Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2112.12582	Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs	Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. T...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,006
2409.12500	LLMR: Knowledge Distillation with a Large Language Model-Induced Reward	Large language models have become increasingly popular and demonstrated remarkable performance in various natural language processing (NLP) tasks. However, these models are typically computationally expensive and difficult to be deployed in resource-constrained environments. In this paper, we propose LLMR, a novel know...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	489,620
1507.01716	Temporal-varying failures of nodes in networks	We consider networks in which random walkers are removed because of the failure of specific nodes. We interpret the rate of loss as a measure of the importance of nodes, a notion we denote as failure-centrality. We show that the degree of the node is not sufficient to determine this measure and that, in a first approxi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	44,898
1111.6087	Fast Distributed Computation of Distances in Networks	This paper presents a distributed algorithm to simultaneously compute the diameter, radius and node eccentricity in all nodes of a synchronous network. Such topological information may be useful as input to configure other algorithms. Previous approaches have been modular, progressing in sequential phases using buildin...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	13,181
2312.06633	Examining the Effect of Implementation Factors on Deep Learning Reproducibility	Reproducing published deep learning papers to validate their conclusions can be difficult due to sources of irreproducibility. We investigate the impact that implementation factors have on the results and how they affect reproducibility of deep learning studies. Three deep learning experiments were ran five times each ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	414,599
2412.14088	Joint Perception and Prediction for Autonomous Driving: A Survey	Perception and prediction modules are critical components of autonomous driving systems, enabling vehicles to navigate safely through complex environments. The perception module is responsible for perceiving the environment, including static and dynamic objects, while the prediction module is responsible for predicting...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	518,567
2104.03899	Unsupervised Speech Representation Learning for Behavior Modeling using Triplet Enhanced Contextualized Networks	Speech encodes a wealth of information related to human behavior and has been used in a variety of automated behavior recognition tasks. However, extracting behavioral information from speech remains challenging including due to inadequate training data resources stemming from the often low occurrence frequencies of sp...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	229,216
2306.05881	Nonlinear Stability Assessment Of Type-4 Wind Turbines During Unbalanced Grid Faults Based On Reduced-Order Model	As the number of converter-based renewable generations in the power system is increasing, the inertia provided by the synchronous generators is reducing, which in turn is reducing the stability margins of the power system. In order to assess the large-signal stability, it is essential to model the wind power plant conn...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	372,371
2301.02781	Knowledge Reasoning via Jointly Modeling Knowledge Graphs and Soft Rules	Knowledge graphs (KGs) play a crucial role in many applications, such as question answering, but incompleteness is an urgent issue for their broad application. Much research in knowledge graph completion (KGC) has been performed to resolve this issue. The methods of KGC can be classified into two major categories: rule...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	339,594
1010.0189	Reed-Muller Codes for Peak Power Control in Multicarrier CDMA	Reed-Muller codes are studied for peak power control in multicarrier code-division multiple access (MC-CDMA) communication systems. In a coded MC-CDMA system, the information data multiplexed from users is encoded by a Reed-Muller subcode and the codeword is fully-loaded to Walsh-Hadamard spreading sequences. The polyn...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,749
2301.08102	Geometric path augmentation for inference of sparsely observed stochastic nonlinear systems	Stochastic evolution equations describing the dynamics of systems under the influence of both deterministic and stochastic forces are prevalent in all fields of science. Yet, identifying these systems from sparse-in-time observations remains still a challenging endeavour. Existing approaches focus either on the tempora...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	341,094
1901.10423	A Minimalistic Approach to Segregation in Robot Swarms	We present a decentralized algorithm to achieve segregation into an arbitrary number of groups with swarms of autonomous robots. The distinguishing feature of our approach is in the minimalistic assumptions on which it is based. Specifically, we assume that (i) Each robot is equipped with a ternary sensor capable of de...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	120,014
1910.09952	Convolutional Neural Networks for Space-Time Block Coding Recognition	We apply the latest advances in machine learning with deep neural networks to the tasks of radio modulation recognition, channel coding recognition, and spectrum monitoring. This paper first proