.73637259e-01 2.71361843e-02 -4.92822140e-01 1.12287946e-01 -5.10510147e-01 -6.12087071e-01 2.73737013e-01 5.45921922e-01 -2.47734189e-01 3.93021815e-02 -4.43677709e-04 5.52194715e-01 7.46621490e-01 4.83424902e-01 -8.25362563e-01 6.08434081e-01 1.79497823e-01 4.31921840e-01 1.90880135e-01 -1.80907369e-01 1.78716153e-01 8.25909495e-01 -2.49918386e-01 -6.01548791e-01 -8.88925254e-01 -8.43531117e-02 1.49195743e+00 -4.34461832e-02 -5.91463983e-01 -1.21499026e+00 -1.33821249e+00 -4.32305813e-01 8.69046152e-01 -4.98939335e-01 2.59685546e-01 -8.75030160e-01 -7.96562493e-01 6.06766403e-01 8.47835124e-01 5.26285946e-01 -8.99854958e-01 -2.24715248e-02 -3.38470214e-03 -7.85216317e-02 -1.68793523e+00 -3.51395816e-01 4.90702420e-01 -9.66941297e-01 -9.55189466e-01 -2.23898709e-01 -1.45251906e+00 5.39765775e-01 -2.05976948e-01 1.49357617e+00 1.05842128e-01 1.48859352e-01 2.21599653e-01 -5.81658542e-01 -1.62867337e-01 -5.69193363e-01 3.96547884e-01 -3.23231786e-01 -6.08860493e-01 7.38549292e-01 -6.98454678e-01 6.69981865e-03 -2.31512766e-02 -3.23491424e-01 -1.47404984e-01 5.20512760e-01 4.91046816e-01 5.09183884e-01 -3.88761222e-01 5.34916103e-01 -1.32753408e+00 6.23294115e-01 -3.61645669e-01 -5.08307397e-01 4.77944821e-01 -2.70508707e-01 3.74034375e-01 7.17929900e-01 1.02910399e-01 -1.34607625e+00 6.17470928e-02 -7.14744210e-01 3.64504312e-03 -5.18441021e-01 5.05695939e-01 -5.84623396e-01 1.32155642e-01 3.84579062e-01 -5.04620314e-01 -5.50496340e-01 -6.85246944e-01 9.13981557e-01 4.92187798e-01 4.64336425e-01 -1.15475583e+00 4.02501494e-01 1.54296011e-01 -3.47214758e-01 -7.08741605e-01 -1.27950513e+00 -2.48586372e-01 -1.13409877e+00 4.29341853e-01 1.55737615e+00 -9.95081723e-01 -4.13705297e-02 2.59989470e-01 -1.59601533e+00 -5.06105006e-01 -1.15926951e-01 4.79403526e-01 -4.49491531e-01 3.56406391e-01 -1.15096962e+00 -2.01723799e-01 -2.30275035e-01 -8.11871767e-01 1.05114412e+00 -1.15759812e-01 4.76189181e-02 -1.72772431e+00 4.17036355e-01 1.76917642e-01 -1.44041404e-02 1.65473241e-02 1.29707813e+00 -9.69879329e-01 -1.89672917e-01 -1.94465294e-01 -3.31159949e-01 3.35686207e-01 1.72890097e-01 -3.34836096e-01 -1.03629470e+00 -9.35196951e-02 -2.12576747e-01 -3.95022690e-01 4.35227215e-01 8.32183510e-02 6.74770474e-01 2.01389968e-01 -4.54280317e-01 6.09059334e-01 1.53931236e+00 4.13204618e-02 6.21309519e-01 1.25671148e-01 8.42409670e-01 7.77675271e-01 3.79477620e-01 -4.96982217e-01 8.45870256e-01 7.01717734e-01 2.12898273e-02 -2.41447315e-01 -6.33324265e-01 -5.86454630e-01 5.73467195e-01 1.44317412e+00 -1.87663183e-01 -2.58141309e-01 -8.60258162e-01 5.95772445e-01 -1.70065475e+00 -2.59798110e-01 -2.41935313e-01 1.91261804e+00 8.61574888e-01 1.56086445e-01 -7.17092305e-02 -5.98912835e-01 8.94317627e-01 4.76171225e-02 2.79299710e-02 -1.18912017e+00 1.37627617e-01 4.38003302e-01 6.77484274e-01 9.97549951e-01 -1.21172845e+00 2.00191021e+00 7.62220955e+00 5.10319471e-01 -8.33788097e-01 7.29270339e-01 2.98879743e-01 9.51357782e-01 -2.62910604e-01 1.95748344e-01 -1.23278069e+00 6.59117009e-03 1.44995761e+00 -3.84065472e-02 -3.29816639e-02 8.36804926e-01 -3.88876647e-01 1.72636315e-01 -1.01238978e+00 5.12900174e-01 1.55602783e-01 -7.62721658e-01 1.41146138e-01 -2.08380923e-01 4.42301273e-01 4.76929098e-01 -4.42276001e-01 5.35602868e-01 1.05911922e+00 -7.47027993e-01 1.64685503e-01 -2.42424563e-01 8.66291702e-01 -6.51995242e-01 8.13444972e-01 5.59863932e-02 -1.52817035e+00 4.24940169e-01 -2.34923467e-01 3.19124945e-02 5.07701635e-01 1.92593291e-01 -3.16726625e-01 9.16286349e-01 6.28141940e-01 7.63100445e-01 -3.26720804e-01 2.12871313e-01 -9.94308233e-01 5.04105926e-01 4.76967450e-03 3.46017241e-01 3.10351521e-01 -3.94193560e-01 -5.92191666e-02 1.80724394e+00 2.22254336e-01 -2.08401680e-03 3.68662745e-01 2.56965399e-01 -1.91424087e-01 3.92210990e-01 -6.94512784e-01 -1.12192176e-01 1.58336774e-01 1.10941458e+00 -8.10261786e-01 -4.90462422e-01 -9.97774601e-01 1.19582665e+00 7.54607141e-01 1.89977825e-01 -9.17819262e-01 -4.08645749e-01 7.42157042e-01 -6.39584586e-02 3.59625310e-01 -5.62157393e-01 -3.69010091e-01 -1.41399872e+00 -3.89856517e-01 -4.44519579e-01 9.41733837e-01 -6.81027830e-01 -1.44609296e+00 9.50538278e-01 2.25892752e-01 -4.65037346e-01 -3.01679671e-01 -9.68748748e-01 -5.16337037e-01 1.05072951e+00 -1.95075607e+00 -1.63965011e+00 3.59140962e-01 6.45528197e-01 5.58848083e-01 8.68400261e-02 1.47575688e+00 2.63560981e-01 -3.90689701e-01 8.28735292e-01 -5.66406250e-01 4.87560451e-01 6.71401501e-01 -1.33056891e+00 7.85117328e-01 9.57670748e-01 2.49650434e-01 5.06498218e-01 4.64187980e-01 -6.53190374e-01 -1.14269090e+00 -1.05185235e+00 1.36825669e+00 -6.62948310e-01 1.11370778e+00 -6.17912531e-01 -1.06216264e+00 1.30043471e+00 7.34473348e-01 1.55809984e-01 7.50625134e-01 6.52655721e-01 -9.50359464e-01 1.97881758e-01 -9.29141939e-01 4.53251719e-01 1.33744824e+00 -8.54675114e-01 -1.18302882e+00 4.66131270e-01 1.02412379e+00 -3.84047776e-01 -1.08375704e+00 2.83525258e-01 2.54736599e-02 -8.86826813e-01 7.78723419e-01 -8.78743827e-01 3.22831035e-01 1.12257667e-01 -2.67987758e-01 -1.50222743e+00 -4.41150293e-02 -4.00714606e-01 3.79364431e-01 1.42711568e+00 7.57469893e-01 -8.98593962e-01 5.79874158e-01 3.89272004e-01 -6.81170821e-01 -2.24474996e-01 -8.11988652e-01 -1.16967022e+00 9.16090965e-01 -4.13511783e-01 2.75715232e-01 1.29459107e+00 3.25805932e-01 9.41952348e-01 1.54992193e-01 3.30692947e-01 4.36581433e-01 7.42491782e-02 4.01866496e-01 -1.03375185e+00 -3.48180830e-01 -1.04503803e-01 -3.08795571e-01 -9.83368218e-01 8.88548553e-01 -1.26011479e+00 9.28025469e-02 -1.65823770e+00 -1.88730329e-01 -4.83839184e-01 -5.30174851e-01 8.00794840e-01 -7.94830620e-02 2.02730656e-01 -4.39597815e-02 -7.20786974e-02 -4.78866309e-01 1.57498375e-01 1.21662652e+00 5.09547174e-01 -7.76666030e-02 -5.99464417e-01 -7.95173109e-01 8.94415677e-01 9.76477981e-01 -7.22295761e-01 -4.78153795e-01 -9.35245991e-01 -1.22994356e-01 1.55208141e-01 -4.20930415e-01 -5.99962056e-01 -1.40003726e-01 -1.14161819e-01 -2.24749416e-01 -1.94272131e-01 2.16082230e-01 -4.79915231e-01 -3.29219699e-01 3.16931158e-01 -9.82265696e-02 3.76191348e-01 5.27100444e-01 1.90919355e-01 -5.71780324e-01 -1.21435352e-01 7.11248457e-01 -4.38773334e-01 -8.66692305e-01 7.80298337e-02 -1.93351075e-01 3.46172690e-01 9.18666124e-01 1.64489880e-01 -4.43534374e-01 5.55927381e-02 -8.47005188e-01 1.67403556e-02 3.74922693e-01 7.08449602e-01 -1.80567950e-01 -9.26306427e-01 -6.17577851e-01 2.32925832e-01 1.65073544e-01 -5.90555191e-01 -2.13567451e-01 4.99866009e-01 -2.61249632e-01 7.28397787e-01 -2.00280204e-01 -2.51821041e-01 -1.08652937e+00 5.80192208e-01 3.40607345e-01 -4.41099077e-01 -5.41736245e-01 1.07956290e+00 4.14355069e-01 -9.45642352e-01 -1.90255210e-01 -1.43891945e-01 -1.92795634e-01 -1.78496003e-01 1.62562281e-01 -4.20553714e-01 2.03741491e-01 -8.92075121e-01 -5.91739237e-01 1.04539657e+00 -5.28083295e-02 -1.94890499e-02 1.08034706e+00 -6.05415329e-02 -4.63998497e-01 4.70258266e-01 1.22568798e+00 9.97455642e-02 -9.46161211e-01 1.29575029e-01 5.06566703e-01 -6.67873845e-02 -1.58467293e-01 -8.69524002e-01 -1.04101753e+00 1.11631465e+00 1.49663135e-01 2.22826928e-01 8.18744779e-01 6.39040351e-01 7.35275447e-01 1.98254213e-01 7.70960629e-01 -1.02076828e+00 -2.32128292e-01 8.72619927e-01 6.52446330e-01 -9.88474786e-01 -1.49895653e-01 -1.16684186e+00 -6.78257287e-01 8.41576457e-01 8.38377774e-01 -4.77967769e-01 8.44285548e-01 4.52838123e-01 5.68085730e-01 -2.96684951e-01 -5.34671307e-01 -5.20848513e-01 3.71533185e-02 8.72918308e-01 1.24279046e+00 3.11235338e-01 -6.84797347e-01 6.41822100e-01 -3.66725385e-01 -3.67152125e-01 1.35685131e-01 1.06732965e+00 -3.23497415e-01 -1.70751512e+00 -4.88740169e-02 -4.91401434e-01 -9.11356449e-01 -4.05317664e-01 -3.48447770e-01 1.38162112e+00 3.44163664e-02 8.78626108e-01 1.08106911e-01 -2.06031978e-01 5.04146218e-01 5.15941799e-01 8.68389428e-01 -1.09977591e+00 -4.10064518e-01 5.28393760e-02 8.17425787e-01 -6.35247529e-01 -6.83184683e-01 -2.80222446e-01 -1.54738152e+00 9.95691866e-02 -2.65695155e-01 4.88654166e-01 1.03986740e+00 1.19489121e+00 2.68704563e-01 4.52617079e-01 7.99931064e-02 -6.10189140e-01 -2.31631193e-02 -8.24856222e-01 -3.78914028e-01 2.76122928e-01 -1.83478042e-01 -3.32189858e-01 -3.21200252e-01 3.29906493e-01]	[10.475801467895508, 9.76611042022705]
7df5667c-031e-466a-98a7-c6f0b623b83a	assessment-of-algorithms-for-mitosis	1411.5825	null	http://arxiv.org/abs/1411.5825v1	http://arxiv.org/pdf/1411.5825v1.pdf	Assessment of algorithms for mitosis detection in breast cancer histopathology images	The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers. However, mitosis counting is laborious, subjective and may suffer from low inter-observer agreement. With the wider acceptance of whole slide images in pathology labs, automatic image analysis has been proposed as a potential solution for these issues. In this paper, the results from the Assessment of Mitosis Detection Algorithms 2013 (AMIDA13) challenge are described. The challenge was based on a data set consisting of 12 training and 11 testing subjects, with more than one thousand annotated mitotic figures by multiple observers. Short descriptions and results from the evaluation of eleven methods are presented. The top performing method has an error rate that is comparable to the inter-observer agreement among pathologists.	['Josien P. W. Pluim', 'Max A. Viergever', 'Ching-Wei Wang', 'Thomas Walter', 'Jürgen Schmidhuber', 'Dan C. Cireşan', 'Anders B. L. Larsen', 'Angel Cruz-Roa', 'Stefan M. Willems', 'Teofilo E. de Campos', 'Paul J. van Diest', 'Mitko Veta', 'Miangela M. Lacle', 'Anant Madabhushi', 'Satoshi Kondo', 'Nasir M. Rajpoot', 'Josef Kittler', 'Adnan M. Khan', 'Luca M. Gambardella', 'Jacob S. Vestergaard', 'Fabio Gonzalez', 'Evdokia Arkoumani', 'Bogdan J. Matuszewski', 'Violet Snell', 'Haibo Wang', 'Frederic Precioso', 'F. Boray Tek', 'Anders B. Dahl', 'Alessandro Giusti']	2014-11-21	null	null	null	null	['mitosis-detection']	['medical']	[ 5.08399010e-02 1.25438988e-01 -4.36597943e-01 -6.33492395e-02 -1.16840458e+00 -6.16213143e-01 3.79718363e-01 9.78211701e-01 -7.01776326e-01 8.84213984e-01 1.92269180e-02 -2.83891886e-01 2.71535188e-01 -4.03168976e-01 -5.82018755e-02 -1.15911937e+00 9.77306161e-04 9.96835172e-01 4.67455328e-01 3.54553938e-01 2.87030131e-01 5.38386047e-01 -1.07477677e+00 2.74059802e-01 4.70743597e-01 6.72942638e-01 -1.85549542e-01 1.09605825e+00 -7.68942758e-02 5.88382423e-01 -5.57991624e-01 -4.26010489e-01 -2.43773967e-01 -3.11703026e-01 -8.50819826e-01 2.26296678e-01 2.13716805e-01 -2.03937829e-01 2.40189984e-01 8.18997025e-01 6.75187826e-01 -5.69442987e-01 9.84563947e-01 -1.03713131e+00 1.46255895e-01 3.66122425e-01 -9.27051306e-01 6.43862069e-01 -4.43174429e-02 2.35780597e-01 6.75866604e-01 -6.99596643e-01 9.58677590e-01 5.32877147e-01 8.17554057e-01 5.28542221e-01 -1.55552983e+00 -5.20203888e-01 -8.35463941e-01 2.25004360e-01 -1.55775392e+00 -2.56017208e-01 -2.23672092e-02 -5.90781212e-01 8.50445628e-01 2.89240867e-01 9.40230668e-01 3.18644285e-01 5.35282731e-01 5.63652337e-01 1.19356048e+00 -5.15737712e-01 4.79910105e-01 5.13001561e-01 1.67832792e-01 7.07006633e-01 7.53874183e-01 -2.76259184e-01 -1.92063764e-01 -2.65481263e-01 4.61760074e-01 -3.07000637e-01 -2.09735990e-01 -2.25364253e-01 -1.13115907e+00 6.61656439e-01 1.47433117e-01 7.19201386e-01 1.16529375e-01 -1.68320864e-01 7.18214750e-01 -1.65362254e-01 2.68883109e-01 2.96961337e-01 1.83433499e-02 -1.04271509e-01 -1.15205324e+00 -1.72336221e-01 7.46009171e-01 2.79068381e-01 2.85862982e-01 -5.23330867e-01 -2.79880669e-02 5.06504655e-01 4.05847341e-01 3.22265893e-01 7.00901151e-01 -6.92289174e-01 -3.59427422e-01 9.48452055e-01 -1.74009465e-02 -8.32474768e-01 -7.47489035e-01 -3.96050751e-01 -1.19164658e+00 5.65500975e-01 1.04096818e+00 3.80927145e-01 -1.06411231e+00 1.01484072e+00 3.11881304e-01 -2.65215188e-01 -2.29701638e-01 7.65533090e-01 7.74389446e-01 2.57310629e-01 4.29381967e-01 -4.39899296e-01 1.59305060e+00 -8.09270680e-01 -7.50295281e-01 2.89895907e-02 9.14518833e-01 -7.88967788e-01 7.89714336e-01 4.40150082e-01 -1.09519601e+00 6.00064080e-03 -1.22849512e+00 -4.46230434e-02 -4.99072075e-01 3.71059000e-01 4.02586371e-01 7.91902721e-01 -1.29194880e+00 4.64398190e-02 -1.12452412e+00 -8.77651632e-01 5.89638233e-01 5.86038232e-01 -7.38089800e-01 1.90553933e-01 -3.23622972e-01 1.03153729e+00 3.10763419e-01 -5.70523441e-02 -4.98634607e-01 -7.30960369e-01 -2.83692271e-01 -3.28986794e-01 -2.83994168e-01 -4.67401743e-01 1.31382859e+00 -4.81540829e-01 -1.06990933e+00 1.75931573e+00 -3.57961237e-01 -2.84561306e-01 5.09042561e-01 7.68111825e-01 -1.28808409e-01 4.90513623e-01 4.37478013e-02 7.44357824e-01 6.44688532e-02 -9.88949776e-01 -9.33994591e-01 -2.63848662e-01 -6.53645396e-01 -1.23770274e-01 -1.69542193e-01 -1.08264297e-01 -4.17865604e-01 -2.02928662e-01 -4.64398451e-02 -7.29006469e-01 -3.34285557e-01 3.17963600e-01 -4.63006385e-02 -1.04550384e-01 4.07401711e-01 -8.01351190e-01 1.26412296e+00 -2.28653312e+00 -3.17017376e-01 3.64514470e-01 5.32488763e-01 2.36662716e-01 4.59558904e-01 -6.05264492e-02 3.70384715e-02 4.62132722e-01 4.03684378e-02 -3.17815363e-01 -1.29554912e-01 -3.63135971e-02 4.14853901e-01 9.03428495e-01 4.52592894e-02 6.50619209e-01 -9.36783373e-01 -1.05096996e+00 1.61033571e-01 3.56325984e-01 -9.05627310e-02 -6.06595613e-02 2.79527962e-01 2.23371118e-01 1.29959762e-01 1.04812312e+00 5.60171425e-01 -7.73253918e-01 4.16887254e-01 -2.13762850e-01 2.45118961e-01 -2.26747289e-01 -7.99390912e-01 9.04793501e-01 2.43860945e-01 8.39485288e-01 1.22131698e-01 -2.99120277e-01 4.58622664e-01 5.72134912e-01 4.03700352e-01 -3.29936624e-01 4.19181198e-01 6.01773679e-01 1.97944596e-01 -2.75941730e-01 7.40523487e-02 -4.35156435e-01 2.71302670e-01 3.70588064e-01 -3.30370218e-02 -2.61888981e-01 8.51964891e-01 1.26369357e-01 1.38573778e+00 -7.90343165e-01 1.05655122e+00 -3.16276968e-01 6.85429573e-01 3.01776707e-01 5.40618718e-01 1.78762034e-01 -8.89661014e-01 6.58882320e-01 7.84642220e-01 -5.03024340e-01 -1.12647653e+00 -9.87497330e-01 -3.68617505e-01 2.78116286e-01 -1.20668545e-01 -3.14936370e-01 -7.11693347e-01 -5.31128287e-01 -1.08380757e-01 2.01449078e-02 -1.08008504e+00 2.76408374e-01 -9.50431600e-02 -1.00770140e+00 6.70190096e-01 4.91243333e-01 2.80190676e-01 -7.87419379e-01 -6.98558509e-01 5.34489006e-02 -2.35069439e-01 -9.32818234e-01 -1.24027915e-01 2.89606720e-01 -9.67669964e-01 -1.48167264e+00 -1.03436768e+00 -9.68015969e-01 1.28036249e+00 -3.32137905e-02 1.04949415e+00 5.50595343e-01 -9.29830909e-01 6.41168132e-02 -8.49268287e-02 -5.79275668e-01 -7.29308605e-01 2.49365419e-01 -3.80164683e-01 -4.02309835e-01 7.18496263e-01 -3.84066179e-02 -7.54831851e-01 3.98407489e-01 -8.51941109e-01 7.82500356e-02 9.90333259e-01 8.72735262e-01 1.10440588e+00 -7.40183368e-02 1.66018829e-01 -9.30121362e-01 -1.39335012e-02 -1.31547898e-01 -5.10426462e-01 1.40379652e-01 -7.06945240e-01 -5.06561637e-01 2.29592249e-01 -9.65292081e-02 -6.31039798e-01 3.86866219e-02 1.10583000e-01 2.67654181e-01 -2.50086784e-01 3.88440609e-01 3.22930664e-01 -3.67674381e-01 7.27794170e-01 -3.16413820e-01 3.75607044e-01 2.22696006e-01 -5.73034227e-01 4.37463611e-01 6.00611746e-01 2.81960398e-01 4.81090307e-01 6.49335980e-01 3.80388230e-01 -7.70583928e-01 -5.59270680e-01 -1.03985107e+00 -2.64241844e-01 -4.88699347e-01 7.78899848e-01 -6.40341282e-01 -4.96272266e-01 6.26782596e-01 -7.38673389e-01 -5.54605722e-01 -2.79676039e-02 5.61075032e-01 -3.35393488e-01 2.60350198e-01 -1.01089132e+00 -4.21289384e-01 -6.23182416e-01 -1.05091858e+00 1.05257142e+00 6.35893941e-01 -8.07146311e-01 -1.22396815e+00 5.08379936e-01 5.28971314e-01 4.39728230e-01 4.96479839e-01 1.00701880e+00 -5.85469186e-01 -1.42570093e-01 -7.23420203e-01 -1.68710187e-01 -2.58689374e-01 1.53952718e-01 7.02113092e-01 -9.15613532e-01 -3.22848350e-01 -4.01051193e-01 -2.25351587e-01 6.77683830e-01 5.74352682e-01 8.15753341e-01 1.01918533e-01 -8.60014975e-01 2.09645554e-01 1.66561508e+00 -2.71949284e-02 8.34668517e-01 6.24466598e-01 -1.56763628e-01 4.90013301e-01 6.26714349e-01 1.97491050e-01 1.07976152e-02 2.92581860e-02 3.19352627e-01 -4.05064762e-01 -1.58327490e-01 2.47611910e-01 -1.52568519e-01 5.81484914e-01 -1.72646418e-01 -2.45953098e-01 -1.31239927e+00 7.58800924e-01 -1.16587520e+00 -7.64160454e-01 -3.80220920e-01 1.91015136e+00 9.81564045e-01 2.03966990e-01 3.62358153e-01 6.80109262e-01 7.42509484e-01 -4.99810964e-01 -1.53516844e-01 -2.54511982e-01 -8.29360485e-02 1.90044612e-01 5.52616954e-01 3.95952821e-01 -9.96039510e-01 2.70775020e-01 7.65382862e+00 8.15468550e-01 -1.10272038e+00 1.93488821e-02 1.24866080e+00 3.36119868e-02 2.20060468e-01 -2.19045296e-01 -8.20605099e-01 3.12008560e-01 8.21328640e-01 -4.18961018e-01 -2.93777406e-01 4.17784333e-01 1.19243555e-01 -9.54430640e-01 -9.90423024e-01 7.23960638e-01 1.06676951e-01 -1.40822518e+00 -3.27490032e-01 4.06021208e-01 5.46643496e-01 -3.06033731e-01 -6.47338852e-03 2.48101130e-02 4.72640768e-02 -1.10366476e+00 1.73971280e-02 2.72982419e-01 1.02223849e+00 -4.27028120e-01 1.59758461e+00 2.17659429e-01 -9.49614286e-01 4.32795495e-01 2.42332630e-02 3.08277816e-01 -5.35904951e-02 6.51171267e-01 -1.60419488e+00 -8.10089782e-02 5.84465563e-01 3.66868198e-01 -9.85063076e-01 1.57305229e+00 1.13436114e-02 7.12068021e-01 -4.46535319e-01 -3.31950068e-01 -9.91686061e-02 2.85366386e-01 1.05095267e-01 1.35394216e+00 1.97597146e-01 2.64066476e-02 -2.67738432e-01 7.47679397e-02 2.07318991e-01 3.85080308e-01 -3.87821011e-02 -2.46663526e-01 2.81334221e-01 1.91057920e+00 -1.71438920e+00 -3.22939724e-01 -2.47933224e-01 3.04079354e-01 5.46256676e-02 -7.86334649e-02 -6.52881980e-01 -2.15981916e-01 -2.10590005e-01 4.03822243e-01 -8.76270458e-02 3.86224985e-01 -5.85586548e-01 -3.04519117e-01 -3.81914556e-01 -7.23992765e-01 7.61998177e-01 -5.28780878e-01 -1.04740083e+00 1.77073389e-01 -3.63494545e-01 -1.24632967e+00 -2.04274748e-02 -7.78589785e-01 -6.26024246e-01 5.79593360e-01 -1.32823932e+00 -8.53070259e-01 -6.44531906e-01 -1.36801377e-01 1.32079884e-01 4.76296470e-02 1.09392130e+00 2.46531695e-01 -4.90679115e-01 7.23602831e-01 -3.20540182e-02 7.31268078e-02 9.90859807e-01 -1.64582050e+00 -4.15885657e-01 2.98932523e-01 -6.84655070e-01 2.41590664e-01 8.44090819e-01 -3.43919247e-01 -8.01796317e-01 -8.26120198e-01 1.16955960e+00 -2.98043251e-01 7.10153401e-01 3.34125817e-01 -6.73898280e-01 4.56832707e-01 3.52914125e-01 9.36572105e-02 1.61177778e+00 -3.74431133e-01 1.38492405e-01 4.84342920e-03 -1.46671164e+00 4.77852106e-01 -3.36899189e-03 -7.25991502e-02 6.99732751e-02 2.53579468e-01 -4.03384447e-01 -6.26610994e-01 -1.03579140e+00 4.10212070e-01 7.39890754e-01 -1.08109140e+00 3.36805105e-01 1.12317152e-01 2.43674740e-01 -5.46090901e-01 2.61237949e-01 -8.06527078e-01 -3.71871859e-01 -6.65237829e-02 2.46529028e-01 1.12068450e+00 6.86122298e-01 -3.86169940e-01 1.30153811e+00 3.10237139e-01 1.83681697e-01 -8.02902043e-01 -1.01083338e+00 -2.62747914e-01 -9.84090101e-03 4.38616216e-01 -1.22008786e-01 5.94052553e-01 6.09389424e-01 2.16179773e-01 5.18998802e-01 -1.39023617e-01 6.17646813e-01 -5.14052510e-01 8.48833680e-01 -1.13714278e+00 -1.95582360e-01 -8.99728954e-01 -1.12295461e+00 4.41330299e-02 -2.80530334e-01 -8.21417689e-01 1.07333012e-01 -1.57786500e+00 8.40095401e-01 1.65850017e-02 -1.33127496e-01 4.13607299e-01 -2.19293475e-01 8.78035128e-01 -3.30723852e-01 2.16974929e-01 -6.85506999e-01 -4.75907683e-01 1.13286388e+00 -3.50995332e-01 2.68869042e-01 -2.26888865e-01 -5.39779544e-01 7.90780365e-01 9.21923995e-01 -4.90072578e-01 3.98582220e-02 2.75224388e-01 3.26696634e-01 -1.80470318e-01 1.75900280e-01 -1.21730733e+00 5.57467580e-01 1.95490886e-02 7.54928589e-01 -9.41538393e-01 1.54617667e-01 -6.40794516e-01 4.25022274e-01 9.98866916e-01 -1.71059415e-01 -1.46937624e-01 2.38200337e-01 4.41203207e-01 -3.62381756e-01 -2.44562149e-01 9.94596481e-01 -1.47965610e-01 -2.72162259e-01 8.44346639e-03 -8.31481397e-01 -3.50368947e-01 1.39684021e+00 -6.96512043e-01 -6.15256190e-01 -4.26798053e-02 -7.19843805e-01 4.98454630e-01 8.84083271e-01 -5.91410697e-01 2.03126565e-01 -1.05783057e+00 -6.69691205e-01 -3.00399095e-01 4.19623613e-01 1.54580981e-01 1.75925478e-01 1.53298628e+00 -1.18455493e+00 3.57073128e-01 -2.26050794e-01 -9.49099541e-01 -1.82337880e+00 2.37588257e-01 4.46657240e-01 -1.07850802e+00 -1.07610211e-01 8.25432003e-01 -1.50713682e-01 2.14669377e-01 2.89014816e-01 -2.32627735e-01 -4.21389580e-01 5.50754666e-02 8.58219445e-01 6.49554789e-01 3.48978907e-01 -3.71304899e-01 -4.09445554e-01 4.01479334e-01 -3.89706731e-01 -9.92766097e-02 8.01439643e-01 6.49679974e-02 -4.28611398e-01 6.96938217e-01 9.78065670e-01 -1.19237766e-01 -5.48596263e-01 2.37128824e-01 1.43524706e-01 -2.38548353e-01 -9.08733010e-02 -8.28418672e-01 -8.37399185e-01 7.61520565e-01 8.12697113e-01 2.64172196e-01 1.13991845e+00 -4.76195961e-02 3.69288713e-01 -7.71080628e-02 3.01638603e-01 -1.09611690e+00 1.30397141e-01 1.72900856e-02 3.58938992e-01 -1.39349258e+00 2.24460632e-01 -7.24060059e-01 -1.80748656e-01 1.38029647e+00 5.11819661e-01 1.58366576e-01 5.16559005e-01 6.26627505e-01 3.60299766e-01 -2.02109307e-01 -9.03484404e-01 2.39497483e-01 -1.09492727e-01 5.47873974e-01 8.39699149e-01 3.25171202e-02 -8.43714833e-01 4.56790209e-01 5.70423231e-02 3.70344639e-01 5.39214671e-01 1.02822018e+00 -5.77714264e-01 -7.80728221e-01 -4.43320602e-01 6.46925330e-01 -8.51788163e-01 4.83012617e-01 -5.86256504e-01 1.03257501e+00 -1.03008270e-01 7.34571457e-01 6.40329942e-02 1.16493709e-01 -2.78439410e-02 -2.05824122e-01 5.69713295e-01 -4.27320510e-01 -5.38048744e-01 2.24945903e-01 1.74620170e-02 -1.54910564e-01 -5.89604437e-01 -7.26837754e-01 -1.50453889e+00 -5.99855125e-01 -3.80340755e-01 2.33309895e-01 3.96471262e-01 7.59198189e-01 -1.48266762e-01 4.31446493e-01 2.67689168e-01 -4.38401699e-01 -1.28910735e-01 -9.72023129e-01 -9.40217316e-01 9.28888768e-02 2.78308362e-01 -4.22293663e-01 -8.08419645e-01 6.31703079e-01]	[15.0613374710083, -3.146801710128784]
7f47bfb1-01c0-4c40-b9b8-959fcdf031aa	cmc-v2-towards-more-accurate-covid-19	2211.14557	null	https://arxiv.org/abs/2211.14557v1	https://arxiv.org/pdf/2211.14557v1.pdf	CMC v2: Towards More Accurate COVID-19 Detection with Discriminative Video Priors	This paper presents our solution for the 2nd COVID-19 Competition, occurring in the framework of the AIMIA Workshop at the European Conference on Computer Vision (ECCV 2022). In our approach, we employ the winning solution last year which uses a strong 3D Contrastive Mixup Classifcation network (CMC v1) as the baseline method, composed of contrastive representation learning and mixup classification. In this paper, we propose CMC v2 by introducing natural video priors to COVID-19 diagnosis. Specifcally, we adapt a pre-trained (on video dataset) video transformer backbone to COVID-19 detection. Moreover, advanced training strategies, including hybrid mixup and cutmix, slicelevel augmentation, and small resolution training are also utilized to boost the robustness and the generalization ability of the model. Among 14 participating teams, CMC v2 ranked 1st in the 2nd COVID-19 Competition with an average Macro F1 Score of 89.11%.	['Rui Feng', 'Xiaobo Zhang', 'Yuejie Zhang', 'Yi Wang', 'Nan Zhang', 'Jilan Xu', 'Junlin Hou']	2022-11-26	null	null	null	null	['covid-19-detection']	['medical']	[ 3.49530578e-01 1.45694882e-01 -1.25616238e-01 7.34652132e-02 -7.89565384e-01 -5.07191539e-01 8.46849620e-01 -3.80236618e-02 -6.01933420e-01 4.00637180e-01 1.29478812e-01 1.09461211e-01 2.14865282e-01 -2.73349583e-01 -8.00859332e-01 -4.13164735e-01 2.16426551e-01 3.02199066e-01 4.77825284e-01 -1.35736421e-01 8.85421932e-02 5.18082559e-01 -1.53127754e+00 6.42551839e-01 6.54321849e-01 1.09890997e+00 2.76186198e-01 7.46089041e-01 2.54237115e-01 7.04476058e-01 -5.94718874e-01 -4.86713737e-01 3.36227506e-01 -2.79770136e-01 -6.60204351e-01 -1.79040506e-02 9.67119932e-01 -2.19477177e-01 -2.50199616e-01 8.57116401e-01 2.53137916e-01 6.55500516e-02 8.82586360e-01 -1.29306936e+00 -2.72563323e-02 7.32930243e-01 -8.45657170e-01 5.22672296e-01 2.05072686e-01 1.60788000e-01 7.98327446e-01 -1.07806349e+00 1.06123388e+00 9.32505071e-01 7.79902816e-01 5.77949405e-01 -1.14442229e+00 -5.97303987e-01 3.89662743e-01 5.50693035e-01 -1.29509199e+00 -2.17491984e-01 7.07452893e-01 -8.54783177e-01 8.92953336e-01 1.33324713e-01 7.29017198e-01 1.51549053e+00 3.08735073e-02 1.15966499e+00 1.01790380e+00 -4.71453905e-01 4.05266769e-02 1.48106664e-01 2.11436778e-01 6.16691530e-01 1.37717754e-01 1.60306841e-01 -1.25249907e-01 2.39027500e-01 5.75994492e-01 -3.21699470e-01 -4.08045977e-01 -5.87670684e-01 -1.06764960e+00 6.01933777e-01 4.60529655e-01 2.78790683e-01 -3.57915252e-01 3.80763561e-02 6.70051336e-01 -7.25545585e-02 2.98328221e-01 3.77030998e-01 -2.47427151e-01 1.87548459e-01 -1.28917062e+00 4.31789249e-01 2.41685361e-01 6.40839994e-01 2.21010938e-01 6.83269575e-02 -3.79051805e-01 8.69209766e-01 2.99570292e-01 2.93853670e-01 4.47131842e-01 -9.95127022e-01 5.11842012e-01 2.68262118e-01 -8.39285702e-02 -8.62633705e-01 -6.41848624e-01 -6.69614613e-01 -8.09920490e-01 4.34444696e-01 2.55888492e-01 -2.20351055e-01 -1.23025870e+00 1.59682119e+00 -2.92176250e-02 4.60502803e-01 -3.26877199e-02 1.00509179e+00 1.23947215e+00 4.93398458e-01 -2.87382342e-02 -1.59663737e-01 1.12883043e+00 -1.29733443e+00 -3.86923432e-01 -5.49920686e-02 3.93053949e-01 -7.20442832e-01 6.28439844e-01 7.58350849e-01 -1.24309802e+00 -8.55134428e-01 -1.43372536e+00 2.25040242e-01 -3.22870076e-01 2.22580373e-01 1.30311370e-01 5.81827581e-01 -1.05339396e+00 2.47904718e-01 -7.39230752e-01 -1.78895250e-01 2.76431590e-01 3.84928770e-02 -3.49520355e-01 -4.25789565e-01 -9.02533054e-01 8.60139370e-01 4.38401312e-01 8.59577432e-02 -1.29944396e+00 -8.68834972e-01 -6.58726335e-01 -3.14293861e-01 5.41051507e-01 -6.53062403e-01 8.01195323e-01 -8.66768420e-01 -1.07535863e+00 1.18435490e+00 4.34291184e-01 -6.52643800e-01 1.04007757e+00 -2.45488614e-01 -3.76822978e-01 4.12609935e-01 2.67629158e-02 1.08137918e+00 1.02634752e+00 -1.37634850e+00 -6.52919173e-01 -4.20340225e-02 1.14177153e-01 6.46276176e-02 1.94689974e-01 -3.43904719e-02 -9.20980155e-01 -7.80668437e-01 -7.13925287e-02 -1.02274752e+00 -1.07837245e-01 -2.34233633e-01 -2.50571668e-01 -4.02507409e-02 8.29283297e-01 -8.09479833e-01 9.10941303e-01 -2.24949503e+00 4.66077000e-01 2.15534702e-01 3.59463602e-01 4.95641947e-01 -3.17368448e-01 1.18050743e-02 -3.65799397e-01 -9.36428085e-02 -3.45865279e-01 -6.18863523e-01 -1.96675628e-01 -4.91790958e-02 5.37679568e-02 4.64697331e-01 3.07250530e-01 5.88360310e-01 -7.33121812e-01 -5.03399670e-01 4.99550700e-01 4.91144478e-01 -7.34967053e-01 9.68186036e-02 -2.72834033e-01 2.39080161e-01 1.08383060e-01 4.99591023e-01 1.01070774e+00 -7.73168653e-02 1.20103240e-01 -4.94112641e-01 -1.39480919e-01 -4.25561041e-01 -1.33338833e+00 1.67853916e+00 -3.65190804e-01 6.78708375e-01 3.84333879e-01 -1.23087585e+00 5.64082026e-01 2.15611622e-01 6.60828710e-01 -4.51682597e-01 2.02377662e-01 1.62517875e-01 -2.48087138e-01 -5.18176615e-01 5.52137315e-01 3.07289273e-01 2.05653280e-01 -1.71998888e-01 3.72875750e-01 -1.84678406e-01 6.31758988e-01 3.08971941e-01 8.70086968e-01 3.91995877e-01 2.98671257e-02 -1.62801117e-01 8.15769434e-01 -5.58707863e-02 5.37890494e-01 7.70488799e-01 -3.65506679e-01 1.26390100e+00 4.89287525e-01 -1.66553423e-01 -8.28343630e-01 -1.03805447e+00 -1.60206452e-01 6.67350173e-01 2.55751777e-02 -5.13068914e-01 -7.97661185e-01 -1.06072819e+00 -4.35024440e-01 4.50763315e-01 -7.54078269e-01 7.56383687e-02 -8.31574619e-01 -6.32090211e-01 6.01653457e-01 6.81089044e-01 5.87866127e-01 -9.50073481e-01 -5.13347268e-01 1.13696158e-01 -4.65393633e-01 -1.53448761e+00 -3.28065246e-01 2.75709122e-01 -4.53899771e-01 -1.19322932e+00 -1.06953871e+00 -8.13874066e-01 2.13640690e-01 1.00461461e-01 9.59486187e-01 2.29421235e-03 -5.14084816e-01 3.50883722e-01 -5.45882940e-01 -1.69740677e-01 -2.78072387e-01 9.28448960e-02 -1.79883525e-01 5.33280037e-02 -2.15601653e-01 -4.88285953e-03 -4.37398553e-01 1.93382457e-01 -8.99710774e-01 1.73034579e-01 5.58587611e-01 8.21341515e-01 5.19980073e-01 -2.99682498e-01 2.89755106e-01 -7.14815497e-01 1.11044258e-01 -2.88762301e-01 -8.02612007e-01 1.59560755e-01 -5.53270936e-01 -4.39453721e-01 3.62727553e-01 -2.57476062e-01 -9.71481025e-01 1.52811751e-01 -4.91181135e-01 -8.51689696e-01 -1.79184660e-01 3.56588989e-01 -9.08365920e-02 1.94106484e-03 6.32580519e-01 2.26350389e-02 -1.67473570e-01 -2.73104578e-01 4.16181237e-01 3.77551883e-01 8.92283082e-01 -2.35469550e-01 6.01017952e-01 4.18406129e-01 -1.56432018e-02 -8.77243519e-01 -7.48661399e-01 -5.11027336e-01 -5.49954355e-01 -4.47928518e-01 1.38667941e+00 -1.22780955e+00 -2.46777639e-01 6.71050131e-01 -1.10867190e+00 -3.10046166e-01 -8.27342868e-02 7.36409128e-01 -4.89923924e-01 4.66756701e-01 -5.44810534e-01 -4.28470343e-01 -1.58790141e-01 -1.48349154e+00 9.25646782e-01 6.07515946e-02 -5.44763431e-02 -7.82259345e-01 7.71873966e-02 8.32845807e-01 2.72482306e-01 5.54238558e-01 5.64044535e-01 -4.68832880e-01 -3.70340258e-01 -1.36087993e-02 -4.51556742e-01 7.78651536e-01 -4.99472052e-01 2.16961399e-01 -1.20651317e+00 -1.89565152e-01 -4.77577239e-01 -3.15134346e-01 1.37845027e+00 7.98625052e-01 1.08968437e+00 3.91706705e-01 -2.52619177e-01 8.31631362e-01 1.41520202e+00 2.50801258e-02 6.03401482e-01 3.92044157e-01 8.36616278e-01 5.05729198e-01 5.33956707e-01 1.81662500e-01 2.39588186e-01 1.02344692e+00 7.74970174e-01 -1.38092905e-01 -6.72180772e-01 9.21498463e-02 4.96551901e-01 3.79650682e-01 -4.27865744e-01 -2.09414229e-01 -8.80948126e-01 4.69482958e-01 -1.63070321e+00 -9.41720784e-01 -3.82866353e-01 1.89667475e+00 2.52750486e-01 4.20413882e-01 4.10874695e-01 1.42650217e-01 7.13763475e-01 2.24776983e-01 -5.37598245e-02 -2.16473877e-01 -2.98039079e-01 1.30043373e-01 2.92934299e-01 4.05673295e-01 -1.52110565e+00 7.51716793e-01 5.85324383e+00 7.92635798e-01 -1.24843717e+00 1.51096925e-01 4.99745458e-01 -1.16375439e-01 1.20830029e-01 -4.83543545e-01 -8.41334522e-01 4.38675612e-01 7.19542325e-01 3.98048997e-01 8.12535062e-02 6.68106854e-01 -9.62823182e-02 1.04725771e-01 -8.84986401e-01 1.05587494e+00 5.80217779e-01 -1.52412772e+00 -2.01849535e-01 -1.77070469e-01 9.64808702e-01 4.52539355e-01 1.50022492e-01 6.55802488e-01 -1.40222892e-01 -8.39348793e-01 9.73937094e-01 4.15622830e-01 7.36201048e-01 -6.83302402e-01 9.80810165e-01 3.17628193e-03 -1.22091734e+00 -8.36720690e-02 -5.44474944e-02 5.13252437e-01 2.67583162e-01 4.00248319e-01 -6.74714804e-01 9.29158211e-01 8.37260962e-01 8.30616593e-01 -6.98657811e-01 1.27956009e+00 -2.66431272e-01 4.92056340e-01 -2.17227429e-01 4.57977682e-01 2.37242684e-01 5.68116903e-02 7.81177759e-01 1.61290526e+00 9.85474661e-02 -3.40656459e-01 3.53060514e-01 3.59452248e-01 -2.39278704e-01 -6.12376593e-02 -3.38280678e-01 3.67877424e-01 -3.54171321e-02 1.41634607e+00 -7.50726283e-01 -4.79136437e-01 -3.56683433e-01 9.07434464e-01 -5.23994565e-02 2.32658312e-01 -1.08604419e+00 1.04311414e-01 2.29153246e-01 9.30370465e-02 7.92490423e-01 9.84104872e-02 -3.74992588e-03 -1.21598268e+00 4.59027439e-02 -8.90005887e-01 5.15323937e-01 -7.95570135e-01 -1.15575838e+00 8.49114776e-01 4.10391539e-01 -1.23094904e+00 -3.05241615e-01 -7.85708308e-01 -5.04388213e-01 4.11775798e-01 -1.58976567e+00 -1.40367770e+00 -5.25125742e-01 5.68776786e-01 6.91902518e-01 -2.61435062e-01 5.07457376e-01 3.99660021e-01 -5.77134550e-01 7.30582893e-01 -1.14821255e-01 1.06634032e-02 6.91631675e-01 -1.11968422e+00 5.92929870e-02 1.02309620e+00 5.94209395e-02 4.96031158e-02 5.37338555e-01 -5.09136200e-01 -9.37523186e-01 -1.32045996e+00 4.66955066e-01 -2.26312131e-01 5.76736927e-01 -3.47777277e-01 -6.68743253e-01 5.44823229e-01 5.02403855e-01 3.55238199e-01 2.83454120e-01 -1.65070832e-01 -4.46391255e-01 1.24600902e-02 -1.20829761e+00 3.83940965e-01 8.67199898e-01 -1.88967109e-01 -5.90945303e-01 1.45986810e-01 6.85041428e-01 -5.60569465e-01 -7.49782920e-01 6.66956544e-01 4.38183099e-01 -1.01227999e+00 1.15623713e+00 -2.39728421e-01 5.60651064e-01 -3.46202582e-01 -4.00477082e-01 -1.14996421e+00 -2.03516647e-01 -2.27290198e-01 -8.99356827e-02 1.10133243e+00 3.57338041e-01 4.92825285e-02 7.98316717e-01 -1.74392551e-01 -4.02829111e-01 -6.00048542e-01 -7.63324320e-01 -7.35366642e-01 3.82887833e-02 -5.97229481e-01 -9.16625783e-02 7.75594294e-01 -5.17455280e-01 2.48374388e-01 -4.16511625e-01 3.72658446e-02 7.12141454e-01 -1.86027944e-01 6.91478312e-01 -1.10274708e+00 -6.24356627e-01 -7.30371475e-01 -6.66014194e-01 -7.14850545e-01 -1.08166657e-01 -9.59895492e-01 -7.49342293e-02 -1.38413894e+00 1.92094371e-01 -1.64196789e-02 -4.48974848e-01 1.05044611e-01 -1.48373395e-01 7.06035137e-01 7.07104087e-01 -8.66138339e-02 -4.84987706e-01 1.78734347e-01 1.05528450e+00 -4.02087927e-01 -6.32551759e-02 -1.18912905e-01 -3.48555297e-01 7.59707034e-01 4.91924852e-01 -6.92824498e-02 -4.50227946e-01 -2.85873741e-01 -7.27824345e-02 -3.87495384e-02 5.15194952e-01 -1.21291995e+00 -1.10240258e-01 1.86538920e-01 5.34721911e-01 -9.04565036e-01 5.73190033e-01 -6.27798259e-01 3.82021070e-02 5.13974190e-01 -2.15925574e-01 1.09289987e-02 3.00291002e-01 3.24843526e-01 -2.65833199e-01 -3.99430156e-01 1.08872950e+00 -3.71468104e-02 -9.38539386e-01 1.93392798e-01 -4.93392467e-01 2.33406544e-01 1.24439728e+00 -2.26235911e-02 -4.00195420e-01 7.99849704e-02 -1.07238102e+00 1.43155813e-01 2.41621509e-01 4.41121399e-01 7.37258434e-01 -8.85167718e-01 -1.05685151e+00 2.12877676e-01 3.21363688e-01 -7.57669881e-02 6.47155464e-01 1.16387141e+00 -7.06957459e-01 1.92504659e-01 -3.89056355e-01 -8.69508862e-01 -1.39188695e+00 6.12264931e-01 3.70232850e-01 -5.89294612e-01 -8.80137980e-01 1.07597399e+00 2.82358557e-01 -2.03056604e-01 4.26159471e-01 -2.45685846e-01 -6.69948459e-01 3.49218696e-01 6.11140728e-01 3.59967798e-01 3.13326061e-01 -5.57352602e-01 -6.21550441e-01 6.83852196e-01 -3.90391320e-01 -3.31033766e-01 1.28869295e+00 1.00614905e-01 3.44080001e-01 1.35276452e-01 1.24129319e+00 -1.05483256e-01 -1.29558086e+00 1.27530396e-01 -1.45945922e-01 -1.75799459e-01 2.94624746e-01 -8.72084498e-01 -1.38779497e+00 7.68255532e-01 9.92608607e-01 -1.11729175e-01 1.15683424e+00 -2.90602650e-02 3.85026902e-01 -1.70977116e-01 5.68859628e-04 -1.09239268e+00 1.08304597e-01 3.31968188e-01 1.05082810e+00 -1.17485011e+00 2.42561065e-02 -4.61274773e-01 -8.37816119e-01 1.08101630e+00 7.48450637e-01 -4.68711525e-01 6.16658747e-01 3.12975824e-01 6.58269152e-02 -1.44185927e-02 -7.03094840e-01 -1.99381739e-01 4.88601387e-01 9.01917994e-01 2.86983192e-01 -8.32190961e-02 -4.16252673e-01 4.56061929e-01 1.29655793e-01 -3.76624838e-02 6.88074410e-01 5.54855168e-01 -1.33368690e-02 -7.81217694e-01 -3.46442312e-01 1.80495217e-01 -4.71906960e-01 1.48087565e-03 -2.49995604e-01 9.96843755e-01 6.09914124e-01 8.31396878e-01 1.81724578e-02 -5.46849310e-01 3.50637794e-01 -2.97486752e-01 7.43664145e-01 -3.72719646e-01 -7.74670660e-01 2.69931525e-01 1.81846142e-01 -6.69169724e-01 -5.23478091e-01 -8.52963746e-01 -1.05300915e+00 1.38939247e-01 -1.36187738e-02 -1.86204970e-01 8.69844258e-01 8.51496994e-01 -8.39573219e-02 9.44562376e-01 3.71096104e-01 -1.01034105e+00 -2.15719864e-01 -9.21417475e-01 -3.64071310e-01 2.85263866e-01 3.84395868e-01 -9.34892416e-01 -1.26135349e-01 1.90568507e-01]	[8.872897148132324, -0.11668851226568222]
497e28e0-4a6c-48ab-be93-15178d98fed4	can-we-find-neurons-that-cause-unrealistic	2201.06346	null	https://arxiv.org/abs/2201.06346v4	https://arxiv.org/pdf/2201.06346v4.pdf	Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks?	Even though Generative Adversarial Networks (GANs) have shown a remarkable ability to generate high-quality images, GANs do not always guarantee the generation of photorealistic images. Occasionally, they generate images that have defective or unnatural objects, which are referred to as 'artifacts'. Research to investigate why these artifacts emerge and how they can be detected and removed has yet to be sufficiently carried out. To analyze this, we first hypothesize that rarely activated neurons and frequently activated neurons have different purposes and responsibilities for the progress of generating images. In this study, by analyzing the statistics and the roles for those neurons, we empirically show that rarely activated neurons are related to the failure results of making diverse objects and inducing artifacts. In addition, we suggest a correction method, called 'Sequential Ablation', to repair the defective part of the generated images without high computational cost and manual efforts.	['Jaesik Choi', 'Wonjoon Chang', 'Hwanil Choi']	2022-01-17	null	null	null	null	['gan-image-forensics']	['computer-vision']	[ 4.29815680e-01 2.67362535e-01 4.15161252e-01 -1.02227367e-01 -3.25689644e-01 -6.91799164e-01 6.74875557e-01 -4.34127420e-01 7.39713311e-02 9.68792200e-01 6.03311732e-02 -6.02603145e-02 2.19189048e-01 -8.39481831e-01 -8.81059766e-01 -9.00924087e-01 4.56766307e-01 -7.68977106e-02 -1.02075502e-01 -8.79790355e-03 3.08076710e-01 4.44976419e-01 -1.58095169e+00 1.72987789e-01 1.12657964e+00 4.47095305e-01 1.79834723e-01 4.89237964e-01 -1.71197206e-01 7.76865542e-01 -1.24471867e+00 -4.47530001e-01 3.84687275e-01 -1.06090879e+00 -4.41472948e-01 1.69165567e-01 2.42514372e-01 -4.88578379e-01 1.23102285e-01 1.14692819e+00 4.49535251e-01 -2.88995653e-01 8.03291857e-01 -1.32218623e+00 -9.77965474e-01 4.63593721e-01 -5.56066692e-01 -1.54718524e-02 3.72183293e-01 4.75951135e-01 4.17122096e-01 -6.02803349e-01 7.01629817e-01 1.05559087e+00 3.44395161e-01 9.41918731e-01 -1.28441536e+00 -7.03061819e-01 -3.39513391e-01 -1.98857248e-01 -1.26918101e+00 -4.45763439e-01 8.22680593e-01 -4.88774121e-01 3.10119450e-01 5.07546723e-01 7.61705935e-01 1.48369563e+00 3.37402374e-01 5.88175774e-01 1.22679675e+00 -4.48441476e-01 1.92584142e-01 2.54184514e-01 -3.77907604e-01 4.89493817e-01 7.19809532e-01 1.67439595e-01 -2.43865415e-01 1.13153882e-01 9.94670153e-01 -2.13936955e-01 -5.00955999e-01 -1.01634108e-01 -9.40187573e-01 5.92503548e-01 2.12812066e-01 5.19343853e-01 -6.52032435e-01 2.68027425e-01 -3.92972864e-02 1.17224574e-01 3.07485968e-01 8.91672134e-01 -1.08539253e-01 -1.25681579e-01 -7.55536199e-01 6.37169257e-02 4.24518853e-01 7.43700445e-01 6.92706525e-01 5.40039003e-01 -2.48405889e-01 6.24738574e-01 -8.72821212e-02 2.41654634e-01 4.49468225e-01 -1.06118619e+00 9.67685357e-02 9.29954052e-01 2.47659996e-01 -9.62681532e-01 1.22536793e-01 -3.41513991e-01 -8.86209846e-01 5.79926074e-01 4.58525300e-01 -3.89441431e-01 -1.06821799e+00 1.74084342e+00 -1.01746228e-02 1.03527769e-01 8.46197009e-02 7.70538509e-01 6.10006690e-01 5.92081428e-01 1.88873317e-02 -1.65245757e-01 9.82692599e-01 -7.25274444e-01 -8.87030721e-01 -6.66025952e-02 3.97863895e-01 -7.26788342e-01 1.37003565e+00 3.22233289e-01 -1.17964017e+00 -5.06119132e-01 -1.06350553e+00 2.52974093e-01 -2.85316139e-01 1.15835905e-01 6.19324386e-01 9.68844891e-01 -9.80872989e-01 5.25370002e-01 -5.78797400e-01 -1.82213664e-01 6.71806693e-01 -9.23245307e-03 -1.85410306e-01 2.26101220e-01 -7.40459144e-01 8.30503345e-01 9.55649018e-02 1.28290564e-01 -1.18623006e+00 -7.54794478e-01 -4.42081004e-01 2.30768938e-02 1.51074320e-01 -8.00381482e-01 7.12512314e-01 -1.53180754e+00 -1.36603975e+00 7.75969923e-01 2.24988498e-02 -2.88259596e-01 6.41722262e-01 -1.81297839e-01 -2.89755255e-01 -1.01864479e-01 -3.06992773e-02 7.20143914e-01 9.75845993e-01 -1.87561941e+00 -3.07882696e-01 -1.48930594e-01 4.64443490e-02 -5.78616112e-02 -2.10757762e-01 2.14234404e-02 -2.18100753e-02 -8.70432615e-01 2.58387048e-02 -8.94789517e-01 -1.45849407e-01 -1.67958155e-01 -6.72979534e-01 4.44191247e-02 7.40999460e-01 -5.78311145e-01 8.86836708e-01 -2.45905662e+00 -7.79961720e-02 5.74966185e-02 2.62683183e-01 3.67244989e-01 -1.84867248e-01 2.55427301e-01 -1.00897094e-02 7.19069481e-01 -2.81375855e-01 -1.36788294e-01 -3.26642036e-01 1.74524426e-01 -3.81496876e-01 2.37498954e-01 3.45345348e-01 9.17365730e-01 -7.91519582e-01 -2.51196504e-01 9.86547843e-02 5.56727290e-01 -3.01582932e-01 1.99045464e-01 -6.83097914e-02 7.03008890e-01 -3.34144980e-01 7.71279037e-01 7.23076820e-01 -2.16333531e-02 -1.36991620e-01 -3.69571075e-02 -6.76139083e-04 -1.46340057e-01 -6.34568214e-01 1.20729482e+00 -1.32072359e-01 9.73915815e-01 -9.90013257e-02 -7.18030393e-01 8.91596794e-01 2.86027670e-01 9.70007107e-02 -7.43452728e-01 2.43387312e-01 3.12172979e-01 1.71175167e-01 -5.22443533e-01 4.50788915e-01 -1.45742476e-01 2.47273862e-01 4.83569175e-01 -2.74002403e-01 -2.83422381e-01 1.63318098e-01 5.63680567e-02 1.15185297e+00 9.71073136e-02 -1.29878772e-02 -2.22904291e-02 2.51671553e-01 -6.75481791e-03 6.01270676e-01 8.15318882e-01 6.66265655e-03 9.38906252e-01 6.74650550e-01 -3.02643567e-01 -1.28822315e+00 -1.06687188e+00 3.12664270e-01 3.32483798e-01 1.60202906e-01 -1.20582525e-03 -1.10827160e+00 -5.41400135e-01 -2.63019979e-01 9.83929157e-01 -7.21018255e-01 -4.07315522e-01 -3.77189755e-01 -6.03057027e-01 7.47762680e-01 3.37025106e-01 4.83823717e-01 -1.47892380e+00 -8.52614403e-01 1.99805927e-02 -6.65505901e-02 -8.11669111e-01 -1.95870191e-01 -1.78880379e-01 -7.44253516e-01 -1.10885572e+00 -8.63921165e-01 -3.95034462e-01 1.32647705e+00 3.22107673e-01 1.08992267e+00 4.83690232e-01 -3.04517835e-01 -3.03153135e-02 -4.76072401e-01 -6.43617272e-01 -8.30850780e-01 -3.15230161e-01 -2.90371552e-02 1.19946497e-02 -1.01809338e-01 -7.31625378e-01 -6.20276451e-01 4.50809807e-01 -1.21172631e+00 1.85530335e-01 7.98708439e-01 6.14362180e-01 3.49979460e-01 3.52104902e-01 4.29883182e-01 -8.91734600e-01 1.00829732e+00 -2.11381137e-01 -4.40879315e-01 2.06593692e-01 -5.48395038e-01 1.71204389e-03 7.50601590e-01 -5.28901935e-01 -1.11840272e+00 -1.21766992e-01 1.32553250e-01 -5.20640731e-01 -4.57666934e-01 2.23062299e-02 -1.07898682e-01 -7.12504387e-02 8.02563727e-01 4.18871492e-01 5.04199229e-02 -2.65423357e-01 6.92193583e-02 2.82853782e-01 3.76383066e-01 -4.38033462e-01 1.09720993e+00 5.93549967e-01 -1.45319209e-01 -6.09650493e-01 -5.53516984e-01 3.05205435e-01 -1.02162153e-01 -4.57876503e-01 8.92329037e-01 -6.14959180e-01 -3.78022343e-01 6.67347312e-01 -1.11374903e+00 -3.46289247e-01 -5.34994900e-01 9.77753401e-02 -4.07685548e-01 2.07418859e-01 -3.80283475e-01 -9.61644351e-01 -1.70624673e-01 -1.07798159e+00 7.53275931e-01 5.54602683e-01 -3.01261485e-01 -4.22989309e-01 -1.55515745e-01 4.00866032e-01 5.27238548e-01 4.52861756e-01 1.02192223e+00 -9.85326692e-02 -7.76124418e-01 -1.25704616e-01 -1.51998207e-01 5.59307516e-01 3.89141917e-01 3.30531150e-01 -8.29972744e-01 -6.26939312e-02 8.51976648e-02 -9.54715908e-02 5.60285449e-01 4.62858498e-01 1.19406486e+00 -4.25106764e-01 -1.75306588e-01 5.36970675e-01 1.36935711e+00 7.10192144e-01 1.31496072e+00 2.21935630e-01 5.35762310e-01 7.69908905e-01 4.20301467e-01 1.43649131e-01 -3.15599918e-01 3.13875556e-01 4.73156542e-01 -2.68204302e-01 -2.40981519e-01 -4.90162253e-01 4.30247396e-01 3.69468212e-01 -4.52673972e-01 -6.07966483e-01 -5.84527194e-01 4.72639471e-01 -1.34389961e+00 -9.73495901e-01 -2.83925474e-01 1.90487432e+00 5.97416520e-01 1.68170765e-01 -1.39746189e-01 2.55335748e-01 9.05054331e-01 -7.10257962e-02 -3.89347851e-01 -4.33728904e-01 -3.03899705e-01 6.77541569e-02 3.23525965e-01 -9.02517810e-02 -4.69083309e-01 8.43093932e-01 7.14208174e+00 6.22333765e-01 -1.20233762e+00 -7.70820826e-02 8.36247981e-01 -1.35680307e-02 -7.65401661e-01 1.17244199e-01 -3.11083019e-01 7.50651836e-01 5.39443135e-01 6.48298338e-02 5.06759107e-01 6.32912934e-01 3.88379812e-01 -2.77578503e-01 -6.54237866e-01 7.97907829e-01 1.85106814e-01 -1.11864841e+00 2.80207634e-01 2.58311301e-01 8.37880254e-01 -7.54522204e-01 1.12833403e-01 -2.19723396e-02 3.84729296e-01 -1.17426336e+00 9.33616400e-01 6.88828647e-01 6.55438364e-01 -7.38944113e-01 6.67459011e-01 2.05686808e-01 -3.89728278e-01 9.45443846e-03 -3.77887666e-01 2.08755955e-02 1.50850698e-01 7.47174084e-01 -7.03717530e-01 2.53147691e-01 6.04836047e-01 9.38205421e-02 -7.52064645e-01 8.38897884e-01 -6.36220813e-01 7.21688271e-01 -6.82314020e-03 4.25731391e-02 -7.90211558e-02 -3.59350055e-01 7.03214884e-01 4.65929389e-01 7.49160409e-01 -4.50056158e-02 -7.38870203e-01 1.55999112e+00 4.97609675e-02 -1.77801564e-01 -8.39542091e-01 -4.41810638e-01 3.23137522e-01 1.05641484e+00 -9.41622615e-01 -8.84685218e-02 -6.30379794e-03 1.21465123e+00 -1.59128413e-01 4.37573403e-01 -1.03485203e+00 -1.29693627e-01 5.17757714e-01 2.36704543e-01 -1.95074994e-02 -3.14123333e-02 -6.14188552e-01 -8.86336088e-01 1.46063790e-01 -9.49159443e-01 -3.48670930e-01 -1.19974101e+00 -1.11333108e+00 4.94689256e-01 -3.68757784e-01 -1.04530156e+00 -1.02624848e-01 -2.21076772e-01 -8.11393201e-01 6.53554738e-01 -9.35390294e-01 -9.39145029e-01 -5.63150167e-01 3.21125448e-01 4.99062210e-01 -2.48671338e-01 6.89781249e-01 1.43392950e-01 -7.30362773e-01 4.86340404e-01 -1.78054512e-01 6.16439953e-02 4.47920233e-01 -1.03592253e+00 2.99537480e-01 1.00057220e+00 1.14186503e-01 5.14677405e-01 9.05676305e-01 -7.43336022e-01 -1.13876224e+00 -8.19035172e-01 6.20607972e-01 -3.47805887e-01 -4.95069660e-02 -2.65541494e-01 -8.19575965e-01 3.83614570e-01 3.05249602e-01 -4.52755928e-01 4.42540348e-01 -2.02598482e-01 2.89084334e-02 -1.49139212e-02 -1.23419249e+00 9.90904570e-01 1.01621151e+00 -1.76729515e-01 -3.77470434e-01 -1.71216391e-02 5.16807795e-01 -3.42289284e-02 -3.92259508e-01 4.41413969e-01 4.14251566e-01 -1.33452356e+00 8.85682702e-01 -2.57805377e-01 9.42735553e-01 -2.60433733e-01 3.03932607e-01 -1.36415744e+00 -1.86873838e-01 -5.38605809e-01 2.54400641e-01 1.52664769e+00 5.83653986e-01 -5.40386081e-01 9.17642236e-01 5.84611773e-01 -1.23981930e-01 -4.79462177e-01 -6.10916018e-01 -8.55684400e-01 -1.93482041e-01 -2.64876429e-02 7.29149163e-01 1.09928417e+00 -5.43359280e-01 -1.89427249e-02 -4.92775440e-01 -2.30820645e-02 4.06794131e-01 -1.11342534e-01 8.29234540e-01 -9.99927223e-01 8.37218016e-02 -6.11113489e-01 -4.12597984e-01 -3.33619833e-01 4.23170207e-03 -2.85557210e-01 1.58229396e-01 -1.40315390e+00 2.21007466e-01 -4.78533089e-01 -3.01676840e-02 3.98384273e-01 -2.82009661e-01 4.42068428e-01 1.28833964e-01 3.33213061e-01 -1.77201536e-02 3.85371715e-01 1.58288896e+00 9.93427914e-03 -1.91852033e-01 -2.00497136e-01 -9.54008996e-01 5.92004836e-01 1.01424932e+00 -5.18677175e-01 -5.30074537e-01 -4.27619427e-01 3.88084799e-01 -2.67319884e-02 4.84635323e-01 -1.13440788e+00 -3.09576660e-01 -2.82546133e-01 4.36985284e-01 -3.34486812e-01 1.68483436e-01 -7.48797715e-01 7.74173439e-01 4.55996096e-01 -1.21328495e-01 4.68223616e-02 5.07507659e-02 3.69154900e-01 -2.19294026e-01 -5.50658405e-01 9.06921744e-01 -3.75893444e-01 -2.95599878e-01 -2.04986230e-01 -6.99341953e-01 -2.20375642e-01 1.40572476e+00 -5.33267379e-01 -2.40616307e-01 -5.60079217e-01 -3.00343513e-01 -2.64784694e-01 9.33783174e-01 3.98522645e-01 6.71624064e-01 -1.14413047e+00 -6.58528447e-01 1.73050463e-01 -2.65271634e-01 -6.39790446e-02 3.70986253e-01 4.79691923e-01 -7.65752614e-01 8.25153887e-02 -4.19716209e-01 -2.50985205e-01 -1.03970182e+00 5.15532255e-01 2.67460287e-01 -1.63939856e-02 -5.18121839e-01 8.98227513e-01 3.31533045e-01 1.14904288e-02 -6.65814057e-02 -7.49032423e-02 -1.57145426e-01 -1.21097481e-02 2.26561010e-01 3.41500610e-01 -1.62973180e-01 -3.08047086e-01 -1.20805367e-03 1.55137792e-01 1.89811170e-01 6.40855581e-02 1.12853122e+00 -4.95345518e-03 -2.04154328e-01 1.63251355e-01 5.42885184e-01 1.80599213e-01 -1.21806872e+00 7.21813202e-01 -3.84593189e-01 -7.38281786e-01 -3.07513773e-01 -8.42365563e-01 -1.50953817e+00 6.54974580e-01 5.27943194e-01 4.66855615e-01 1.21133971e+00 -1.88008443e-01 7.57935941e-01 -2.61076480e-01 3.18214804e-01 -8.98724496e-01 2.98513710e-01 -2.49337293e-02 1.00319445e+00 -8.76681089e-01 -2.59159029e-01 -6.09169364e-01 -6.88681483e-01 5.91440320e-01 8.26126099e-01 -8.20678473e-02 -6.04791157e-02 3.40634614e-01 2.25801229e-01 -9.27569568e-02 -5.41286469e-01 3.04020289e-02 -1.28007233e-01 8.27544391e-01 3.41731697e-01 8.14108700e-02 -6.76069438e-01 3.64335686e-01 -4.11824316e-01 1.15919784e-02 8.34944546e-01 7.61575222e-01 -1.27574757e-01 -1.10421669e+00 -5.28912485e-01 4.63419527e-01 -6.03116751e-01 5.07643074e-02 -7.64956236e-01 6.47479415e-01 4.68332857e-01 8.90569925e-01 -2.97591612e-02 -4.95797664e-01 1.27514243e-01 7.19357729e-02 5.24350822e-01 -4.51124936e-01 -5.25670648e-01 -2.21333206e-01 3.60926874e-02 -2.98046142e-01 -5.21536350e-01 -3.50604355e-01 -9.29300487e-01 -3.40994716e-01 -4.34929103e-01 -2.21467260e-02 6.99055672e-01 8.71397197e-01 3.51424009e-01 7.26916790e-01 5.41024387e-01 -4.91409630e-01 -2.68030345e-01 -8.85155082e-01 -5.92790902e-01 7.38524616e-01 -3.16938572e-02 -4.67213303e-01 -6.98375106e-01 2.15632454e-01]	[11.656780242919922, -0.44420403242111206]
b0fc09b5-4e81-4523-8328-fd97a9e1f3d3	rtmdet-an-empirical-study-of-designing-real	2212.07784	null	https://arxiv.org/abs/2212.07784v2	https://arxiv.org/pdf/2212.07784v2.pdf	RTMDet: An Empirical Study of Designing Real-Time Object Detectors	In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO series and is easily extensible for many object recognition tasks such as instance segmentation and rotated object detection. To obtain a more efficient model architecture, we explore an architecture that has compatible capacities in the backbone and neck, constructed by a basic building block that consists of large-kernel depth-wise convolutions. We further introduce soft labels when calculating matching costs in the dynamic label assignment to improve accuracy. Together with better training techniques, the resulting object detector, named RTMDet, achieves 52.8% AP on COCO with 300+ FPS on an NVIDIA 3090 GPU, outperforming the current mainstream industrial detectors. RTMDet achieves the best parameter-accuracy trade-off with tiny/small/medium/large/extra-large model sizes for various application scenarios, and obtains new state-of-the-art performance on real-time instance segmentation and rotated object detection. We hope the experimental results can provide new insights into designing versatile real-time object detectors for many object recognition tasks. Code and models are released at https://github.com/open-mmlab/mmdetection/tree/3.x/configs/rtmdet.	['Kai Chen', 'Shilong Zhang', 'Yanyi Liu', 'Yudong Wang', 'Yue Zhou', 'Haian Huang', 'Wenwei Zhang', 'Chengqi Lyu']	2022-12-14	null	null	null	null	['real-time-instance-segmentation', 'object-detection-in-aerial-images', 'real-time-object-detection']	['computer-vision', 'computer-vision', 'computer-vision']	[-1.43851802e-01 -4.94951427e-01 -2.80326217e-01 -3.71500641e-01 -5.88053226e-01 -4.47922111e-01 4.25320715e-02 -1.77702636e-01 -5.42379439e-01 -5.16989492e-02 -8.96874011e-01 -4.57531303e-01 4.15347874e-01 -5.29570222e-01 -8.24926198e-01 -6.56063080e-01 -6.73900619e-02 3.68852496e-01 9.27189112e-01 8.67502689e-02 1.09606683e-01 6.87328279e-01 -1.69217300e+00 4.14295614e-01 5.54473877e-01 1.46802664e+00 4.95283842e-01 1.10178435e+00 2.74738699e-01 7.81805456e-01 -5.14871836e-01 -4.06002492e-01 4.67645675e-01 1.81936488e-01 -6.22569382e-01 1.33569404e-01 6.78660154e-01 -5.30181885e-01 -3.28681022e-01 9.17404413e-01 6.88785136e-01 -2.77537614e-01 3.35235804e-01 -1.43036926e+00 -3.75928044e-01 5.26452601e-01 -9.47605014e-01 7.30441928e-01 -1.71494126e-01 4.53788877e-01 6.67587757e-01 -9.05170619e-01 2.21286520e-01 1.31975210e+00 5.67462504e-01 5.08452296e-01 -9.40930009e-01 -8.80085289e-01 3.48761231e-01 2.88005143e-01 -1.41195869e+00 -2.91099042e-01 1.65256962e-01 -2.81927973e-01 1.09229851e+00 2.86579221e-01 4.82080489e-01 9.18580651e-01 2.16950521e-01 1.20304668e+00 6.95817292e-01 -2.44670600e-01 -1.02438843e-02 1.07305318e-01 5.07321775e-01 8.47143292e-01 4.27738756e-01 -5.54925352e-02 -3.11614394e-01 3.18142660e-02 1.00074995e+00 4.65747528e-02 2.52615362e-02 -2.49682873e-01 -1.13841164e+00 7.11441457e-01 7.06370533e-01 8.34273696e-02 6.05724864e-02 5.72480381e-01 7.44468153e-01 6.22272864e-02 2.07424879e-01 2.25473478e-01 -7.51484454e-01 -7.50571713e-02 -7.08468080e-01 1.77891701e-01 6.27448022e-01 1.35993552e+00 4.20890272e-01 2.06661806e-01 -1.08234130e-01 6.88516915e-01 3.75555128e-01 6.72128737e-01 3.19887251e-01 -1.17173409e+00 4.54931796e-01 4.66619730e-01 7.11737946e-02 -5.54553270e-01 -7.51110673e-01 -7.44828939e-01 -5.64763129e-01 2.47087955e-01 5.23925364e-01 -6.60633072e-02 -1.11038685e+00 1.11262739e+00 6.78833127e-01 3.94638121e-01 -3.37895840e-01 1.18487871e+00 1.05124497e+00 5.66690505e-01 2.36537054e-01 3.35572481e-01 1.98429787e+00 -1.41065919e+00 -1.07212968e-01 -4.63035196e-01 9.25944865e-01 -8.86042893e-01 9.60704803e-01 4.92128998e-01 -9.21884477e-01 -9.33972418e-01 -1.25192165e+00 -2.83006161e-01 -1.10392973e-01 6.01490796e-01 1.04293370e+00 9.25346673e-01 -7.26577759e-01 3.77105951e-01 -1.28942621e+00 -2.07353771e-01 6.83625102e-01 5.84554613e-01 2.74675459e-01 -1.96250565e-02 -5.77960134e-01 4.09418851e-01 4.82999325e-01 1.82923481e-01 -8.57530236e-01 -7.62655318e-01 -5.49521446e-01 5.27523495e-02 5.92323542e-01 -6.78720355e-01 1.64834237e+00 -8.93140674e-01 -1.36048162e+00 1.06612015e+00 9.83048826e-02 -6.53199911e-01 6.56224608e-01 -3.39692950e-01 -4.32092011e-01 8.72133225e-02 1.05428353e-01 8.98362994e-01 1.05529308e+00 -8.56972873e-01 -1.20692766e+00 -3.61541510e-01 -9.85746831e-03 -4.25862074e-02 -2.58141398e-01 3.90740544e-01 -1.06050646e+00 -4.35060441e-01 6.67949170e-02 -1.09709454e+00 -2.96207517e-01 2.07041800e-01 -3.98982674e-01 -3.06762099e-01 1.01940513e+00 -1.09674826e-01 1.02216840e+00 -2.11082196e+00 -4.58918214e-01 -2.05522642e-01 3.39301109e-01 7.21201003e-01 -2.87994910e-02 -2.30728015e-01 9.64746848e-02 -2.59650469e-01 2.04411626e-01 -4.02032673e-01 -5.74193709e-02 -6.14168830e-02 -1.88662440e-01 6.17252111e-01 1.99970350e-01 1.05232847e+00 -7.01120973e-01 -5.33816814e-01 4.56844598e-01 4.12550360e-01 -4.80789065e-01 3.95810828e-02 -7.04579130e-02 1.90299630e-01 -6.82470262e-01 1.06999183e+00 9.00090873e-01 -5.11927068e-01 -1.13990769e-01 -9.50446352e-02 -2.23512903e-01 7.39019439e-02 -1.44127440e+00 1.39654350e+00 -1.52029887e-01 8.34779084e-01 3.08067679e-01 -8.07450533e-01 7.35096812e-01 -1.27779245e-01 3.56238663e-01 -8.03191364e-01 5.80483258e-01 2.70896375e-01 1.13183446e-02 -3.26951057e-01 6.83440328e-01 6.93243682e-01 1.26299728e-02 -1.63146295e-02 -1.01840369e-01 1.75199941e-01 4.34511334e-01 1.62204623e-01 1.02573252e+00 3.21926810e-02 -3.15268189e-02 -3.57344776e-01 2.50280619e-01 1.11747906e-01 4.59343970e-01 1.06735766e+00 -5.14227986e-01 5.49850225e-01 3.89859587e-01 -5.38023293e-01 -9.87855256e-01 -9.12934542e-01 -7.41740942e-01 1.57492614e+00 3.95424783e-01 -2.26110414e-01 -8.10126841e-01 -4.19935465e-01 1.74010247e-01 2.75370747e-01 -2.49516219e-01 1.12831041e-01 -7.89090037e-01 -1.20515442e+00 7.57346869e-01 1.04050183e+00 7.03999102e-01 -1.03020501e+00 -9.39708114e-01 3.68159443e-01 2.71796644e-01 -1.46250856e+00 -3.87370139e-01 4.29834127e-01 -9.50523317e-01 -9.76849437e-01 -5.01081824e-01 -1.03522575e+00 4.95036453e-01 6.55687094e-01 1.08885288e+00 7.23047601e-03 -8.42726529e-01 6.34717345e-02 -2.89860994e-01 -4.98828739e-01 -4.73987311e-02 3.71781170e-01 2.69782934e-02 -2.44560257e-01 2.93547034e-01 -4.27680500e-02 -9.41891074e-01 6.91841662e-01 -7.88268805e-01 1.23377115e-01 3.81137699e-01 5.82975030e-01 5.91194332e-01 -3.80050004e-01 2.76520610e-01 -7.66500354e-01 -7.23610669e-02 -2.00967327e-01 -1.24731219e+00 -7.98658729e-02 -4.43481326e-01 -2.48072743e-01 4.54529881e-01 -7.40735054e-01 -9.04951453e-01 2.50214785e-01 -4.04338807e-01 -5.31817913e-01 -1.35929763e-01 -2.43068397e-01 9.91249382e-02 -2.54500687e-01 7.20581532e-01 -7.62088597e-02 -5.26677907e-01 -5.49106359e-01 3.58678430e-01 8.31897676e-01 5.91832936e-01 -5.77869475e-01 3.39594752e-01 6.38998687e-01 -2.10584283e-01 -7.37517715e-01 -8.07718098e-01 -9.58372593e-01 -5.16415000e-01 -9.79232043e-02 8.32455754e-01 -1.28394532e+00 -1.19496763e+00 9.45468605e-01 -1.06482339e+00 -6.43262029e-01 -1.34550840e-01 3.57969195e-01 -3.52632880e-01 1.77850388e-02 -1.17553639e+00 -5.94716907e-01 -5.19557953e-01 -1.43119597e+00 1.43598175e+00 5.16263306e-01 3.82660508e-01 -4.89967436e-01 -5.76403499e-01 4.23432112e-01 2.69839644e-01 -1.62279636e-01 1.89772114e-01 -4.35820818e-01 -9.50984657e-01 -1.83764696e-01 -7.74787664e-01 4.96847630e-01 -4.22230065e-01 2.12851763e-01 -1.06595087e+00 -5.49797356e-01 -1.38069496e-01 -4.11195040e-01 1.16479671e+00 6.02251232e-01 1.57365358e+00 2.51974583e-01 -7.36901939e-01 9.83688235e-01 1.33513880e+00 1.42789066e-01 4.81346875e-01 5.09080350e-01 1.05806327e+00 -8.07947069e-02 7.94426978e-01 5.38081050e-01 4.02964324e-01 7.67485261e-01 5.49308598e-01 -2.92756349e-01 -1.77767962e-01 3.99137616e-01 3.09459597e-01 6.09742701e-01 1.07468152e-02 -3.92132223e-01 -9.56527472e-01 3.14557761e-01 -1.92536271e+00 -6.21143758e-01 -6.25573277e-01 1.96108902e+00 3.73557270e-01 6.53100729e-01 2.99464852e-01 -4.24395278e-02 7.77542651e-01 -6.18031360e-02 -8.32726657e-01 -3.83244783e-01 1.81281239e-01 1.56234711e-01 1.05349231e+00 1.21134356e-01 -1.58922851e+00 1.22083127e+00 5.92454624e+00 1.21384394e+00 -1.31563962e+00 3.26955467e-01 8.57706010e-01 -2.39718601e-01 8.65828335e-01 -3.38568449e-01 -1.69715750e+00 4.27681953e-01 9.38701868e-01 3.19930613e-01 1.88746839e-03 1.48273110e+00 7.11228400e-02 -1.37893394e-01 -1.04880548e+00 9.69363928e-01 -2.90668279e-01 -1.35091245e+00 -4.06172276e-01 -1.09443121e-01 6.25151038e-01 6.44451916e-01 1.62491694e-01 4.29641366e-01 1.45394206e-01 -6.69580758e-01 9.18821990e-01 -2.18708381e-01 7.50740469e-01 -5.63418984e-01 5.92342138e-01 2.82727808e-01 -1.61512768e+00 -1.61114022e-01 -6.63951218e-01 -1.13375997e-02 -5.69991693e-02 4.51865524e-01 -7.44371176e-01 2.32881382e-01 1.10597956e+00 5.29296756e-01 -7.69575119e-01 1.34427941e+00 5.26152924e-02 7.08990991e-01 -6.35750830e-01 -5.22000194e-02 3.10748905e-01 2.06845567e-01 2.53751844e-01 1.60884702e+00 1.69633459e-02 1.40880737e-02 4.79116410e-01 6.14286065e-01 -1.35283783e-01 -1.04893789e-01 7.32598081e-02 3.77151847e-01 4.91147071e-01 1.63547468e+00 -1.34157681e+00 -5.84946990e-01 -4.74360466e-01 8.85896206e-01 3.28094125e-01 4.17348221e-02 -1.51194465e+00 -2.42188320e-01 7.91676939e-01 1.01583526e-01 7.47855246e-01 -3.50281477e-01 -3.11908513e-01 -1.13592339e+00 2.58053448e-02 -7.07698703e-01 4.17642355e-01 -4.56130803e-01 -1.02245641e+00 6.32896364e-01 -1.96155593e-01 -1.12464976e+00 2.26175711e-01 -1.30883050e+00 -4.11093831e-01 2.72170454e-01 -1.47291279e+00 -1.11186659e+00 -4.74799067e-01 2.40529492e-01 7.67246306e-01 1.93727508e-01 3.90606821e-01 6.97143793e-01 -1.04496861e+00 8.90110433e-01 2.10006416e-01 3.71184289e-01 5.08565128e-01 -1.06634855e+00 9.09867764e-01 7.33777046e-01 1.07069738e-01 1.59699783e-01 3.98322225e-01 -2.88155973e-01 -1.58342433e+00 -1.33967090e+00 -1.12672197e-02 -4.51772392e-01 7.30670452e-01 -5.96165001e-01 -7.95498729e-01 8.37345421e-01 -2.88298070e-01 7.13132143e-01 2.06313744e-01 -1.27990454e-01 -3.74674767e-01 -2.23042071e-01 -9.33652401e-01 4.31700170e-01 1.26461363e+00 3.18387225e-02 5.50043695e-02 5.96607566e-01 8.76152515e-01 -9.01750326e-01 -8.27016056e-01 4.35858518e-01 6.42733812e-01 -8.62206578e-01 1.14652979e+00 -3.76972616e-01 -6.34358823e-02 -3.76477271e-01 -1.18865594e-02 -4.13212985e-01 -5.08736849e-01 -3.89677435e-01 -3.67761016e-01 1.06309640e+00 2.85133868e-01 -7.71108210e-01 1.09397721e+00 3.17295104e-01 -3.78453344e-01 -9.10540938e-01 -1.05955076e+00 -1.08885038e+00 -1.97155118e-01 -9.27939594e-01 2.34095797e-01 5.20954967e-01 -6.01535797e-01 1.83248803e-01 -1.08559966e-01 4.19452608e-01 7.01762378e-01 2.66492546e-01 8.39572549e-01 -8.89932811e-01 -3.92270416e-01 -5.93163669e-01 -6.44546986e-01 -1.61427307e+00 -3.12857538e-01 -6.91523731e-01 -1.01814352e-01 -9.90586638e-01 1.79591060e-01 -7.67412186e-01 -2.63745934e-01 5.12815833e-01 -1.73040524e-01 8.09665442e-01 4.33356911e-01 2.20914125e-01 -1.11329067e+00 1.92271218e-01 1.20514560e+00 6.74339160e-02 -2.02772915e-01 1.83655381e-01 -3.66652668e-01 9.34297800e-01 6.80716932e-01 -6.70928836e-01 1.55530766e-01 -5.83976209e-01 -3.59513521e-01 -2.63418645e-01 4.68905360e-01 -1.47889960e+00 1.97240070e-01 6.53560981e-02 5.42973936e-01 -7.90777206e-01 4.59643483e-01 -5.55718422e-01 -2.26513565e-01 7.90961921e-01 1.15405269e-01 4.96249162e-02 4.64930058e-01 1.86601311e-01 1.22576840e-01 -1.00445621e-01 1.12581539e+00 2.52447072e-02 -1.19501185e+00 4.56062615e-01 -1.82169363e-01 1.10150399e-02 1.31233096e+00 -3.00396115e-01 -6.72005355e-01 4.61391628e-01 -5.44624507e-01 6.57024384e-01 2.45678023e-01 6.59393907e-01 2.70206451e-01 -1.10620427e+00 -6.54185832e-01 9.30303112e-02 2.19549805e-01 1.90977320e-01 2.59670228e-01 8.82652164e-01 -1.01456511e+00 6.50254488e-01 -1.38941154e-01 -1.10322821e+00 -1.39237320e+00 5.36413193e-01 4.01978612e-01 -2.05219686e-01 -8.61013353e-01 1.19711864e+00 3.37910146e-01 -1.02152400e-01 3.80291790e-01 -5.89101791e-01 2.91480213e-01 -1.29121646e-01 6.64928794e-01 6.81487918e-01 3.24904323e-01 -4.65703160e-01 -5.16850352e-01 3.90287638e-01 -3.99609566e-01 5.01193166e-01 9.55324471e-01 6.37556389e-02 2.93383718e-01 1.77856207e-01 1.00189066e+00 -5.35736918e-01 -1.60583174e+00 -1.03010297e-01 -8.33265949e-03 -4.61080790e-01 2.19807059e-01 -4.18944508e-01 -1.31578922e+00 6.58048987e-01 1.09421647e+00 2.68232614e-01 9.81527746e-01 3.72509450e-01 9.82360721e-01 3.98559868e-01 4.56959933e-01 -1.03560770e+00 1.78211600e-01 5.79536378e-01 3.34567875e-01 -1.53112960e+00 1.35548756e-01 -8.69381309e-01 -3.69522542e-01 1.09765506e+00 1.17573845e+00 -4.25596684e-01 4.70692545e-01 6.92494571e-01 1.08091310e-01 -2.31786102e-01 -6.21333003e-01 -4.93563026e-01 2.74364740e-01 3.09831440e-01 3.87417912e-01 4.09693986e-01 -6.40380234e-02 4.32480842e-01 -6.45407662e-03 -1.99287951e-01 2.85615534e-01 9.38403726e-01 -6.16599500e-01 -9.10922885e-01 -4.93702650e-01 5.66789985e-01 -5.87318003e-01 4.81463075e-02 2.47392908e-01 8.45471621e-01 3.30208242e-01 7.35629976e-01 4.40207899e-01 -1.89145118e-01 2.78189361e-01 -3.24007750e-01 5.43356597e-01 -5.68458259e-01 -7.69154191e-01 1.47220731e-01 -4.26468924e-02 -8.25295985e-01 -3.42705399e-02 -5.35297692e-01 -1.51599586e+00 -5.03302395e-01 -6.87000930e-01 -4.83375430e-01 8.02501261e-01 7.30812430e-01 4.54631060e-01 7.94808328e-01 2.67838061e-01 -1.36208129e+00 -4.07783806e-01 -8.09458435e-01 -5.30972958e-01 -2.89147645e-02 1.18916847e-01 -6.38191402e-01 3.37063782e-02 -6.39231130e-02]	[8.733859062194824, -0.25068241357803345]
381b52fd-2219-4280-a3c4-59344e139846	learning-discriminative-illumination-and	null	null	http://openaccess.thecvf.com/content_cvpr_2013/html/Liu_Learning_Discriminative_Illumination_2013_CVPR_paper.html	http://openaccess.thecvf.com/content_cvpr_2013/papers/Liu_Learning_Discriminative_Illumination_2013_CVPR_paper.pdf	Learning Discriminative Illumination and Filters for Raw Material Classification with Optimal Projections of Bidirectional Texture Functions	We present a computational imaging method for raw material classification using features of Bidirectional Texture Functions (BTF). Texture is an intrinsic feature for many materials, such as wood, fabric, and granite. At appropriate scales, even "uniform" materials will also exhibit texture features that can be helpful for recognition, such as paper, metal, and ceramic. To cope with the high-dimensionality of BTFs, in this paper, we proposed to learn discriminative illumination patterns and texture filters, with which we can directly measure optimal projections of BTFs for classification. We also studied the effects of texture rotation and scale variation for material classification. We built an LED-based multispectral dome, with which we have acquired a BTF database of a variety of materials and demonstrated the effectiveness of the proposed approach for material classification.	['Chao Liu', 'Geifei Yang', 'Jinwei Gu']	2013-06-01	null	null	null	cvpr-2013-6	['material-classification']	['computer-vision']	[ 4.38167512e-01 -5.64895391e-01 3.30311805e-01 -3.83589298e-01 -2.79784590e-01 -5.47363400e-01 4.54962850e-01 -2.74840385e-01 1.58742025e-01 7.56110549e-01 1.25811279e-01 2.97585521e-02 -6.17597163e-01 -9.83470261e-01 -4.41506773e-01 -1.10082114e+00 1.21908143e-01 2.70880163e-01 2.35348150e-01 -8.37769657e-02 3.71380210e-01 8.41078758e-01 -1.72263694e+00 4.69578445e-01 4.96292353e-01 1.26948607e+00 5.16237497e-01 3.80230010e-01 3.11209075e-03 3.01633775e-01 -3.10946196e-01 -3.17338146e-02 3.54264855e-01 -5.72732352e-02 -6.35281920e-01 5.37610292e-01 3.26419920e-01 -1.91829920e-01 -2.45917931e-01 9.00259435e-01 1.11708619e-01 5.59206717e-02 1.11896837e+00 -6.83474422e-01 -6.55390382e-01 -1.11784656e-02 -5.38980544e-01 -2.14653969e-01 3.54640543e-01 -7.85002336e-02 8.21454227e-01 -1.04780197e+00 6.31041467e-01 1.22529042e+00 2.69155264e-01 2.35855550e-01 -1.13434839e+00 -1.58844918e-01 -3.37330848e-01 4.30098087e-01 -1.15784776e+00 -4.70446050e-01 9.45891380e-01 -4.82517570e-01 3.07517320e-01 5.49386263e-01 7.43925869e-01 1.00127935e+00 4.72263902e-01 5.70244253e-01 1.96028328e+00 -7.20879853e-01 1.00402623e-01 4.53434847e-02 1.43360972e-01 7.57562578e-01 1.03774220e-01 1.82482705e-01 -3.90220582e-01 -9.23649371e-02 8.77913713e-01 -1.77855775e-01 -4.29216951e-01 -2.60003120e-01 -1.21321130e+00 4.95869607e-01 2.12573372e-02 1.34906098e-01 -2.51584440e-01 -2.37267837e-01 3.80765237e-02 3.03804904e-01 5.94368517e-01 1.99219152e-01 -1.44137844e-01 9.24693793e-03 -3.00951093e-01 -2.14101583e-01 7.85207808e-01 5.35481215e-01 8.11288774e-01 -1.24582060e-01 2.59123486e-03 1.35071373e+00 9.42612886e-02 1.19548690e+00 1.71798944e-01 -8.18072438e-01 -4.45879139e-02 2.04431653e-01 2.64587134e-01 -1.16173589e+00 -3.43612194e-01 -6.03471622e-02 -9.73068893e-01 3.24514508e-01 3.21525633e-01 4.59112436e-01 -6.06666803e-01 1.10928273e+00 3.07603002e-01 -2.97629297e-01 -8.15609470e-02 8.84412467e-01 5.52339554e-01 4.09464478e-01 -6.74725652e-01 -1.46397099e-01 1.23760629e+00 -4.98315305e-01 -5.63750207e-01 2.57613063e-01 1.02722179e-02 -1.27306867e+00 1.32573462e+00 6.69941485e-01 -6.71787381e-01 -4.27686453e-01 -7.15108693e-01 4.10453618e-01 -7.63566568e-02 6.27906680e-01 6.92422748e-01 7.04710305e-01 -6.61816597e-01 6.91522896e-01 -7.38810480e-01 -5.78628242e-01 2.08843514e-01 5.21885604e-02 -4.72336888e-01 -2.88540184e-01 -3.65180492e-01 6.35816514e-01 1.35683054e-02 4.31160629e-01 -5.88238120e-01 4.86771241e-02 -2.33365059e-01 -2.03041941e-01 1.78821981e-01 -3.02633345e-01 5.30053318e-01 -8.17299843e-01 -1.78496182e+00 7.73041487e-01 -1.65460989e-01 3.22635800e-01 2.78724730e-01 -2.17645317e-01 -5.94913125e-01 2.86464930e-01 -2.74606831e-02 -3.47218141e-02 1.16150212e+00 -1.31777430e+00 -7.90025517e-02 -2.42131904e-01 -9.47120562e-02 -2.98954770e-02 -4.44634229e-01 -4.77731079e-02 1.07941084e-01 -5.98962009e-01 5.81303179e-01 -1.00886130e+00 3.58670026e-01 8.32511187e-02 -5.35829961e-01 1.75484598e-01 1.10744476e+00 -6.94247007e-01 5.38015246e-01 -2.32672405e+00 4.92858551e-02 5.41681349e-01 -1.20184377e-01 -2.56277144e-01 -1.85871810e-01 3.10540468e-01 2.14075416e-01 -2.83030748e-01 -1.47111073e-01 2.92870253e-01 -2.41742551e-01 3.85368794e-01 -2.75120527e-01 6.03096545e-01 4.26252857e-02 3.75676751e-01 -4.96774822e-01 -2.03232691e-01 3.38169694e-01 1.68519050e-01 -1.93650126e-01 1.80172056e-01 -8.96725431e-02 4.36136156e-01 -5.89999795e-01 1.06648242e+00 7.07936943e-01 -5.34478612e-02 -6.69640377e-02 -7.00702488e-01 -2.58616090e-01 -1.16018154e-01 -1.18880594e+00 1.05963051e+00 -5.42976677e-01 8.21692228e-01 2.96487451e-01 -9.34508264e-01 1.30817711e+00 1.13765866e-01 5.42867601e-01 -6.76193893e-01 -9.80796814e-02 2.80741394e-01 -6.56219423e-02 -6.01681590e-01 4.14682478e-01 1.40672922e-01 3.65783751e-01 3.43156219e-01 -3.55482191e-01 -3.35483134e-01 -1.43197179e-01 -4.94121313e-01 9.39116597e-01 2.26662800e-01 -1.64110377e-01 -7.73058832e-01 5.21541297e-01 -1.53012305e-01 9.88804176e-02 5.82124472e-01 3.68135571e-01 6.00980639e-01 1.02245688e-01 -6.62962496e-01 -1.12997520e+00 -1.29466689e+00 -4.92475569e-01 8.09412539e-01 2.52207130e-01 1.44701719e-01 -4.03684705e-01 -1.06529072e-01 -6.86061662e-03 5.67772463e-02 -3.74653757e-01 7.15270191e-02 -3.93298626e-01 -1.07526338e+00 1.08032644e-01 1.29316032e-01 1.01340628e+00 -8.24633360e-01 -2.52264291e-01 1.22214712e-01 -1.61988705e-01 -1.13007426e+00 -1.23485588e-01 1.33998081e-01 -8.30182433e-01 -1.31105888e+00 -3.94550979e-01 -6.82839513e-01 7.25485921e-01 5.84208667e-01 9.05745149e-01 -1.92778304e-01 -5.44159591e-01 7.35684514e-01 -6.01297438e-01 -8.15537274e-02 -3.47517431e-01 -2.43995160e-01 9.85467955e-02 5.29525876e-01 -1.85759917e-01 -4.91772920e-01 -3.85328710e-01 8.49364519e-01 -7.99810171e-01 2.97310621e-01 6.02535725e-01 1.16639686e+00 6.92087233e-01 3.53675455e-01 2.59435326e-01 -7.09466159e-01 5.50799191e-01 4.15212996e-02 -5.31970680e-01 5.13093233e-01 -2.59347022e-01 -2.13683974e-02 5.05390286e-01 -3.13042134e-01 -1.32453883e+00 -2.72972107e-01 4.22182195e-02 -1.06571265e-01 -2.56919861e-01 3.13560128e-01 -1.25570625e-01 -5.91455758e-01 5.05518258e-01 3.26492965e-01 -2.12473832e-02 -7.02839315e-01 -1.03105150e-01 9.01988685e-01 5.20096540e-01 -1.10962319e+00 7.28341520e-01 7.40755439e-01 3.50011647e-01 -1.52562153e+00 -5.69184542e-01 -2.42826879e-01 -5.17419577e-01 -4.88031447e-01 6.38489962e-01 -4.97542322e-01 -8.33698809e-01 8.53631735e-01 -9.50410903e-01 -2.91700721e-01 -1.17491968e-01 6.61755919e-01 -4.61445689e-01 4.20130998e-01 -6.85770154e-01 -8.22752237e-01 -1.64957687e-01 -9.17067289e-01 1.03757834e+00 -2.61211395e-02 2.48082623e-01 -1.17473626e+00 -1.67969361e-01 2.63151318e-01 6.48662150e-01 1.92888975e-01 1.21473658e+00 2.49241948e-01 -7.34342039e-01 2.59780556e-01 -3.23464453e-01 4.62547481e-01 5.81137002e-01 1.63979545e-01 -1.14938796e+00 -4.50428843e-01 3.35658401e-01 -2.13749424e-01 7.96801686e-01 2.70493776e-01 1.43131554e+00 -1.39387339e-01 -1.01227798e-01 8.29032183e-01 1.46058834e+00 2.16406286e-01 6.97318494e-01 4.52760935e-01 7.30131447e-01 6.86991811e-01 7.45017529e-01 4.14449930e-01 -1.88510180e-01 8.07976902e-01 2.22805440e-01 -1.60346910e-01 -1.27687216e-01 3.98248196e-01 2.49271899e-01 9.76893842e-01 -6.76194370e-01 -2.69617409e-01 -6.14827693e-01 9.97566581e-02 -1.36628222e+00 -8.11134815e-01 -2.11210012e-01 2.17567635e+00 3.74669969e-01 -2.11265385e-01 -2.34168679e-01 2.66820550e-01 7.69348800e-01 -7.83430636e-02 -2.30814308e-01 -1.49287775e-01 -6.33858263e-01 4.94591832e-01 5.75626910e-01 2.22198620e-01 -1.08550942e+00 5.90355575e-01 6.80720043e+00 8.51119459e-01 -1.44746125e+00 -1.56801790e-01 4.78489071e-01 4.87857223e-01 -4.70534384e-01 -7.50233755e-02 -3.30370277e-01 3.18182766e-01 1.11331172e-01 2.09250569e-01 8.02804828e-01 5.05212426e-01 2.32332185e-01 -3.78999442e-01 -7.28099346e-01 1.04728305e+00 -1.96580395e-01 -1.01232314e+00 -9.63717028e-02 5.11408783e-02 5.62062025e-01 -1.37142390e-01 1.55103818e-01 -4.70272154e-01 -8.15659463e-02 -7.82258928e-01 5.23274183e-01 5.33510208e-01 8.41061473e-01 -1.70158312e-01 5.70632935e-01 -1.28053695e-01 -1.09530377e+00 -1.42339487e-02 -7.36766636e-01 1.68555193e-02 -2.88273454e-01 1.06122565e+00 -6.21780097e-01 6.97469175e-01 7.12889552e-01 7.54719853e-01 -5.10746300e-01 8.56788278e-01 -6.31022975e-02 5.63157141e-01 -5.70705235e-01 -1.08698137e-01 -2.04818800e-01 -9.02362168e-01 4.88717765e-01 8.84149492e-01 7.56695330e-01 -3.50597389e-02 2.71849513e-01 7.52232194e-01 2.82198399e-01 1.69932947e-01 -6.06798768e-01 -8.03652182e-02 3.34255695e-01 1.44389188e+00 -1.11228573e+00 -3.31507735e-02 -3.86062890e-01 8.15776646e-01 -1.54385522e-01 4.45388198e-01 -4.03890550e-01 3.66938002e-02 3.45139176e-01 1.01210572e-01 1.42065451e-01 -5.23455560e-01 -2.77360380e-01 -1.26155722e+00 2.60682791e-01 -6.32022202e-01 -5.25294170e-02 -9.94558752e-01 -1.53393030e+00 4.14004356e-01 -7.93440789e-02 -1.33370066e+00 4.91445601e-01 -1.16767073e+00 -4.93497998e-01 8.03291798e-01 -1.13055015e+00 -1.32278824e+00 -6.40058100e-01 7.69473970e-01 2.91846335e-01 -3.37223649e-01 9.61522460e-01 7.10548386e-02 -2.28030175e-01 -1.57668903e-01 8.16523492e-01 -1.53278217e-01 6.28719449e-01 -9.26205218e-01 -1.49304315e-01 4.33068246e-01 1.13440536e-01 2.72240758e-01 5.07752120e-01 -4.69978988e-01 -1.82621264e+00 -8.18034112e-01 4.19468768e-02 3.81765552e-02 4.57830101e-01 -2.35905886e-01 -6.95760012e-01 1.86199203e-01 -1.82120264e-01 -2.46013030e-02 5.38352370e-01 9.60467085e-02 -2.12464333e-01 -4.85683262e-01 -1.09221423e+00 2.36577958e-01 1.01504672e+00 -7.39332080e-01 -3.37886870e-01 7.03365266e-01 -2.59888858e-01 -2.23915100e-01 -9.02173042e-01 5.15743971e-01 1.14826131e+00 -1.18070960e+00 9.92108345e-01 1.38934925e-01 2.73233205e-01 -2.45259613e-01 -5.18969774e-01 -1.42438233e+00 -6.06890500e-01 -9.84435081e-02 4.28168327e-01 1.01582015e+00 -9.52545851e-02 -9.73046303e-01 7.21705377e-01 -6.23279437e-02 -2.24100187e-01 -2.98520297e-01 -7.49663770e-01 -1.02043450e+00 -4.69915062e-01 -6.08419552e-02 4.05092388e-01 7.23381341e-01 -5.47632694e-01 -4.52923439e-02 -4.31491762e-01 2.18598768e-01 8.52230549e-01 7.61008680e-01 5.11871159e-01 -1.29896986e+00 -5.92301488e-01 -2.06040785e-01 -4.84462738e-01 -7.44267166e-01 1.27999976e-01 -7.80313611e-01 -4.64420244e-02 -1.15175486e+00 3.30915838e-01 -8.61369252e-01 -9.65986028e-02 2.49429703e-01 2.69027025e-01 2.74365008e-01 -1.33275270e-01 4.54499394e-01 5.43111078e-02 3.95535260e-01 1.44298971e+00 -4.48962063e-01 6.21044710e-02 2.31094994e-02 7.96924010e-02 6.79267406e-01 6.09272480e-01 -1.57024264e-01 -2.21603572e-01 -6.07973516e-01 -1.86989475e-02 -3.88785042e-02 6.43311024e-01 -1.06714356e+00 -2.76627898e-01 -3.91542852e-01 5.39401889e-01 -2.54797131e-01 4.72949803e-01 -1.01324570e+00 6.14167392e-01 2.89800286e-01 8.89830962e-02 -2.98094243e-01 -2.06300914e-01 3.89218479e-01 -3.53993356e-01 2.18126569e-02 7.71815240e-01 -8.46656132e-03 -6.84888780e-01 7.91293569e-03 -2.65909642e-01 -5.10226309e-01 6.33472383e-01 -2.91755974e-01 -6.08302116e-01 -2.61323452e-01 -5.18364668e-01 -5.12795627e-01 7.79823363e-01 3.12169585e-02 8.15791428e-01 -1.42092621e+00 -4.61180389e-01 5.84990025e-01 -7.45767727e-03 -3.68593633e-01 9.01470780e-02 7.95683503e-01 -8.94699395e-01 6.54200017e-02 -7.17025459e-01 -8.72413635e-01 -1.21710813e+00 1.09298356e-01 1.39512926e-01 2.49423742e-01 -4.83182400e-01 3.47511619e-01 4.32524413e-01 -1.63595527e-01 -3.61741126e-01 -3.04704428e-01 -1.16139553e-01 -1.77089393e-01 5.42183332e-02 5.76526582e-01 3.40767980e-01 -4.92060512e-01 -1.46670297e-01 1.17915773e+00 4.05523777e-01 3.09844892e-02 1.48404467e+00 -1.20898925e-01 -5.28687060e-01 5.22109509e-01 9.48556006e-01 2.68844038e-01 -9.39553022e-01 -9.06938612e-02 -3.41631509e-02 -8.99294496e-01 2.40943842e-02 -5.18498182e-01 -1.08525908e+00 7.13340640e-01 7.69016266e-01 3.54592830e-01 1.35885656e+00 -1.09503023e-01 3.84143025e-01 7.82611668e-01 9.40814793e-01 -1.13100064e+00 1.25213116e-01 5.17645419e-01 9.06596124e-01 -9.96713698e-01 -3.68268900e-02 -7.48927236e-01 -1.18345052e-01 1.66584039e+00 1.13900304e-01 -4.50358465e-02 6.58865392e-01 3.00183445e-01 5.51768765e-03 -2.08945557e-01 -4.45202887e-01 -1.24927104e-01 4.07338738e-01 6.26649320e-01 3.03902358e-01 3.69868755e-01 -1.99056998e-01 -2.01556226e-03 2.68701818e-02 -1.91319436e-01 4.17635888e-01 8.71580541e-01 -5.08736551e-01 -1.14711618e+00 -7.73517787e-01 7.28320777e-01 -2.70673305e-01 1.55857176e-01 -1.45322353e-01 5.66682994e-01 -3.93413045e-02 7.41308689e-01 -5.72557226e-02 -5.78986406e-01 1.78506359e-01 -5.92180230e-02 8.30908716e-01 -2.60811239e-01 1.48439854e-01 2.83396125e-01 3.25749785e-01 -2.30541050e-01 -7.61295080e-01 -6.09488428e-01 -4.12563980e-01 -1.19663149e-01 -4.25929874e-01 -4.82066534e-02 7.19672203e-01 9.04278994e-01 -2.12516710e-01 2.29139194e-01 1.05365324e+00 -7.80391514e-01 -2.63952911e-01 -9.29233432e-01 -1.32788336e+00 7.17714190e-01 4.52131592e-03 -9.51842427e-01 -3.76775175e-01 2.24051178e-01]	[10.003211975097656, -2.651890277862549]
625fe872-ea5e-4fac-9f10-e246f9591d2c	bass-boosting-abstractive-summarization-with	2105.12041	null	https://arxiv.org/abs/2105.12041v1	https://arxiv.org/pdf/2105.12041v1.pdf	BASS: Boosting Abstractive Summarization with Unified Semantic Graph	Abstractive summarization for long-document or multi-document remains challenging for the Seq2Seq architecture, as Seq2Seq is not good at analyzing long-distance relations in text. In this paper, we present BASS, a novel framework for Boosting Abstractive Summarization based on a unified Semantic graph, which aggregates co-referent phrases distributing across a long range of context and conveys rich relations between phrases. Further, a graph-based encoder-decoder model is proposed to improve both the document representation and summary generation process by leveraging the graph structure. Specifically, several graph augmentation methods are designed to encode both the explicit and implicit relations in the text while the graph-propagation attention mechanism is developed in the decoder to select salient content into the summary. Empirical results show that the proposed architecture brings substantial improvements for both long-document and multi-document summarization tasks.	['Haifeng Wang', 'Hua Wu', 'Sujian Li', 'Ziqiang Cao', 'Jiachen Liu', 'Xinyan Xiao', 'Wei Li', 'Wenhao Wu']	2021-05-25	null	https://aclanthology.org/2021.acl-long.472	https://aclanthology.org/2021.acl-long.472.pdf	acl-2021-5	['implicit-relations']	['natural-language-processing']	[ 4.49201137e-01 5.81027925e-01 -3.95590007e-01 -4.07691270e-01 -1.07012296e+00 -5.67389250e-01 5.78566968e-01 7.38075078e-01 -7.89294243e-02 9.18666124e-01 1.39740694e+00 -1.08039491e-01 -9.53562465e-03 -7.42307842e-01 -6.51782870e-01 -2.44573355e-01 -1.33642927e-01 3.30239356e-01 7.45822862e-02 -4.97834593e-01 5.60189784e-01 -3.44302654e-02 -8.26851785e-01 5.40304720e-01 1.29226160e+00 3.72414678e-01 2.81963319e-01 1.11444747e+00 -4.96826559e-01 9.50905800e-01 -1.04951978e+00 -6.95041835e-01 -3.12909871e-01 -1.02473557e+00 -9.72050846e-01 -1.01310708e-01 6.04275465e-01 -2.53538311e-01 -5.83891153e-01 1.02988255e+00 7.94500351e-01 3.48276526e-01 5.99269807e-01 -6.95272684e-01 -8.59740078e-01 1.33784628e+00 -7.07457602e-01 4.46964532e-01 6.42147303e-01 -2.90287048e-01 1.77920604e+00 -5.56030095e-01 5.05658686e-01 1.40141594e+00 4.05901521e-01 4.55484390e-01 -8.20226490e-01 -2.47326627e-01 6.05130613e-01 8.30110013e-02 -9.15791929e-01 -2.72005856e-01 8.38387668e-01 1.16370961e-01 1.38546944e+00 4.85356838e-01 8.25350821e-01 1.04364824e+00 6.40075326e-01 1.03447795e+00 6.21354431e-02 -1.82978496e-01 -5.02684861e-02 -6.65355444e-01 5.95045269e-01 7.59313405e-01 5.37528038e-01 -7.21876383e-01 -9.12893295e-01 -2.02044576e-01 4.36219990e-01 -3.52922320e-01 -2.70287365e-01 3.34904581e-01 -1.14093983e+00 8.92275989e-01 5.67057312e-01 1.39205754e-01 -5.30397594e-01 3.47698033e-01 8.75469446e-01 3.50768082e-02 9.77451682e-01 8.54689240e-01 -1.76697388e-01 -3.85747366e-02 -1.17317164e+00 2.94424266e-01 8.37581277e-01 1.28090811e+00 4.61343974e-01 9.12112072e-02 -1.06301498e+00 8.81762445e-01 9.20220166e-02 3.12103480e-01 3.67956609e-01 -4.58110780e-01 1.05364096e+00 8.11133444e-01 -5.32509804e-01 -1.20720255e+00 -3.35349768e-01 -6.97151780e-01 -1.28913951e+00 -8.79257262e-01 -5.11797965e-01 -3.82451057e-01 -8.64360988e-01 1.51389050e+00 1.70006696e-02 5.85079752e-03 2.41140828e-01 7.06535518e-01 1.41101944e+00 1.09222257e+00 -2.82950420e-03 -3.41517478e-01 1.29447198e+00 -1.54693079e+00 -1.11424065e+00 -5.87415934e-01 6.25711977e-01 -3.89327079e-01 8.06030512e-01 -1.83404967e-01 -1.48836625e+00 -3.94256949e-01 -1.09115040e+00 -5.72895765e-01 1.59643870e-02 -2.23727718e-01 4.42490131e-01 -8.50291029e-02 -1.10087788e+00 5.24758160e-01 -6.32854998e-01 -3.67763966e-01 5.38565218e-01 1.16421610e-01 7.59288669e-03 -4.48357053e-02 -1.24609935e+00 6.72722220e-01 6.91937208e-01 1.40328750e-01 -3.43183100e-01 -4.37420756e-01 -1.16904461e+00 5.41943967e-01 2.97856539e-01 -1.54953456e+00 1.15043557e+00 -6.20482981e-01 -1.32835615e+00 4.34401602e-01 -5.08111715e-01 -6.27713382e-01 1.06460787e-01 -4.65748280e-01 -1.44286275e-01 3.60760570e-01 3.53816688e-01 4.45553780e-01 5.67207217e-01 -8.83902729e-01 -4.57583696e-01 -4.55074340e-01 -7.25131035e-02 8.30920637e-01 -2.63754249e-01 6.99919015e-02 -7.44761527e-01 -1.27096868e+00 -2.61031568e-01 -5.34753144e-01 -4.58707064e-01 -9.31443632e-01 -1.25900412e+00 -3.56546640e-01 5.05073845e-01 -9.55253601e-01 1.79832280e+00 -1.63091838e+00 6.67098939e-01 -3.92125584e-02 2.20169246e-01 2.05103263e-01 -5.06297529e-01 1.00322962e+00 1.50950119e-01 2.39832401e-01 -4.75339442e-01 -3.93029094e-01 -6.56935051e-02 1.41045749e-01 -5.25312841e-01 -1.39951661e-01 3.18551540e-01 1.53494263e+00 -1.24807537e+00 -5.47930121e-01 -4.12164897e-01 1.65032327e-01 -6.42076731e-01 3.47431540e-01 -4.99464422e-01 3.08210254e-01 -7.60241151e-01 1.59360439e-01 4.11276162e-01 -2.97085017e-01 2.18186989e-01 -8.91875550e-02 2.86395431e-01 8.05404127e-01 -4.23320502e-01 2.26952958e+00 -2.33266696e-01 4.81747031e-01 -1.08955018e-01 -9.03513908e-01 8.58860373e-01 1.56132117e-01 1.24922760e-01 -5.26746035e-01 -6.84518367e-02 -1.15230225e-01 -2.76822239e-01 -3.91927540e-01 1.28441763e+00 1.12850480e-01 -4.81427193e-01 5.30332208e-01 1.66648969e-01 -4.64834124e-01 5.64997613e-01 1.03815484e+00 1.31696224e+00 -1.34707615e-01 4.13733989e-01 -3.50879878e-01 4.42290395e-01 4.59467573e-03 3.62850398e-01 8.87461901e-01 4.87862617e-01 7.80713618e-01 9.39406812e-01 1.54714480e-01 -8.52255225e-01 -8.46138775e-01 6.39843941e-01 1.14175701e+00 2.40563959e-01 -1.10456204e+00 -7.21904337e-01 -9.94797468e-01 -7.07120076e-02 1.03463125e+00 -4.33392882e-01 -5.48765540e-01 -8.12233567e-01 -5.76353848e-01 5.63210428e-01 6.49395883e-01 4.58205581e-01 -9.03839290e-01 -3.41480738e-03 4.26177025e-01 -5.31341434e-01 -9.62441504e-01 -1.15528762e+00 -1.60480276e-01 -9.41424608e-01 -8.38813841e-01 -7.50990272e-01 -9.02804136e-01 5.57696462e-01 3.36549461e-01 1.34728515e+00 3.02515384e-02 8.94429088e-02 2.59215504e-01 -5.69883883e-01 -4.46486592e-01 -4.69612986e-01 6.78787827e-01 -5.51331043e-01 -2.87633687e-01 -1.47075549e-01 -5.52208960e-01 -5.86540043e-01 -4.96627122e-01 -8.18979979e-01 4.59678620e-01 5.86718917e-01 8.51302505e-01 3.45698744e-01 -2.36520290e-01 1.13762903e+00 -1.19089365e+00 1.37128341e+00 -5.26506007e-01 2.44923476e-02 4.46344554e-01 -2.61643767e-01 3.88691455e-01 6.56956375e-01 1.99441612e-01 -1.19200385e+00 -5.64432204e-01 -3.22022647e-01 2.41257191e-01 4.36115652e-01 1.04766500e+00 -3.10591143e-02 7.16658473e-01 3.45378309e-01 4.21766013e-01 -1.12698749e-01 -3.02154958e-01 7.56171823e-01 5.57966471e-01 6.24326885e-01 -2.88525313e-01 4.60725009e-01 3.70455137e-03 -3.70611772e-02 -9.40105677e-01 -1.42272842e+00 -6.44820035e-01 -5.71487784e-01 2.24437136e-02 1.00624764e+00 -9.95793283e-01 -1.29020765e-01 2.04409942e-01 -1.57916832e+00 -1.55558243e-01 -4.48854625e-01 2.10795149e-01 -3.88679147e-01 6.76189125e-01 -7.35016227e-01 -4.33657348e-01 -1.33090329e+00 -6.61377192e-01 1.49301112e+00 2.43939966e-01 -4.47933406e-01 -1.13148534e+00 1.10357091e-01 2.90769845e-01 2.49610171e-01 1.70774937e-01 1.05138552e+00 -8.37315321e-01 -4.95786220e-01 -1.01095244e-01 -3.33185256e-01 3.26930732e-01 2.26059347e-01 -2.00390518e-01 -3.34659129e-01 -3.00356388e-01 -4.63502705e-01 -2.55358905e-01 1.51618850e+00 4.91827607e-01 1.24768651e+00 -8.78491223e-01 -3.09508622e-01 3.45013440e-01 9.52300966e-01 -2.99815118e-01 5.87496877e-01 -1.08473726e-01 1.24492764e+00 5.67368329e-01 4.66847539e-01 4.28013355e-01 7.23851502e-01 2.89547712e-01 2.45756492e-01 1.13051673e-02 -4.54585433e-01 -5.69626749e-01 4.03267175e-01 1.53854287e+00 2.06685290e-01 -9.06736732e-01 -6.51488721e-01 5.49424589e-01 -2.08669305e+00 -1.11474681e+00 -4.18907911e-01 1.65391088e+00 9.64644432e-01 1.08594388e-01 1.17561547e-02 -3.33373427e-01 8.02098334e-01 8.40525627e-01 -4.13302779e-01 -7.50238597e-01 -3.24007392e-01 1.29767433e-01 3.32469732e-01 7.66781449e-01 -7.71844864e-01 1.08801663e+00 6.42685556e+00 7.99439013e-01 -7.76063025e-01 -3.02939117e-01 3.73883367e-01 -1.31667823e-01 -8.39220762e-01 -2.05876634e-01 -6.67380035e-01 2.62023181e-01 7.89889932e-01 -7.04382598e-01 -3.00560966e-02 4.06722337e-01 2.20568672e-01 -2.20060442e-02 -8.36614549e-01 4.98859048e-01 5.68049967e-01 -1.75398326e+00 7.49247313e-01 -3.58840913e-01 8.91630948e-01 6.58080503e-02 -3.17724824e-01 2.94625372e-01 4.05334085e-01 -8.11358094e-01 5.46728611e-01 4.45722282e-01 6.59246683e-01 -9.60305989e-01 6.72742605e-01 3.63134414e-01 -1.18930995e+00 1.94377989e-01 -3.36820126e-01 1.01152897e-01 5.24654090e-01 6.20774806e-01 -9.18890357e-01 1.26787150e+00 2.31394544e-02 1.28110421e+00 -6.50624216e-01 7.97589362e-01 -7.24409997e-01 8.07672679e-01 2.93352306e-01 -3.45107079e-01 5.09142518e-01 -3.11612248e-01 1.01538742e+00 1.85469103e+00 2.82066345e-01 2.25782052e-01 1.52190045e-01 4.93167400e-01 -4.52901572e-01 2.02495620e-01 -6.22043550e-01 -2.54930526e-01 2.17415243e-01 1.20455003e+00 -4.34248835e-01 -6.29489362e-01 -2.28280932e-01 1.32969558e+00 5.17169416e-01 5.16203880e-01 -6.79391861e-01 -7.58900225e-01 3.51539642e-01 -1.76234782e-01 2.97196448e-01 -3.32694501e-01 -3.77300352e-01 -1.37366188e+00 -2.35056449e-02 -6.93483591e-01 7.49532759e-01 -8.07034850e-01 -1.17712796e+00 6.40214801e-01 -1.62773263e-02 -4.65865582e-01 -2.52414197e-01 1.42779484e-01 -1.07839131e+00 9.18002903e-01 -1.58651972e+00 -1.22918975e+00 -9.25549567e-02 1.53665051e-01 9.53473270e-01 6.96893036e-02 6.64703071e-01 -1.62963241e-01 -7.24057078e-01 3.68453711e-01 9.87958163e-02 4.06316333e-02 5.15427351e-01 -1.52247441e+00 9.90864336e-01 9.78671014e-01 1.57929182e-01 6.40541017e-01 6.30735755e-01 -1.05111587e+00 -1.39932430e+00 -1.57153249e+00 1.20432365e+00 -4.01508510e-02 5.88026464e-01 -4.61235732e-01 -1.03978872e+00 7.96353698e-01 9.02758002e-01 -5.75447142e-01 7.35328317e-01 2.25385040e-01 -2.78110623e-01 2.02017054e-01 -4.83722866e-01 7.63118207e-01 1.27750003e+00 -4.74698991e-01 -1.04793215e+00 4.40879732e-01 1.24715030e+00 -4.60503876e-01 -6.52882814e-01 2.69468307e-01 1.11645676e-01 -5.39610684e-01 7.18239367e-01 -8.32693815e-01 1.03951681e+00 9.78997424e-02 1.61794126e-01 -1.89949000e+00 -5.41951656e-01 -9.56363440e-01 -5.47633886e-01 1.51088226e+00 6.06785417e-01 -2.79712111e-01 6.78569794e-01 -9.33062360e-02 -7.94318378e-01 -8.46510708e-01 -5.30308723e-01 -4.55077618e-01 -6.10297471e-02 -2.34219618e-02 5.06751955e-01 6.23128474e-01 5.05249918e-01 1.42457020e+00 -3.59628737e-01 6.29091810e-04 4.65964288e-01 3.16994339e-01 6.81943178e-01 -7.85235345e-01 -1.02344893e-01 -5.73271513e-01 -8.45297128e-02 -1.53877604e+00 4.90173250e-01 -1.45387161e+00 -2.76953191e-03 -2.65975785e+00 5.14452755e-01 2.11890221e-01 4.96945232e-02 8.10356364e-02 -9.73318279e-01 -3.28975797e-01 6.21692054e-02 -1.13645196e-02 -1.08436167e+00 1.17985260e+00 1.53813589e+00 -4.08840626e-01 -1.81342319e-01 -1.10250637e-01 -1.15638924e+00 3.81009102e-01 6.40264034e-01 -2.87210494e-01 -6.26985133e-01 -8.00172865e-01 4.48443592e-01 3.76662701e-01 -2.42579058e-02 -4.78979290e-01 4.76768672e-01 1.22018144e-01 1.32598514e-02 -1.05592120e+00 1.15811534e-01 3.64338257e-03 -4.73148555e-01 2.38565266e-01 -9.77384567e-01 2.36535832e-01 1.71417356e-01 9.79901850e-01 -4.36094642e-01 -6.86564818e-02 3.04719478e-01 -1.34523198e-01 -2.76854068e-01 3.90359432e-01 -2.34584615e-01 5.65771282e-01 6.20799065e-01 1.06813818e-01 -5.45812547e-01 -7.25434422e-01 -3.69798660e-01 7.68354416e-01 -2.14189775e-02 4.67667460e-01 7.57937789e-01 -1.22056150e+00 -1.28049028e+00 -2.12565139e-01 6.51123971e-02 5.15075207e-01 3.00411016e-01 4.83860314e-01 -3.87362599e-01 5.55088580e-01 1.73761785e-01 -1.77246317e-01 -1.37322390e+00 4.17275906e-01 -1.25913754e-01 -6.51721597e-01 -8.01878154e-01 1.12618542e+00 2.47922719e-01 -9.07146037e-02 1.77391425e-01 -4.49478924e-01 -3.73863697e-01 3.56882393e-01 5.70845425e-01 3.78089309e-01 1.20946653e-02 -5.49425244e-01 -1.32788882e-01 2.91168869e-01 -3.68758112e-01 7.12500736e-02 1.42010486e+00 -3.16692948e-01 -6.21073723e-01 3.24497432e-01 1.22633028e+00 1.79234743e-01 -8.13326120e-01 -2.01281324e-01 2.26082981e-01 -3.01610995e-02 6.26568124e-02 -5.69564581e-01 -6.43188119e-01 6.90320492e-01 -8.59074354e-01 3.65193099e-01 1.01958895e+00 1.86481431e-01 1.14915001e+00 3.87605935e-01 -2.68097550e-01 -9.66657102e-01 4.72955048e-01 9.96985674e-01 1.35772586e+00 -7.86996841e-01 3.03709388e-01 -6.10051572e-01 -1.01130438e+00 1.08772290e+00 4.76981759e-01 -1.32375240e-01 5.36961108e-02 -5.12231961e-02 -4.91538823e-01 -5.01328409e-01 -1.07949340e+00 -1.12589791e-01 6.06199861e-01 2.74998784e-01 7.08714068e-01 -1.63171589e-01 -5.26663721e-01 6.80139840e-01 -3.44832689e-01 -4.94626045e-01 6.41305029e-01 7.26360857e-01 -5.95309258e-01 -8.26504529e-01 1.66023150e-01 7.04052091e-01 -6.08856797e-01 -4.80163187e-01 -8.10984373e-01 1.70631424e-01 -6.65137589e-01 1.03946340e+00 1.63339123e-01 -1.59284472e-01 5.16832709e-01 -8.06550533e-02 4.62729275e-01 -1.18671703e+00 -9.12379622e-01 -3.26120369e-02 6.96018994e-01 -4.25107777e-01 -2.64219910e-01 -4.44371492e-01 -1.44614685e+00 -1.40822873e-01 -3.80984128e-01 5.61410606e-01 4.11442935e-01 6.73678219e-01 7.81518996e-01 1.23880589e+00 5.35369873e-01 -6.37817264e-01 -5.45080960e-01 -1.17224646e+00 -5.24677634e-01 2.33419567e-01 5.06996155e-01 1.55024186e-01 -4.63393889e-02 -1.34683356e-01]	[12.5098876953125, 9.49025821685791]
3e8e0133-8efc-425d-90ea-70f90f0ee904	fair-k-center-clustering-for-data	1901.08628	null	https://arxiv.org/abs/1901.08628v2	https://arxiv.org/pdf/1901.08628v2.pdf	Fair k-Center Clustering for Data Summarization	In data summarization we want to choose $k$ prototypes in order to summarize a data set. We study a setting where the data set comprises several demographic groups and we are restricted to choose $k_i$ prototypes belonging to group $i$. A common approach to the problem without the fairness constraint is to optimize a centroid-based clustering objective such as $k$-center. A natural extension then is to incorporate the fairness constraint into the clustering problem. Existing algorithms for doing so run in time super-quadratic in the size of the data set, which is in contrast to the standard $k$-center problem being approximable in linear time. In this paper, we resolve this gap by providing a simple approximation algorithm for the $k$-center problem under the fairness constraint with running time linear in the size of the data set and $k$. If the number of demographic groups is small, the approximation guarantee of our algorithm only incurs a constant-factor overhead.	['Matthäus Kleindessner', 'Pranjal Awasthi', 'Jamie Morgenstern']	2019-01-24	null	null	null	null	['data-summarization']	['miscellaneous']	[-2.75507152e-01 3.03003371e-01 -3.79535496e-01 -5.66074550e-01 -7.69128442e-01 -5.66194892e-01 -7.34333396e-02 8.75966668e-01 -7.40110219e-01 4.74577099e-01 5.28826416e-02 -1.61470339e-01 -3.94468993e-01 -9.97499228e-01 -6.49483502e-01 -4.74600077e-01 -2.96383947e-01 8.86291862e-01 -4.21530642e-02 2.89794635e-02 6.76766992e-01 1.93378568e-01 -1.48284566e+00 -4.23423082e-01 1.16761053e+00 9.44644868e-01 -2.52674282e-01 7.05176294e-01 -2.16697991e-01 2.99265623e-01 -6.89181685e-01 -4.11883175e-01 6.56347454e-01 -6.27869368e-01 -1.12147760e+00 2.46404529e-01 3.27416599e-01 -1.06547773e-01 -1.50934026e-01 1.04281878e+00 4.93413121e-01 5.92741907e-01 6.81905985e-01 -1.57321441e+00 -1.63335621e-01 1.04408658e+00 -9.08828020e-01 2.22740769e-02 1.39296278e-01 -4.55333889e-01 1.15969908e+00 -2.09804535e-01 3.95555228e-01 1.11669981e+00 4.03761506e-01 4.49979782e-01 -1.37400603e+00 -5.91232240e-01 2.74878085e-01 -5.40534221e-02 -1.61502290e+00 -6.11717880e-01 5.60835779e-01 -2.19236717e-01 6.90834820e-01 6.26036942e-01 3.94170910e-01 -3.35827321e-01 -6.61925256e-01 6.54320359e-01 5.51686227e-01 -3.73161077e-01 7.54263282e-01 3.34049091e-02 6.84492946e-01 5.54788828e-01 6.83284402e-01 -6.36700451e-01 -3.16220045e-01 -7.34343588e-01 1.62028968e-01 -1.04754213e-02 -1.02270953e-01 -4.36783820e-01 -6.95455611e-01 1.09674776e+00 4.52017963e-01 4.70753200e-02 3.67594026e-02 4.83587444e-01 5.44099271e-01 4.27725673e-01 5.18029928e-01 4.77843285e-01 -3.01944703e-01 1.14987325e-02 -1.30919468e+00 5.41611075e-01 1.01545060e+00 1.09113252e+00 8.65390301e-01 -3.24986368e-01 2.95352727e-01 6.57886446e-01 -1.09772757e-01 3.88857186e-01 1.93377972e-01 -1.62082124e+00 4.65129405e-01 6.66086733e-01 2.75981218e-01 -1.13771498e+00 -2.22338632e-01 1.37266899e-02 -9.65255737e-01 -2.05121282e-02 6.14281118e-01 -8.64345282e-02 -4.61240381e-01 1.99792242e+00 5.76884747e-01 -3.31903726e-01 -2.01826900e-01 4.99560475e-01 2.42353097e-01 5.18631876e-01 -3.12458009e-01 -9.23367918e-01 1.03710675e+00 -6.40986383e-01 -4.48104262e-01 2.45260090e-01 7.95307398e-01 -4.63852584e-01 7.15056777e-01 2.80116856e-01 -1.49762082e+00 -1.81331392e-02 -7.40018129e-01 -1.49505973e-01 -1.47043213e-01 -3.86005104e-01 4.87467349e-01 8.25550377e-01 -1.34537828e+00 5.02491534e-01 -5.00208795e-01 -6.46046996e-01 5.15307605e-01 6.82946861e-01 -2.06368655e-01 -1.46729529e-01 -4.88848954e-01 5.00044882e-01 4.93032724e-01 -4.52624887e-01 -8.33353624e-02 -7.45901406e-01 -5.60362756e-01 2.44039208e-01 5.52211821e-01 -7.95229554e-01 8.88446748e-01 -7.36491263e-01 -8.44510734e-01 8.17604899e-01 -4.31122392e-01 -3.56382757e-01 6.96143210e-01 2.69188851e-01 4.78179574e-01 1.97483942e-01 2.84891903e-01 3.61085325e-01 4.20304805e-01 -1.28963971e+00 -8.75507951e-01 -6.57547176e-01 1.13976344e-01 3.85591507e-01 -3.46729934e-01 9.53804702e-02 -5.85986495e-01 -2.43392348e-01 1.34564668e-01 -6.84356391e-01 -7.44608939e-01 -4.48014550e-02 -3.76027286e-01 -5.77346087e-01 5.53479791e-01 -2.39451453e-01 1.66679049e+00 -2.20016932e+00 -5.73014840e-02 5.74795902e-01 5.39228380e-01 -5.06074168e-03 2.07057700e-01 4.27647591e-01 2.44817302e-01 4.14826781e-01 -4.90227401e-01 -5.40028989e-01 2.16693699e-01 2.19758928e-01 -2.10964326e-02 7.72882104e-01 -5.69413066e-01 3.04392636e-01 -7.77645946e-01 -5.51309049e-01 -2.13859856e-01 -4.36278522e-01 -9.56278026e-01 1.37088448e-01 -1.11250736e-01 -4.32890475e-01 -3.90754730e-01 2.81266510e-01 9.66109157e-01 -2.03557447e-01 2.59072661e-01 2.58283734e-01 -4.65012295e-03 -1.53888091e-01 -1.49523866e+00 1.47044575e+00 2.61697061e-02 2.08222210e-01 5.24029136e-01 -1.56577420e+00 6.40494704e-01 -5.84557429e-02 9.44734037e-01 -5.01431525e-02 2.50925243e-01 3.09890211e-01 -2.73804396e-01 9.03309509e-03 8.51312637e-01 -4.62228924e-01 -6.83901846e-01 1.03375196e+00 -4.09608454e-01 -6.64161295e-02 4.52632934e-01 6.80161715e-01 1.19596803e+00 -8.95327926e-01 3.31381619e-01 -5.52684605e-01 7.33256564e-02 2.05280319e-01 7.44334579e-01 9.29432452e-01 -3.09976608e-01 4.24146920e-01 7.70817578e-01 -2.44770944e-01 -1.04039931e+00 -6.47938967e-01 1.07978456e-01 1.07188368e+00 2.89352179e-01 -5.87767363e-01 -1.26973069e+00 -6.14634573e-01 2.26388365e-01 4.86048877e-01 -7.22421050e-01 6.92072734e-02 -4.33526009e-01 -8.55923772e-01 2.69989043e-01 2.23184705e-01 4.49434131e-01 -3.64870787e-01 -6.91660166e-01 2.44082734e-01 -3.89309496e-01 -6.10017061e-01 -9.51207936e-01 7.92964473e-02 -9.33521271e-01 -1.27895439e+00 -5.07845104e-01 -6.52779102e-01 1.03027987e+00 3.65759313e-01 9.56386924e-01 9.75111425e-02 -2.97767848e-01 3.27640891e-01 -2.66698688e-01 -4.73292261e-01 -1.01264827e-02 1.43736988e-01 1.15546845e-01 -3.38203281e-01 5.15041769e-01 -4.15551990e-01 -7.20151007e-01 6.45500198e-02 -9.32369411e-01 -5.02502620e-01 -1.04585588e-01 5.40694892e-01 5.41405201e-01 6.35504723e-01 6.36138380e-01 -1.13870573e+00 7.17895567e-01 -6.42984152e-01 -5.14800966e-01 2.41365105e-01 -7.40028441e-01 -3.47270034e-02 8.07127833e-01 -4.22142707e-02 -2.41923764e-01 7.87537321e-02 1.76198974e-01 -1.70043007e-01 1.99869230e-01 4.55034107e-01 -4.32866126e-01 2.60005027e-01 4.80112791e-01 -4.08886820e-02 2.34234527e-01 -3.52094501e-01 5.84805965e-01 7.84626007e-01 4.78852689e-01 -7.06794739e-01 4.80616003e-01 4.98361200e-01 1.06265256e-02 -7.70358443e-01 -4.59453493e-01 -8.10029507e-01 -3.09422553e-01 1.64707109e-01 2.30143055e-01 -7.15509176e-01 -1.15033770e+00 7.58621097e-02 -6.03737295e-01 -3.12712908e-01 -7.40654767e-01 -3.43829244e-02 -7.89717913e-01 7.07361221e-01 -1.71615675e-01 -9.18804646e-01 -6.26868486e-01 -6.84898674e-01 5.92142820e-01 1.23852290e-01 -2.26583943e-01 -5.80808878e-01 3.89902666e-02 2.61981040e-01 2.69800395e-01 4.38122869e-01 1.03658092e+00 -8.30393970e-01 -2.43523329e-01 -5.42536974e-01 -2.95219421e-01 3.96408588e-02 9.36810975e-04 -1.40101343e-01 -2.90399730e-01 -5.72386861e-01 -5.02765179e-02 -7.17513561e-02 7.12825477e-01 5.78284740e-01 1.41574168e+00 -7.65899718e-01 -3.72222453e-01 4.20810103e-01 1.61422515e+00 -4.11458723e-02 1.80543408e-01 -1.16304874e-01 4.46016490e-01 7.35444963e-01 6.41402662e-01 9.54632103e-01 7.80991793e-01 4.11633790e-01 6.11559004e-02 8.39403123e-02 5.32893658e-01 1.34846300e-01 -8.82265493e-02 7.79710531e-01 3.72978896e-02 -4.56475079e-01 -9.46448088e-01 8.37362051e-01 -2.19242072e+00 -9.36249852e-01 1.09430447e-01 2.62041879e+00 8.06043148e-01 -2.49716878e-01 8.54081571e-01 3.94105792e-01 8.65919590e-01 -1.29828364e-01 -6.30837262e-01 -7.81533480e-01 1.05432548e-01 1.02212965e-01 8.06128919e-01 6.86058223e-01 -8.70976269e-01 6.44153059e-01 6.89021111e+00 9.55705106e-01 -7.09764123e-01 -8.92464519e-02 9.45750654e-01 -6.36678159e-01 -4.15505946e-01 9.57147628e-02 -4.79475290e-01 6.46092653e-01 1.12433183e+00 -8.31229389e-01 5.62704444e-01 8.35680366e-01 2.71419615e-01 -6.04877234e-01 -1.10940862e+00 1.00992441e+00 1.49905056e-01 -1.11943173e+00 -1.92818984e-01 4.31785285e-01 6.23556197e-01 -2.03906134e-01 -1.66463181e-01 -1.08905219e-01 7.46533990e-01 -8.40137184e-01 4.48467523e-01 2.48527178e-03 9.47628260e-01 -1.49019969e+00 3.81858647e-01 5.73574543e-01 -1.06370270e+00 -1.78455085e-01 -5.69176137e-01 -2.65898257e-02 1.46655768e-01 7.28619218e-01 -3.43571573e-01 5.05275667e-01 9.19072807e-01 1.39387727e-01 -1.67888835e-01 1.10616481e+00 7.11330116e-01 3.64829719e-01 -9.31164980e-01 -2.36659199e-02 1.32820025e-01 -3.08453918e-01 2.49219224e-01 1.01238513e+00 4.55834508e-01 6.02519751e-01 4.05020416e-01 2.71310836e-01 -4.67734694e-01 3.96281809e-01 -4.15709198e-01 -3.44845057e-02 8.76288891e-01 8.59926999e-01 -8.93702984e-01 -6.54137373e-01 -4.98435386e-02 8.80151749e-01 5.12987316e-01 5.20536900e-02 -3.85551274e-01 -8.46806109e-01 6.63216829e-01 3.26971769e-01 2.80384183e-01 -1.89289436e-01 -5.58849275e-01 -8.84585440e-01 4.18653674e-02 -6.28730297e-01 8.78180742e-01 -7.56617561e-02 -1.29526031e+00 1.53312325e-01 1.56522736e-01 -7.29669809e-01 -4.71356921e-02 4.58636647e-03 -5.20968556e-01 6.55521572e-01 -1.02104592e+00 -4.38973546e-01 3.11619956e-02 6.95539117e-01 1.40093282e-01 3.07907820e-01 6.55861080e-01 1.34644017e-01 -6.01929963e-01 8.99412394e-01 6.39974773e-01 -1.88363701e-01 7.20594943e-01 -1.45295787e+00 -1.72770768e-01 9.70839262e-01 -5.34641325e-01 8.55170310e-01 1.07370186e+00 -2.47851312e-01 -1.08745229e+00 -1.06000340e+00 1.29962003e+00 -2.04631463e-01 1.58977464e-01 -2.57451177e-01 -6.35727704e-01 4.08278435e-01 7.35753924e-02 1.21395759e-01 1.26571012e+00 2.90378183e-01 -2.86544085e-01 -4.35416937e-01 -1.61494565e+00 4.30533767e-01 1.05928195e+00 -9.14808214e-02 -1.73652172e-01 1.88940048e-01 5.00604331e-01 -1.20015899e-02 -9.91970599e-01 2.63430215e-02 2.64216036e-01 -6.83855414e-01 5.99790037e-01 -4.93694127e-01 1.06628582e-01 -4.00995135e-01 -2.69850731e-01 -1.15736747e+00 -2.42276043e-01 -7.85940528e-01 -1.30524710e-02 1.14796269e+00 2.32961312e-01 -4.37719643e-01 1.03554201e+00 1.20023072e+00 2.42719263e-01 -5.64383566e-01 -1.05488884e+00 -5.31664729e-01 5.02967179e-01 -3.94075876e-03 7.01269984e-01 1.02728879e+00 6.08304262e-01 1.43367112e-01 -2.24786535e-01 -1.57097891e-01 9.68912661e-01 4.23749954e-01 1.01905406e+00 -1.17503381e+00 -1.82877675e-01 -6.91204369e-01 -1.10638343e-01 -8.31081986e-01 -2.08867434e-03 -7.94824541e-01 1.84536546e-01 -1.46128023e+00 6.04220808e-01 -1.07370055e+00 -3.34533341e-02 3.00579637e-01 -3.87549162e-01 1.92561205e-02 2.85639435e-01 2.25426197e-01 -1.15346324e+00 1.98342443e-01 4.42037731e-01 4.35267389e-02 -4.67265725e-01 4.35102358e-02 -1.28027654e+00 4.45153505e-01 8.83884251e-01 -5.11460125e-01 -3.98408353e-01 -2.74951696e-01 1.33343607e-01 8.27473104e-02 -3.74012828e-01 -5.29949486e-01 5.25063932e-01 -3.57348084e-01 -1.43794343e-01 -5.78783214e-01 -1.60112187e-01 -7.85851538e-01 1.48480460e-01 4.82962042e-01 -5.00775099e-01 5.13495058e-02 -2.37700120e-01 7.77373552e-01 -2.09593087e-01 -1.86199412e-01 9.02462900e-01 -2.94781715e-01 -5.77381514e-02 6.80509090e-01 -3.61224532e-01 3.81299108e-01 1.26109600e+00 -4.37160194e-01 -3.55383515e-01 -4.01641309e-01 -5.14153481e-01 7.44938970e-01 9.34521556e-01 -1.02512896e-01 1.85994640e-01 -1.01083219e+00 -5.48485875e-01 -1.89073175e-01 1.52530730e-01 5.15565872e-01 2.81776935e-01 6.26567781e-01 -6.86674178e-01 1.71521857e-01 1.17001504e-01 -2.47235954e-01 -1.35907471e+00 8.85689318e-01 7.25827590e-02 -1.40280783e-01 -2.11029470e-01 9.53883052e-01 -1.35633141e-01 -2.67773420e-01 3.63854975e-01 8.85774419e-02 1.60633296e-01 2.81193048e-01 5.30375183e-01 7.30025172e-01 -1.98910862e-01 -5.66543281e-01 -4.47384953e-01 4.32572931e-01 -1.53798535e-01 -2.58805364e-01 1.33442080e+00 -4.66753662e-01 -5.43298364e-01 1.06945366e-01 1.34758234e+00 9.16389078e-02 -7.13345349e-01 -4.52112377e-01 1.31526720e-02 -5.58939874e-01 -3.41325581e-01 -1.50876477e-01 -1.07888401e+00 4.82755363e-01 1.86219394e-01 4.30643171e-01 1.43958712e+00 1.14645198e-01 7.14141488e-01 3.33188415e-01 5.79168797e-01 -1.51659548e+00 -3.02070379e-01 1.87655792e-01 3.33410293e-01 -1.06838882e+00 2.99356490e-01 -2.46526837e-01 -4.26341623e-01 7.96762824e-01 4.02284503e-01 -4.34678435e-01 7.83369899e-01 5.61574735e-02 -2.02173859e-01 -1.10363312e-01 -6.55479252e-01 -6.32834435e-02 -2.90473521e-01 2.79951692e-01 2.95475535e-02 3.84914666e-01 -1.02218783e+00 6.86996937e-01 -4.09327865e-01 -2.10622922e-01 6.99854076e-01 1.20596957e+00 -9.52917457e-01 -1.29697835e+00 -3.28194201e-01 8.42594087e-01 -6.48860216e-01 3.21920484e-01 -4.68884975e-01 2.85408258e-01 1.75525367e-01 1.31427991e+00 4.05471027e-01 -6.32625371e-02 1.41547531e-01 -9.79281068e-02 1.69509053e-01 -5.82302451e-01 -6.15499735e-01 1.12217702e-01 -1.98322028e-01 -5.50589800e-01 -5.33348560e-01 -6.80595100e-01 -1.34642482e+00 -1.20689321e+00 -4.68865663e-01 8.40619028e-01 4.56418544e-01 5.77471793e-01 4.54795152e-01 -2.09884256e-01 9.54520822e-01 -2.55298227e-01 -5.15430391e-01 -5.19141376e-01 -1.00583029e+00 2.64415145e-01 1.73548639e-01 1.56227639e-02 -4.13930357e-01 8.22942238e-04]	[6.642625331878662, 4.935529708862305]
b309e036-05b2-4e37-9b83-2d1db2513964	universal-representation-for-code	2103.03116	null	https://arxiv.org/abs/2103.03116v1	https://arxiv.org/pdf/2103.03116v1.pdf	Universal Representation for Code	Learning from source code usually requires a large amount of labeled data. Despite the possible scarcity of labeled data, the trained model is highly task-specific and lacks transferability to different tasks. In this work, we present effective pre-training strategies on top of a novel graph-based code representation, to produce universal representations for code. Specifically, our graph-based representation captures important semantics between code elements (e.g., control flow and data flow). We pre-train graph neural networks on the representation to extract universal code properties. The pre-trained model then enables the possibility of fine-tuning to support various downstream applications. We evaluate our model on two real-world datasets -- spanning over 30M Java methods and 770K Python methods. Through visualization, we reveal discriminative properties in our universal code representation. By comparing multiple benchmarks, we demonstrate that the proposed framework achieves state-of-the-art results on method name prediction and code graph link prediction.	['Srinivasan Sengamedu', 'George Karypis', 'Hoan Nguyen', 'Linfeng Liu']	2021-03-04	null	null	null	null	['method-name-prediction']	['natural-language-processing']	[ 1.40148833e-01 2.30432466e-01 -7.30854571e-01 -4.17139739e-01 -6.91759825e-01 -7.68031001e-01 4.19004440e-01 5.27755797e-01 3.83688927e-01 2.05778360e-01 1.77606747e-01 -7.43997514e-01 1.03410922e-01 -7.97036111e-01 -8.52550209e-01 -1.09052233e-01 -4.18370306e-01 3.82134807e-03 2.43735060e-01 -3.72484922e-02 5.98772526e-01 2.67549843e-01 -1.53507364e+00 4.62981939e-01 9.09172416e-01 6.37458086e-01 2.21704200e-01 5.57283044e-01 -4.84014988e-01 1.24356639e+00 -4.43198204e-01 -4.58486557e-01 -1.75099764e-02 -3.17864329e-01 -9.68973517e-01 -1.45912871e-01 6.39893889e-01 -1.15572333e-01 -4.15570766e-01 1.04340518e+00 1.31760299e-01 -5.31704910e-02 6.76740050e-01 -1.24010754e+00 -8.42919827e-01 1.00217533e+00 -7.13804305e-01 8.67905468e-02 3.24835092e-01 5.02588339e-02 1.42205620e+00 -7.07596183e-01 7.72695065e-01 8.59670699e-01 8.72805059e-01 6.34386778e-01 -1.34475780e+00 -4.84204262e-01 -3.44917774e-02 3.49865183e-02 -1.07951188e+00 -3.76270652e-01 7.49797225e-01 -8.87055695e-01 1.21036041e+00 4.47439626e-02 2.79671937e-01 9.23576236e-01 1.14906333e-01 5.97459257e-01 5.93818724e-01 -2.61788309e-01 -5.93696628e-03 1.50151858e-02 5.00864685e-01 1.33905494e+00 4.53849494e-01 -2.96765983e-01 -3.36211532e-01 -4.09219563e-01 5.35506725e-01 2.71713465e-01 -2.60899693e-01 -7.29566157e-01 -1.14691842e+00 8.23553383e-01 6.84174418e-01 2.39724055e-01 2.46827647e-01 6.21389449e-01 9.38962698e-01 2.43021503e-01 1.81395829e-01 5.09613752e-01 -6.06560409e-01 -3.15678418e-01 -9.32697713e-01 -1.26260281e-01 1.02318680e+00 1.52682590e+00 1.39243746e+00 1.18994527e-01 -2.76262879e-01 8.24146688e-01 3.43199104e-01 1.95437044e-01 6.55997396e-01 -6.32002532e-01 8.78922880e-01 1.19663966e+00 -5.69901288e-01 -1.27365494e+00 -3.58065873e-01 -3.91134590e-01 -5.54976583e-01 -9.51680318e-02 2.39171863e-01 1.86677128e-01 -5.83370626e-01 1.51107430e+00 -1.07320234e-01 8.28164667e-02 -2.19199881e-01 3.77329946e-01 1.00237417e+00 3.80618632e-01 5.15077747e-02 2.40369812e-01 1.04284513e+00 -1.39129627e+00 -2.24002644e-01 -2.64008790e-01 1.27077985e+00 -4.92664695e-01 1.23234153e+00 -4.41510044e-02 -6.04719937e-01 -5.43427229e-01 -8.72659028e-01 -2.02407688e-01 -3.61737162e-01 4.26848590e-01 9.34392393e-01 5.77744603e-01 -9.95982051e-01 6.40650094e-01 -8.23698938e-01 -4.97300655e-01 4.82909799e-01 3.35983634e-01 -4.42926168e-01 -8.66783857e-02 -4.82088596e-01 4.37743455e-01 3.95042598e-01 -4.32809263e-01 -1.23400247e+00 -7.39162028e-01 -1.09059215e+00 3.88716251e-01 3.99114430e-01 -4.01292861e-01 1.13160920e+00 -8.12450588e-01 -1.27725732e+00 1.04817927e+00 1.14231437e-01 -1.57228678e-01 4.11449485e-02 -2.93528177e-02 -3.10376376e-01 -1.34245735e-02 1.80457115e-01 1.22639745e-01 7.23125458e-01 -1.30142379e+00 -3.76818389e-01 -1.15617752e-01 3.73612255e-01 -5.91140687e-01 -7.69862235e-01 9.78887156e-02 -6.48666561e-01 -7.86674201e-01 -3.08206350e-01 -9.51334834e-01 -1.47022502e-02 -1.06519267e-01 -7.06355214e-01 -1.72237769e-01 6.31483257e-01 -7.03075409e-01 1.67107546e+00 -2.21663976e+00 2.02452987e-01 2.65753627e-01 6.92478240e-01 7.01946914e-02 -3.46966207e-01 6.33545399e-01 -1.61812842e-01 3.04784358e-01 -4.01010126e-01 -1.96105957e-01 1.73251048e-01 1.68663085e-01 -2.59127110e-01 4.77191448e-01 1.92171708e-01 9.49141741e-01 -1.07336843e+00 -5.96402109e-01 -1.16152190e-01 2.12960109e-01 -9.91064548e-01 4.75070000e-01 -4.77559835e-01 1.50613174e-01 -6.19177818e-01 7.22541213e-01 4.08919215e-01 -8.18633735e-01 6.61840737e-01 -4.00316082e-02 1.81298867e-01 6.04074776e-01 -7.19496369e-01 2.16149521e+00 -9.57634687e-01 7.83171117e-01 -2.63454467e-01 -1.21722507e+00 1.16561449e+00 -5.57292141e-02 3.23965013e-01 -2.80675769e-01 -7.44138733e-02 2.24140674e-01 1.21827880e-02 -7.64628589e-01 4.90684032e-01 7.75513530e-01 -3.27568829e-01 7.83036292e-01 3.58158469e-01 1.47342339e-01 3.87244433e-01 4.08440143e-01 1.43826950e+00 4.79223430e-01 3.86405259e-01 -4.96280521e-01 6.20750904e-01 -5.64649813e-02 3.76823604e-01 5.65265417e-01 2.49966383e-01 3.56880575e-01 9.53736603e-01 -4.75576997e-01 -8.30603123e-01 -6.97043300e-01 1.87020048e-01 1.62157083e+00 -3.57877463e-02 -1.22523975e+00 -7.45661318e-01 -1.21487355e+00 2.01153114e-01 6.17267907e-01 -8.15074027e-01 -3.90761465e-01 -7.87305176e-01 -3.41550320e-01 7.47349858e-01 7.33103096e-01 9.54689682e-02 -8.16139042e-01 -4.34351921e-01 3.56593579e-02 1.45276085e-01 -9.30753291e-01 -6.56058550e-01 1.88576177e-01 -1.02067184e+00 -1.38927948e+00 -2.88404822e-01 -1.03621280e+00 9.22826290e-01 3.17262769e-01 1.75621593e+00 6.41581297e-01 -3.23477030e-01 4.10785139e-01 -3.27788353e-01 2.45899290e-01 -8.58918548e-01 4.66560215e-01 -6.23211265e-01 -3.22193682e-01 2.11617351e-01 -6.85969293e-01 -3.90057147e-01 2.11423844e-01 -6.41405582e-01 1.25481144e-01 5.17193973e-01 7.50540733e-01 3.13432306e-01 -4.03779358e-01 3.08574975e-01 -1.35909712e+00 3.71551603e-01 -9.08564508e-01 -7.12058604e-01 4.64201063e-01 -7.30817020e-01 4.41374183e-01 8.95546615e-01 -4.64500844e-01 -8.68994713e-01 4.36349586e-03 2.48988003e-01 -2.63776809e-01 1.67336330e-01 8.24892163e-01 7.18225017e-02 -2.69053161e-01 9.63956714e-01 1.73462555e-01 -2.03874886e-01 -8.12318623e-01 6.19755685e-01 6.32504523e-01 4.62391883e-01 -1.08459675e+00 7.55151093e-01 3.20233405e-02 -6.65837899e-02 -4.82742071e-01 -4.46945846e-01 -4.07720745e-01 -5.34730852e-01 1.39446378e-01 6.00270331e-01 -7.36174226e-01 -5.80403745e-01 1.20293936e-02 -1.22445667e+00 -4.98846442e-01 6.45288527e-02 7.84621835e-02 -6.61847115e-01 4.41287041e-01 -7.41183698e-01 -2.45100379e-01 -3.51502538e-01 -1.41882443e+00 1.06004345e+00 8.80195014e-03 -2.15570480e-02 -1.17336535e+00 2.30604455e-01 2.00534478e-01 4.25306648e-01 1.86731026e-01 1.47042549e+00 -8.10363293e-01 -7.95210779e-01 -9.61960554e-02 -5.36427319e-01 1.67145208e-01 4.19076920e-01 4.13453609e-01 -7.86075950e-01 -3.59615475e-01 -6.63557887e-01 -3.95034641e-01 8.16131413e-01 -3.08395118e-01 1.61045289e+00 -3.70206386e-01 -6.39190972e-01 9.60286558e-01 1.64800906e+00 -3.81844610e-01 4.12342817e-01 2.29276434e-01 1.32352412e+00 3.30557883e-01 9.50113684e-02 6.25816286e-01 5.07574379e-01 7.19007790e-01 7.20470607e-01 1.72555998e-01 -2.89135456e-01 -3.70681465e-01 4.13662672e-01 1.05457556e+00 -1.85498834e-01 6.39647199e-03 -1.37670422e+00 5.95730543e-01 -1.76198518e+00 -5.47686160e-01 -2.90386707e-01 2.08513498e+00 1.05277848e+00 -1.29016250e-01 2.39551261e-01 -3.37749124e-01 7.62541890e-01 -1.80051103e-02 -4.25598562e-01 -3.58381987e-01 4.18379337e-01 1.12565607e-01 5.13834596e-01 8.72226208e-02 -8.60078454e-01 8.85325551e-01 6.14183712e+00 7.50751138e-01 -1.09874618e+00 1.48658291e-01 1.93680018e-01 4.37163383e-01 -5.32723546e-01 2.23006561e-01 -5.80962539e-01 3.63711238e-01 1.10823727e+00 -5.40959001e-01 6.88690782e-01 1.30358613e+00 -3.54988456e-01 5.22331715e-01 -1.49009311e+00 8.45058978e-01 8.74394253e-02 -1.54418564e+00 -1.43348072e-02 -6.03846833e-02 8.65703046e-01 2.48829469e-01 -3.54575574e-01 6.05010152e-01 5.95128238e-01 -8.89163554e-01 6.15486979e-01 2.55325437e-01 9.85307932e-01 -3.59967679e-01 4.02954400e-01 7.95536116e-02 -1.46848011e+00 -1.29149288e-01 -4.29320157e-01 1.38462678e-01 -6.49229050e-01 4.17341977e-01 -8.08559954e-01 6.51154399e-01 5.02334356e-01 1.28114140e+00 -1.15687466e+00 9.09337938e-01 -4.37277019e-01 6.68535888e-01 2.64366448e-01 -9.88004431e-02 1.20829716e-02 8.08661953e-02 3.88223976e-02 1.74961460e+00 3.42611939e-01 -5.85325837e-01 3.32182378e-01 1.15070689e+00 -5.65473080e-01 3.42260450e-01 -8.79709363e-01 -4.92725044e-01 3.66736561e-01 1.44480622e+00 -8.52826715e-01 -4.83187377e-01 -1.03209925e+00 6.78879917e-01 9.58600760e-01 3.86673212e-01 -9.27292109e-01 -5.55246890e-01 6.35875523e-01 -5.81694916e-02 4.20393497e-01 -3.02682489e-01 -1.12376027e-01 -1.51276398e+00 6.60906434e-02 -1.03710556e+00 4.55441356e-01 -3.93704087e-01 -1.14788449e+00 6.46400273e-01 -1.87978536e-01 -1.16374946e+00 -4.02895123e-01 -7.19984829e-01 -6.48883820e-01 6.83138609e-01 -1.35815132e+00 -1.24500406e+00 -5.31442046e-01 4.40561742e-01 2.34196186e-01 -5.20074129e-01 9.90361392e-01 5.36722779e-01 -6.72257960e-01 8.47227454e-01 3.45999867e-01 5.16430795e-01 5.22546709e-01 -1.40788281e+00 7.13451385e-01 7.09927619e-01 3.08517873e-01 1.23230517e+00 3.36288989e-01 -5.25937498e-01 -1.77584839e+00 -1.37606120e+00 3.49122345e-01 -4.49961007e-01 1.03551257e+00 -5.55380106e-01 -1.10944128e+00 1.01060140e+00 1.47763968e-01 5.78001976e-01 8.15722525e-01 2.69055098e-01 -1.18479419e+00 -4.15983424e-02 -7.36772537e-01 2.39678219e-01 1.26762378e+00 -8.86523426e-01 -3.78796488e-01 4.13441688e-01 7.51990616e-01 -2.62360811e-01 -1.10609758e+00 8.61331820e-02 4.44143176e-01 -9.42577064e-01 8.69392753e-01 -1.03271890e+00 9.48647261e-01 -1.41058534e-01 -2.64691472e-01 -1.10038912e+00 -2.99325883e-01 -6.25156462e-01 -5.21644711e-01 1.45137727e+00 4.95856971e-01 -4.58428234e-01 7.30984688e-01 1.80385262e-01 -4.09355342e-01 -8.01148593e-01 -2.50072837e-01 -8.74890327e-01 -7.84585699e-02 -2.05300003e-01 6.71292901e-01 1.28987336e+00 3.34928125e-01 3.22424978e-01 -2.12986857e-01 -1.01842940e-01 5.53250372e-01 7.05711067e-01 1.02759159e+00 -1.14129019e+00 -7.09224939e-01 -6.20568454e-01 -5.89012504e-01 -1.05417275e+00 6.96372867e-01 -1.56489432e+00 -1.80118635e-01 -1.55248058e+00 5.60516655e-01 -5.71896672e-01 -3.20054322e-01 8.89750063e-01 -2.36876786e-01 4.55099009e-02 4.64943014e-02 4.12589341e-01 -6.87206268e-01 2.79432565e-01 8.92214537e-01 -5.71359456e-01 -3.34465690e-02 -1.81336224e-01 -6.69420242e-01 4.96865183e-01 7.41783857e-01 -6.80221856e-01 -5.65197349e-01 -7.63873696e-01 4.92001593e-01 2.18299739e-02 1.15226477e-01 -8.06928754e-01 -8.72134492e-02 -1.45811200e-01 -3.00941765e-01 3.27863656e-02 -3.04735631e-01 -6.49523377e-01 -3.31931002e-02 5.10222673e-01 -5.60579956e-01 2.41002776e-02 3.45118940e-01 6.32165730e-01 -7.03179613e-02 -5.26005805e-01 4.54855859e-01 -1.39383599e-01 -9.71647918e-01 2.75456756e-01 2.47874334e-02 4.53356206e-01 8.25245559e-01 1.83597744e-01 -7.42231429e-01 6.94002658e-02 -2.91566730e-01 -1.64097287e-02 8.10959101e-01 6.42171085e-01 3.46029162e-01 -1.28193259e+00 -4.60539818e-01 1.02634177e-01 7.60561407e-01 -4.84890223e-01 -1.34048253e-01 4.93826091e-01 -7.99533069e-01 1.58409163e-01 -3.41791660e-01 -5.25630057e-01 -1.14555323e+00 1.10053027e+00 1.73385575e-01 -2.81324476e-01 -7.18297124e-01 4.51214314e-01 1.81359574e-01 -6.99881315e-01 5.98507114e-02 -5.26999831e-01 -2.18472317e-01 -3.30811322e-01 3.12922120e-01 3.92094195e-01 7.17082173e-02 -4.64387834e-01 -4.61917639e-01 6.01168036e-01 8.33604336e-02 7.55730808e-01 1.49636638e+00 2.63466775e-01 -6.49530530e-01 4.45837647e-01 1.69590998e+00 2.71541953e-01 -1.04528749e+00 -2.41166562e-01 4.17054743e-01 -5.45027912e-01 -2.17188969e-01 -4.92205560e-01 -1.44708788e+00 1.07193828e+00 9.54621583e-02 3.64162862e-01 8.37830126e-01 1.70355007e-01 4.05182898e-01 7.27918208e-01 6.22142613e-01 -6.14099741e-01 3.04812074e-01 4.14142430e-01 6.45225346e-01 -1.21112239e+00 2.84475330e-02 -6.35908425e-01 -2.94847228e-02 1.50151253e+00 7.21188903e-01 1.63609604e-03 4.97681350e-01 2.12372482e-01 -2.33400330e-01 -4.09481525e-01 -6.92206442e-01 7.86202401e-02 3.99468005e-01 5.02067268e-01 9.27823246e-01 4.98045143e-03 -1.52505711e-02 5.63808799e-01 1.11053273e-01 -1.21105283e-01 6.43571675e-01 1.04085124e+00 -2.25066856e-01 -1.21716714e+00 7.36900195e-02 7.98260093e-01 -2.98605204e-01 -3.44122767e-01 -1.71311826e-01 8.10337484e-01 -2.10215509e-01 5.94770491e-01 -2.53992021e-01 -5.26318669e-01 1.41486496e-01 -5.34591973e-02 4.66533512e-01 -1.14977396e+00 -6.75612569e-01 -5.41677952e-01 1.11019716e-01 -8.41554046e-01 -2.64635593e-01 -2.47657642e-01 -1.29414713e+00 -3.31181198e-01 -2.23467603e-01 5.70809795e-03 5.26076972e-01 4.42993313e-01 7.92221785e-01 8.23978007e-01 3.96270901e-01 -6.62630439e-01 -5.50279558e-01 -8.92345905e-01 -4.22046602e-01 8.66698742e-01 1.55419245e-01 -6.68659449e-01 -2.59651691e-01 4.22536284e-01]	[7.531672954559326, 7.881263256072998]
f1cc7a78-9c41-4ae2-b915-0c22cb63fecf	review-machine-learning-techniques-for	1712.04391	null	http://arxiv.org/abs/1712.04391v2	http://arxiv.org/pdf/1712.04391v2.pdf	Review. Machine learning techniques for traffic sign detection	An automatic road sign detection system localizes road signs from within images captured by an on-board camera of a vehicle, and support the driver to properly ride the vehicle. Most existing algorithms include a preprocessing step, feature extraction and detection step. This paper arranges the methods applied to road sign detection into two groups: general machine learning, neural networks. In this review, the issues related to automatic road sign detection are addressed, the popular existing methods developed to tackle the road sign detection problem are reviewed, and a comparison of the features of these methods is composed.	['Ying Wang', 'Rinat Mukhometzianov']	2017-12-12	null	null	null	null	['traffic-sign-detection']	['computer-vision']	[ 3.37798804e-01 -3.65844399e-01 -8.44062865e-01 -5.91494143e-01 -1.33870557e-01 -2.90467680e-01 7.08233178e-01 -9.09840882e-01 -5.80581129e-01 4.65795666e-01 -2.43613705e-01 -8.06442320e-01 -1.40375167e-01 -5.90390801e-01 -1.71589673e-01 -8.72821569e-01 2.30599970e-01 -1.18549764e-01 4.95071411e-01 -3.04463357e-02 9.60679471e-01 8.84462416e-01 -2.20577788e+00 -4.22967225e-03 6.68978333e-01 8.97628546e-01 -2.55721122e-01 1.14629650e+00 -1.91883400e-01 9.87324774e-01 -4.46300179e-01 2.96690203e-02 4.22835171e-01 -6.60665154e-01 -1.94237441e-01 -6.43667132e-02 1.11889744e+00 -5.85583091e-01 -5.25206804e-01 8.99731696e-01 4.24830765e-01 -1.56744748e-01 1.09116042e+00 -1.74136782e+00 -2.59637594e-01 -2.88812667e-01 -2.46043310e-01 2.05466092e-01 8.19882825e-02 2.81095833e-01 4.88371015e-01 -1.04774702e+00 5.65971792e-01 6.99284434e-01 6.24013722e-01 7.33250201e-01 -7.45151490e-02 -8.18404436e-01 -1.41831771e-01 1.01878369e+00 -1.09099317e+00 -4.58971500e-01 9.07218695e-01 -3.78541499e-01 5.76445758e-01 2.80069292e-01 6.77133739e-01 9.78367031e-02 -7.93435797e-02 1.14804125e+00 1.71283913e+00 -6.80826068e-01 -9.99260768e-02 8.55952948e-02 9.67387974e-01 8.35085750e-01 6.61387980e-01 5.66792667e-01 -1.57136470e-01 2.89321691e-01 3.83120775e-01 -4.67822641e-01 1.01338625e-01 -3.83922398e-01 -7.33095407e-01 4.52638656e-01 1.13023013e-01 2.69164145e-01 -5.33073306e-01 2.26000398e-01 3.02060395e-01 4.19281304e-01 -4.06628996e-01 -1.76722035e-01 -3.60578507e-01 -3.44969988e-01 -8.86331022e-01 2.01479159e-02 8.16488504e-01 6.77385271e-01 6.84741080e-01 4.73959804e-01 5.33237532e-02 4.45428073e-01 5.52322626e-01 1.22056115e+00 1.78070217e-01 -6.61082685e-01 2.45135933e-01 3.02024662e-01 4.19063866e-02 -7.56170392e-01 -2.49176770e-01 4.85722154e-01 -3.04597139e-01 1.07746482e+00 4.80530500e-01 -3.83124501e-01 -1.44966376e+00 4.28503275e-01 3.10988128e-01 4.98077303e-01 2.04682022e-01 7.51173079e-01 1.55307639e+00 4.58262682e-01 -2.98346933e-02 2.33798623e-01 1.23263121e+00 -1.14433730e+00 -1.11562002e+00 -1.89058617e-01 5.38032889e-01 -7.96855092e-01 4.34285939e-01 4.56824780e-01 -6.26317322e-01 -5.43039739e-01 -1.35924256e+00 -1.33434664e-02 -1.19074786e+00 7.48932242e-01 6.47690952e-01 1.31070042e+00 -7.84709275e-01 -6.13763072e-02 -2.01005176e-01 -3.42551529e-01 4.09971744e-01 4.54263836e-01 -2.47617245e-01 -2.81661153e-01 -9.19734776e-01 1.61885583e+00 -1.44362198e-02 8.45604479e-01 -2.83624083e-01 -7.32526556e-02 -7.84557045e-01 -7.59621263e-01 1.03454225e-01 -1.94138065e-01 1.32504880e+00 -7.57055283e-01 -1.71518421e+00 1.20181394e+00 -8.05960059e-01 -9.63161960e-02 6.84404790e-01 -1.52755871e-01 -1.02006757e+00 4.85196523e-02 -5.43388546e-01 2.95723766e-01 1.06920326e+00 -1.07832170e+00 -1.27822220e+00 1.34511128e-01 -5.06506622e-01 -8.29342287e-03 5.84937274e-01 8.12708557e-01 -2.08334684e-01 3.13807160e-01 -1.96000874e-01 -7.09874153e-01 5.04326038e-02 7.83002600e-02 -1.90127119e-02 -5.06743014e-01 1.75968850e+00 -6.92206621e-01 1.13919032e+00 -1.63480437e+00 -9.46809947e-01 7.28109300e-01 -2.49384567e-02 1.25425112e+00 -1.00740142e-01 1.38211638e-01 -5.51473796e-02 -3.50428343e-01 -7.74108917e-02 3.43552619e-01 -8.26452300e-03 4.58763719e-01 -9.97668579e-02 6.93449080e-01 1.44410096e-02 1.24315953e+00 -5.64952135e-01 -5.24468720e-01 8.27359200e-01 3.97123069e-01 7.57030547e-01 -1.65016145e-01 8.98594737e-01 -1.52533621e-01 -3.63212824e-01 1.03094280e+00 1.11720526e+00 6.10622466e-01 -5.88746965e-01 -1.19906329e-01 -8.68592858e-01 2.44169563e-01 -1.33921134e+00 -3.30793634e-02 -1.38647377e-01 1.59181654e+00 2.39197269e-01 -8.79287302e-01 1.24879193e+00 1.16791584e-01 1.08537033e-01 -8.65017653e-01 2.55408198e-01 8.27515602e-01 1.30469829e-01 -8.97564352e-01 4.14146900e-01 2.78892100e-01 5.10042608e-01 3.23900849e-01 -6.68695152e-01 -9.28711817e-02 5.24353266e-01 -4.10145432e-01 5.94285727e-01 -1.92710832e-02 5.20875514e-01 5.43611050e-01 1.14653563e+00 2.18999416e-01 7.62521103e-02 6.74429536e-01 -8.28524530e-01 7.36599937e-02 3.44881266e-02 -6.62746131e-01 -6.41404450e-01 -6.53666317e-01 -3.81520510e-01 5.75871050e-01 2.69917190e-01 3.70278597e-01 -5.79510272e-01 -9.51326966e-01 2.71928966e-01 4.35283273e-01 -5.13615489e-01 5.07655628e-02 -1.17645180e+00 -6.06382549e-01 8.10961246e-01 6.87797487e-01 9.47468638e-01 -1.19915628e+00 -8.89697731e-01 -3.68236572e-01 3.48288625e-01 -9.53772366e-01 -4.27920148e-02 -3.04113120e-01 -6.14262700e-01 -1.55982375e+00 -8.69233727e-01 -1.38113248e+00 9.51066136e-01 8.91793132e-01 2.93218046e-01 4.76346016e-01 -5.09085357e-01 4.67249393e-01 -2.12177113e-01 -7.37871528e-01 -4.32176799e-01 -5.55012465e-01 -3.09921622e-01 2.30302095e-01 1.08763599e+00 1.91182837e-01 -4.26925600e-01 7.27784276e-01 -1.39111161e-01 -4.67952102e-01 1.08381605e+00 4.27748442e-01 7.58503601e-02 -2.50218779e-01 4.39490795e-01 -3.16350728e-01 3.80869448e-01 2.42159292e-01 -9.87902880e-01 3.24513823e-01 -8.99967372e-01 -4.13589001e-01 -1.66705921e-01 -3.80095802e-02 -9.77813303e-01 2.20350951e-01 2.72784494e-02 3.06133687e-01 -8.24910581e-01 -1.58241600e-01 -2.65946627e-01 -1.11627388e+00 3.35181981e-01 4.87162113e-01 4.00507420e-01 -1.84818804e-01 7.83695519e-01 1.19709456e+00 6.99175775e-01 5.77242255e-01 1.14563251e+00 4.72592294e-01 4.33412641e-01 -1.34420705e+00 -2.42867577e-03 -1.18841267e+00 -1.01210499e+00 -1.01009142e+00 5.10943472e-01 -2.95823336e-01 -7.47593641e-01 1.43067598e+00 -9.13009524e-01 -2.56249338e-01 -1.97548226e-01 7.92852044e-01 -5.73991060e-01 3.68878394e-01 -1.70441076e-01 -1.10439646e+00 -2.60415882e-01 -5.93025804e-01 6.24562025e-01 7.52071559e-01 1.81841984e-01 -8.69878232e-01 2.17524841e-01 5.79135776e-01 7.00656593e-01 7.81011134e-02 3.59696478e-01 -3.03514719e-01 -7.35625565e-01 -1.05568719e+00 -8.65157425e-01 5.70436299e-01 2.47620896e-01 4.72313344e-01 -1.27729011e+00 6.81143641e-01 -7.47117043e-01 9.36247632e-02 1.13070309e+00 6.47477508e-01 3.27784151e-01 -9.48270932e-02 -5.99250138e-01 4.35756296e-01 1.08803666e+00 8.25262964e-01 1.02099073e+00 5.72896004e-01 5.37400901e-01 6.93058074e-01 9.77824628e-01 -4.59269226e-01 1.59445837e-01 2.01708317e-01 7.57509619e-02 -4.85185176e-01 -7.33691454e-01 -8.09402317e-02 3.38188559e-01 5.78408539e-01 -4.46086317e-01 7.47241974e-02 -7.51845777e-01 3.76590312e-01 -1.54139686e+00 -1.25223231e+00 -1.10126042e+00 1.90023541e+00 -2.16541085e-02 -7.36788288e-02 3.81898910e-01 8.45843554e-01 8.10251653e-01 -1.71662436e-03 -2.49648884e-01 -8.34526777e-01 -3.87058556e-01 -2.72562150e-02 1.17589724e+00 6.94504797e-01 -1.42821395e+00 9.18944478e-01 7.85738564e+00 4.38652247e-01 -1.50299418e+00 -2.05628708e-01 -7.16454163e-02 6.21886671e-01 4.97398168e-01 -1.37758508e-01 -1.17482352e+00 1.87083200e-01 7.15565562e-01 -7.16695562e-03 -2.61998415e-01 8.29155028e-01 5.87720931e-01 -4.34222132e-01 -4.71263975e-01 9.03698087e-01 5.69478035e-01 -1.01030529e+00 -2.40166977e-01 1.06800586e-01 6.04487360e-01 1.82863384e-01 1.64519832e-01 1.81463882e-01 -1.15870170e-01 -8.67952049e-01 1.83665812e-01 7.73885787e-01 6.60958886e-01 -4.47240949e-01 1.08448744e+00 5.85277490e-02 -1.40952957e+00 -1.15214251e-01 1.05615385e-01 -2.57074684e-01 5.33850431e-01 1.22541957e-01 -9.20316100e-01 1.85550824e-01 -6.46076426e-02 8.86927843e-01 -7.57448435e-01 2.19443583e+00 -9.58076000e-01 8.02640498e-01 -3.57797056e-01 -6.62375987e-01 5.05250037e-01 -4.77117866e-01 4.60296035e-01 1.56335378e+00 6.68364018e-02 -2.42720649e-01 -2.16474414e-01 2.67095864e-01 5.62471926e-01 2.14052483e-01 -9.13675904e-01 3.04933190e-01 -9.99431405e-03 1.23002434e+00 -5.89872956e-01 -5.76682508e-01 -7.60783076e-01 6.26617849e-01 -7.51470864e-01 5.85161030e-01 -7.74572313e-01 -1.30384946e+00 4.79790241e-01 6.47860169e-02 3.34374100e-01 -2.37608701e-01 -4.81369883e-01 -4.56403017e-01 2.84995973e-01 -3.86809438e-01 2.45408997e-01 -8.91148448e-01 -5.02331674e-01 -1.41123116e-01 1.30778432e-01 -1.62710071e+00 -8.92125368e-02 -1.48307312e+00 -1.26728129e+00 7.55027175e-01 -2.55396295e+00 -1.25339830e+00 -6.61580086e-01 2.60946810e-01 3.33146483e-01 -3.37245375e-01 2.09126279e-01 5.48369944e-01 -5.65574706e-01 5.10058522e-01 1.89266175e-01 5.56287348e-01 6.33427501e-01 -9.28834677e-01 3.73019189e-01 1.09482062e+00 -1.43613040e-01 -3.47025506e-02 1.13555178e-01 -6.26707792e-01 -1.24980199e+00 -7.01409340e-01 1.58110178e+00 -3.64009440e-01 3.58857095e-01 4.32240576e-01 -4.95950907e-01 3.89038354e-01 2.01920390e-01 1.65388599e-01 2.58405119e-01 -5.15535533e-01 -2.56724477e-01 -4.24551189e-01 -9.79829192e-01 5.05113065e-01 7.43754685e-01 -2.44881868e-01 -8.54639292e-01 -6.01316616e-02 -6.77682638e-01 -8.49286467e-02 1.13152280e-01 3.05409670e-01 1.17169428e+00 -5.20123184e-01 1.01548636e+00 -6.43475473e-01 -4.43435252e-01 -7.88300157e-01 5.46577036e-01 -6.91945612e-01 3.35599072e-02 -6.74410880e-01 -1.54985443e-01 7.08321333e-01 5.19252419e-01 -1.06077421e+00 1.07897151e+00 7.35553801e-01 -2.21554294e-01 -2.14002088e-01 -9.70766544e-01 -9.50113058e-01 -2.30993360e-01 -5.65774679e-01 1.21517085e-01 3.31136435e-01 5.41615449e-02 -1.00814536e-01 -4.15358901e-01 -1.55497834e-01 6.68061912e-01 -1.95703551e-01 1.17451370e+00 -1.26666355e+00 8.57323289e-01 -1.25304091e+00 -1.08469558e+00 -1.32556355e+00 2.02840311e-03 -3.98089707e-01 4.50998515e-01 -1.83699465e+00 -4.20117795e-01 -1.85226817e-02 -2.49030635e-01 5.09100556e-01 -1.13030925e-01 3.31995219e-01 7.28303492e-02 -3.80635299e-02 -3.65644097e-01 -8.85167941e-02 1.32624102e+00 -1.69052094e-01 -6.88800216e-02 6.11968040e-01 -9.44769010e-03 1.12604618e+00 9.19806302e-01 -1.31483346e-01 2.58204881e-02 2.81866133e-01 -1.12489842e-01 -7.54820943e-01 6.07456326e-01 -8.96018803e-01 6.77018762e-01 -2.26911306e-01 8.24847296e-02 -1.43669724e+00 1.54656783e-01 -8.33816946e-01 -7.79637158e-01 7.50878394e-01 1.20961979e-01 -1.80714712e-01 5.24741821e-02 2.30261236e-01 -5.45735061e-01 -5.23132086e-01 1.06004417e+00 4.39228743e-01 -1.72498667e+00 -1.90858319e-01 -1.18076289e+00 -4.70166385e-01 1.30167294e+00 -1.30268180e+00 -4.67120230e-01 -4.12790388e-01 -7.96834677e-02 3.04175645e-01 -3.16796482e-01 4.81670201e-01 1.06743991e+00 -1.32385612e+00 -5.66534221e-01 6.33841097e-01 1.75443098e-01 -6.97464645e-01 -1.07477352e-01 1.20059419e+00 -9.22615170e-01 1.04783821e+00 -3.98017466e-01 -2.75815368e-01 -2.02718902e+00 2.13676125e-01 5.22741914e-01 4.22962368e-01 -4.22519386e-01 4.39225227e-01 -6.08472586e-01 -1.10896766e-01 3.42030138e-01 -5.81611693e-01 -9.64276195e-01 1.22731894e-01 9.27684903e-01 1.23762631e+00 1.01539120e-01 -1.18606353e+00 -4.35438335e-01 1.76074672e+00 3.41842532e-01 -1.73572991e-02 3.95399362e-01 -1.19762056e-01 1.85644642e-01 1.56016141e-01 1.12735152e+00 -1.31671771e-01 -7.74931133e-01 -3.48684378e-02 7.07756728e-02 -5.29662788e-01 1.23584092e-01 -8.22210550e-01 -8.96582186e-01 9.06550109e-01 8.21849048e-01 -2.44573787e-01 9.37797487e-01 -4.27858442e-01 8.47572446e-01 1.07307708e+00 -9.04860254e-03 -1.55461991e+00 -5.19441783e-01 7.42626607e-01 5.31811178e-01 -1.44006193e+00 -7.14025050e-02 -4.70872432e-01 -4.34969515e-01 1.42710721e+00 4.05119479e-01 -2.37101793e-01 1.04343021e+00 2.88725078e-01 8.90263855e-01 -2.12735221e-01 -9.50853899e-02 -1.02674437e+00 7.90835977e-01 9.45226252e-01 -6.32424057e-02 -2.49486212e-02 -6.35655224e-01 -3.24178189e-01 1.64474159e-01 3.52168649e-01 5.86847723e-01 1.19680893e+00 -1.12851107e+00 -1.00779688e+00 -6.80847704e-01 2.98413217e-01 2.14842618e-01 1.62065551e-01 -1.09243762e+00 1.19564795e+00 4.45913285e-01 1.04240084e+00 -7.69957677e-02 -1.25506461e-01 9.20528114e-01 4.43138659e-01 2.07482889e-01 2.12602749e-01 1.31907677e-02 -5.55153191e-01 6.50779009e-01 -3.32386434e-01 -7.78965890e-01 -1.07804132e+00 -1.15598702e+00 3.38539593e-02 -4.80776608e-01 -1.69877812e-01 1.09989774e+00 8.90054345e-01 -1.76340893e-01 -1.03295773e-01 7.22446084e-01 -5.00271499e-01 -5.49937040e-02 -6.31460488e-01 -4.36857164e-01 -1.28054887e-01 8.63583624e-01 -6.29115999e-01 -7.49253094e-01 9.25766155e-02]	[7.96988582611084, -0.8346313834190369]
f4cc5947-51df-4da1-8231-38c4934bd5c4	understanding-expertise-through	2302.07457	null	https://arxiv.org/abs/2302.07457v2	https://arxiv.org/pdf/2302.07457v2.pdf	Understanding Expertise through Demonstrations: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning	Offline inverse reinforcement learning (Offline IRL) aims to recover the structure of rewards and environment dynamics that underlie observed actions in a fixed, finite set of demonstrations from an expert agent. Accurate models of expertise in executing a task has applications in safety-sensitive applications such as clinical decision making and autonomous driving. However, the structure of an expert's preferences implicit in observed actions is closely linked to the expert's model of the environment dynamics (i.e. the ``world''). Thus, inaccurate models of the world obtained from finite data with limited coverage could compound inaccuracy in estimated rewards. To address this issue, we propose a bi-level optimization formulation of the estimation task wherein the upper level is likelihood maximization based upon a conservative model of the expert's policy (lower level). The policy model is conservative in that it maximizes reward subject to a penalty that is increasing in the uncertainty of the estimated model of the world. We propose a new algorithmic framework to solve the bi-level optimization problem formulation and provide statistical and computational guarantees of performance for the associated reward estimator. Finally, we demonstrate that the proposed algorithm outperforms the state-of-the-art offline IRL and imitation learning benchmarks by a large margin, over the continuous control tasks in MuJoCo and different datasets in the D4RL benchmark.	['Mingyi Hong', 'Alfredo Garcia', 'Chenliang Li', 'Siliang Zeng']	2023-02-15	null	null	null	null	['continuous-control', 'd4rl']	['playing-games', 'robots']	[ 1.98439024e-02 3.93114418e-01 -5.97045362e-01 -8.39761347e-02 -8.73358071e-01 -4.67126817e-01 2.96163082e-01 1.14014946e-01 -8.41827035e-01 1.13359785e+00 1.32156322e-02 -1.41552567e-01 -5.50627410e-01 -3.08823884e-01 -1.15906823e+00 -7.71706343e-01 -3.12169641e-01 5.94681740e-01 -1.37334585e-01 -3.71797718e-02 1.63809538e-01 1.43792108e-01 -1.14167249e+00 -1.73219427e-01 1.03728294e+00 1.17410457e+00 4.64668572e-01 6.51095271e-01 5.50006390e-01 1.38022208e+00 -4.51434433e-01 6.58864081e-02 4.38347489e-01 -2.97056705e-01 -5.01845658e-01 1.08051799e-01 -3.09275210e-01 -9.12345469e-01 -4.53095675e-01 1.19792914e+00 3.58008295e-01 3.20199311e-01 4.89764184e-01 -1.32605588e+00 -1.07058950e-01 4.30181950e-01 -3.67055357e-01 -1.45484796e-02 2.33907312e-01 5.64559281e-01 7.66182661e-01 -3.57249111e-01 7.03541994e-01 1.04329407e+00 1.87092170e-01 6.38394654e-01 -1.04903746e+00 -4.05188769e-01 6.45535648e-01 2.34492153e-01 -1.14288890e+00 -2.14988515e-01 4.97547626e-01 -5.37448883e-01 6.54580414e-01 -9.86020938e-02 7.45631456e-01 1.41324663e+00 5.92258215e-01 9.48763371e-01 1.40349960e+00 1.16327681e-01 7.27799237e-01 2.78291523e-01 -2.12157428e-01 6.01884902e-01 6.04694635e-02 7.20107794e-01 -5.99153101e-01 -3.23931485e-01 7.80445218e-01 -4.13699076e-02 -1.86128110e-01 -6.57602966e-01 -1.25791669e+00 8.90027821e-01 2.42331013e-01 -4.03330386e-01 -8.89337540e-01 4.92952019e-01 4.19738710e-01 4.48614478e-01 1.71206802e-01 5.38449824e-01 -4.44745868e-01 -4.18050528e-01 -3.66333187e-01 5.95606565e-01 7.67640889e-01 1.06947184e+00 2.53868073e-01 7.88262933e-02 -4.72599179e-01 3.14460576e-01 2.79549032e-01 5.88771462e-01 3.16466838e-01 -1.44129133e+00 7.22844183e-01 1.35482386e-01 9.61863101e-01 -4.05432910e-01 -2.58957356e-01 -6.49441838e-01 -2.04281509e-01 5.24008811e-01 6.19005680e-01 -4.63835299e-01 -7.25541294e-01 2.00212288e+00 5.94000578e-01 3.34693640e-01 3.01713407e-01 1.16604459e+00 8.48892927e-02 3.55873793e-01 -4.69666868e-02 -4.69393551e-01 1.10033834e+00 -7.88009822e-01 -7.93935716e-01 -4.64248180e-01 3.53448987e-01 -4.15201373e-02 7.69392371e-01 6.10348105e-01 -1.07970250e+00 -2.53659487e-01 -9.94549990e-01 4.76205170e-01 3.17717463e-01 2.18874916e-01 2.95713574e-01 9.85593647e-02 -5.39633632e-01 7.96841979e-01 -8.93942595e-01 1.86026499e-01 4.02181447e-01 4.19623345e-01 -1.03553742e-01 -1.53486372e-03 -1.33930397e+00 1.26205528e+00 4.12944645e-01 1.80799156e-01 -1.87873673e+00 -7.52483249e-01 -6.74595237e-01 -1.04671316e-02 1.25190079e+00 -4.72453147e-01 1.57817686e+00 -8.61195326e-01 -1.61229837e+00 2.27664500e-01 2.53582865e-01 -8.24093461e-01 1.08494008e+00 -4.09803331e-01 -9.29008983e-03 1.63051412e-01 1.63083628e-01 4.63672161e-01 1.12291801e+00 -1.02377975e+00 -7.51523137e-01 -3.86480868e-01 3.60495895e-01 6.66988254e-01 3.19512218e-01 -4.64536607e-01 -1.03046156e-01 -3.10873866e-01 -5.40851474e-01 -1.20619118e+00 -5.04073322e-01 3.72708216e-02 -1.73580989e-01 -2.75765091e-01 3.86286855e-01 -7.16925263e-01 8.64489436e-01 -1.91045165e+00 3.06475192e-01 1.70930505e-01 1.40096962e-01 -1.77669466e-01 -6.68593347e-02 3.04919988e-01 3.00786436e-01 -4.86220181e-01 -4.06889021e-02 -2.05514297e-01 1.03489727e-01 3.39601785e-01 -4.94861186e-01 7.29519665e-01 -3.84102911e-02 7.79873610e-01 -1.32053721e+00 -3.24377447e-01 1.83251560e-01 -5.81414718e-03 -4.06789809e-01 4.43013906e-01 -5.55651367e-01 8.83202672e-01 -1.07941759e+00 3.27383667e-01 8.27036947e-02 -8.91801640e-02 2.70295501e-01 1.86684474e-01 -6.18055537e-02 1.34739935e-01 -1.18587077e+00 1.72297037e+00 -4.87392634e-01 9.10802484e-02 1.70891538e-01 -1.05036759e+00 5.01745164e-01 4.45395410e-01 7.67912984e-01 -5.96804857e-01 2.19909459e-01 1.63561270e-01 2.52639353e-01 -6.04226887e-01 2.56797969e-01 -9.22112390e-02 -1.57591283e-01 4.82352823e-01 -1.02376290e-01 -1.46420881e-01 -8.20307136e-02 1.22199275e-01 1.26428854e+00 5.38352549e-01 4.62122649e-01 -1.32173777e-01 2.95887262e-01 7.39314258e-02 8.13427985e-01 1.18351138e+00 -5.69987714e-01 -1.07341118e-01 7.94715166e-01 -1.97889611e-01 -8.93982172e-01 -8.62651229e-01 6.82303011e-02 7.67528057e-01 2.21211374e-01 3.18070024e-01 -7.09151328e-01 -8.58880877e-01 3.69628996e-01 1.03031194e+00 -8.34497631e-01 -3.44641536e-01 -4.01352525e-01 -3.24022770e-01 8.50150585e-02 5.84304631e-01 2.20906153e-01 -1.14969397e+00 -1.20116460e+00 4.23380941e-01 -9.82022285e-02 -1.20493531e+00 -6.98659837e-01 1.89307749e-01 -6.90645933e-01 -1.12625360e+00 -4.81267959e-01 -6.41379356e-02 7.56709754e-01 -3.16058964e-01 9.24268246e-01 -4.57146764e-01 -1.54900685e-01 7.97659516e-01 -6.09636232e-02 -6.62196875e-01 -3.82523656e-01 -3.37696105e-01 4.51204300e-01 7.10797608e-02 -1.37203723e-01 -1.47975817e-01 -7.85252273e-01 2.70063847e-01 -5.64895034e-01 -1.01225071e-01 6.55148089e-01 1.01626945e+00 7.95209169e-01 4.79719006e-02 8.53502095e-01 -7.67945945e-01 8.43750536e-01 -7.39398062e-01 -1.10806382e+00 2.48652190e-01 -7.64157474e-01 4.45204437e-01 7.18771160e-01 -7.93012738e-01 -1.18734360e+00 2.51876652e-01 3.16518158e-01 -8.91593277e-01 1.95049271e-01 4.69079435e-01 1.37657464e-01 2.22860724e-01 3.81191403e-01 3.37389737e-01 3.80354881e-01 -1.46887779e-01 1.10834755e-01 4.01537627e-01 4.78515953e-01 -1.01871741e+00 4.05012518e-01 3.17069262e-01 1.22880809e-01 -3.00434172e-01 -1.02301288e+00 -2.33335555e-01 -1.92438841e-01 -4.41740274e-01 6.73073113e-01 -1.07021999e+00 -1.31929421e+00 2.63546437e-01 -8.52188706e-01 -6.75666273e-01 -7.03668535e-01 8.71026695e-01 -1.41321075e+00 2.24197153e-02 -2.40604743e-01 -1.28070557e+00 3.19823436e-02 -1.55205381e+00 9.51506793e-01 1.25036955e-01 2.40894780e-03 -8.59604597e-01 1.64424896e-01 3.41083795e-01 -3.44331302e-02 4.27035064e-01 5.34093559e-01 -4.16316181e-01 -7.90715337e-01 -1.17378205e-01 2.88807392e-01 4.20389771e-01 -7.43478164e-02 -6.90376222e-01 -7.37286091e-01 -4.85740840e-01 4.74563926e-01 -6.87671721e-01 3.89423698e-01 5.20108104e-01 1.21467268e+00 -6.26247942e-01 -2.02330336e-01 1.18627831e-01 1.26890099e+00 5.52759111e-01 1.99267834e-01 3.64794940e-01 2.49590844e-01 6.26640856e-01 1.41768432e+00 9.38233733e-01 3.53319526e-01 5.74421048e-01 8.88977349e-01 5.01316011e-01 6.15429282e-01 -5.07542789e-01 6.51380181e-01 1.90415263e-01 -3.98360975e-02 -7.67263770e-02 -4.03987020e-01 4.94193226e-01 -2.40759063e+00 -8.28217089e-01 4.78180617e-01 2.53723955e+00 8.62210631e-01 8.70238543e-02 1.27518520e-01 -4.89924967e-01 4.34194446e-01 1.58594716e-02 -1.72195303e+00 -2.45439827e-01 4.43897426e-01 -3.33085865e-01 8.71472597e-01 5.22444904e-01 -7.64674664e-01 4.34749961e-01 5.88964128e+00 8.07326972e-01 -6.80739462e-01 1.85166776e-01 5.91650605e-01 -4.00950521e-01 -5.52050620e-02 -1.76878691e-01 -7.42746592e-01 6.53792977e-01 9.76882398e-01 -3.18875670e-01 9.76278007e-01 1.03062809e+00 6.21654510e-01 -4.71894950e-01 -1.62568331e+00 6.74474418e-01 -3.68454784e-01 -1.01949084e+00 -6.46444321e-01 3.93274903e-01 7.21396446e-01 2.28057981e-01 2.39372373e-01 6.22545600e-01 6.50925815e-01 -9.51993346e-01 1.04610515e+00 8.01224887e-01 7.37187922e-01 -8.59906793e-01 6.04410529e-01 1.05925286e+00 -7.48906672e-01 -5.57269394e-01 -1.21965595e-01 1.43178236e-02 -1.54618267e-02 1.31989956e-01 -9.41321850e-01 3.90685260e-01 3.64358574e-01 5.64670563e-01 2.49350771e-01 5.19763589e-01 -3.65556628e-01 3.31635237e-01 -1.57128081e-01 -2.04133183e-01 5.11816323e-01 -3.59388560e-01 7.62731850e-01 4.23662752e-01 8.56839642e-02 1.48338377e-01 4.47254062e-01 1.06667733e+00 7.03310817e-02 -2.79670268e-01 -5.50200880e-01 -1.35643512e-01 4.18931633e-01 8.77591372e-01 -1.39517009e-01 -2.15118036e-01 -1.36880234e-01 5.67392766e-01 6.26359761e-01 4.13617402e-01 -1.13342285e+00 1.55616432e-01 7.83020735e-01 -2.43143797e-01 9.34120566e-02 -1.11870371e-01 1.09024569e-01 -8.91912401e-01 2.11018577e-01 -1.11079240e+00 3.49886686e-01 -5.63486814e-01 -9.47881520e-01 1.79859444e-01 1.83757722e-01 -1.37819612e+00 -8.23987424e-01 -5.82946241e-01 -2.64105469e-01 8.36143076e-01 -1.46934998e+00 -3.52687150e-01 2.12729216e-01 5.11101604e-01 6.12454772e-01 -1.07470773e-01 3.83243710e-01 -2.38898814e-01 -5.01682580e-01 2.36095458e-01 4.50469762e-01 -1.96722776e-01 3.86881769e-01 -1.30012369e+00 -1.72279745e-01 3.83182496e-01 -4.56758648e-01 1.34426638e-01 8.78618598e-01 -8.10491621e-01 -1.81548607e+00 -1.01769471e+00 -1.03672346e-05 -4.46974188e-01 8.18841219e-01 -8.14767778e-02 -6.07380390e-01 7.35751927e-01 -2.80541360e-01 2.80661732e-01 -5.70629761e-02 -3.71863097e-01 2.41719648e-01 -9.84841809e-02 -1.45805871e+00 4.89507049e-01 7.18761444e-01 -4.12316144e-01 -4.04101729e-01 4.90075171e-01 6.38994098e-01 -8.84915829e-01 -9.61244822e-01 2.64246672e-01 6.94314480e-01 -5.06787896e-01 8.43867719e-01 -9.99552071e-01 4.39054489e-01 -1.37993708e-01 1.22239940e-01 -1.59346461e+00 5.60950190e-02 -7.75981069e-01 -6.26651764e-01 3.73852521e-01 1.44299701e-01 -7.57516384e-01 7.50211000e-01 8.66389751e-01 -4.63628434e-02 -1.18886638e+00 -1.25501120e+00 -1.01658416e+00 -1.19214401e-01 -3.36458266e-01 2.79423714e-01 5.19491017e-01 -2.59398036e-02 -1.61234424e-01 -8.84440660e-01 2.67684132e-01 1.01098657e+00 7.53125474e-02 5.79691887e-01 -7.24914908e-01 -6.64726973e-01 8.97330940e-02 1.14490978e-01 -1.10039270e+00 6.19132459e-01 -4.32557613e-01 5.65210462e-01 -1.22845602e+00 2.43918419e-01 -5.42373657e-01 -5.23252249e-01 1.65441975e-01 -1.81384921e-01 -7.54113972e-01 2.09530368e-01 1.15174681e-01 -7.81482160e-01 7.93108642e-01 1.65502787e+00 -2.29514912e-01 -2.43001670e-01 3.20895165e-01 -4.50655222e-01 6.60222411e-01 7.25668013e-01 -6.81967676e-01 -8.20344806e-01 -2.73476213e-01 1.25454083e-01 8.23355794e-01 2.89253145e-01 -5.65577388e-01 2.38206565e-01 -7.52536356e-01 5.11807725e-02 -4.64609385e-01 6.09771073e-01 -9.56315577e-01 9.51327607e-02 8.33241463e-01 -7.71883011e-01 -2.48596698e-01 -1.45544484e-01 1.12797856e+00 1.51852623e-01 -4.35725123e-01 7.36258507e-01 -3.56286168e-01 -5.60709774e-01 5.30567467e-01 -3.19342822e-01 3.77843112e-01 1.28051424e+00 2.58890778e-01 -2.31273279e-01 -6.39612317e-01 -8.25275421e-01 9.13643777e-01 1.39477968e-01 3.55935186e-01 6.94546580e-01 -1.10293937e+00 -6.83502853e-01 -2.70543575e-01 -3.52015346e-02 5.51997721e-02 2.66997099e-01 1.05146563e+00 7.71445110e-02 4.98111635e-01 -1.41530633e-01 -3.58639628e-01 -6.89298749e-01 6.43102109e-01 6.80913866e-01 -6.62705600e-01 -4.92583990e-01 3.39542180e-01 4.44672048e-01 -2.86032498e-01 4.55958039e-01 -3.67127091e-01 -2.97616646e-02 -2.67773151e-01 2.90643305e-01 7.21167147e-01 -2.40550309e-01 -3.35990280e-01 -2.15762109e-01 -4.24169116e-02 -4.07821275e-02 -2.46960282e-01 1.27695227e+00 -1.10872895e-01 5.23600757e-01 5.92610478e-01 7.55879343e-01 -4.40581888e-01 -2.18414783e+00 -2.85471499e-01 -1.01920992e-01 -3.85810584e-01 2.98311561e-01 -1.05125666e+00 -5.98687887e-01 3.75432730e-01 5.83125234e-01 -2.35391989e-01 7.15074122e-01 -1.86289728e-01 4.40506130e-01 6.54356897e-01 8.03183973e-01 -1.73395169e+00 1.58830777e-01 2.37703934e-01 1.05718517e+00 -1.38733947e+00 4.01570797e-02 1.74295217e-01 -1.22284782e+00 6.42498851e-01 8.09707820e-01 -2.40903959e-01 4.08834815e-01 1.96194157e-01 -2.14654177e-01 1.25588790e-01 -1.18313217e+00 -9.73896459e-02 2.26784706e-01 4.00089473e-01 -3.66367429e-01 3.73215675e-01 -4.71097156e-02 5.78203917e-01 3.48663419e-01 2.60402143e-01 4.91258413e-01 9.64605033e-01 -4.03611511e-01 -7.53498018e-01 -4.32926834e-01 5.48291802e-01 -3.11165541e-01 3.27519894e-01 6.47174194e-02 7.59826720e-01 9.71831288e-03 7.51168311e-01 -1.50724530e-01 8.90681520e-02 3.01339507e-01 -2.32760698e-01 6.26571298e-01 -4.18366462e-01 -1.27357915e-01 -3.29650640e-02 1.01705581e-01 -1.10038698e+00 -1.36728242e-01 -8.02511930e-01 -1.37881577e+00 2.74171829e-01 -1.19242407e-01 1.75668165e-01 7.19058633e-01 1.09281123e+00 2.73081630e-01 5.92459559e-01 9.85710740e-01 -7.67572045e-01 -1.69584715e+00 -7.04906642e-01 -8.02745819e-01 1.83881044e-01 6.53135598e-01 -1.01047003e+00 -3.26711029e-01 -3.89458269e-01]	[4.159605026245117, 2.2401249408721924]

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.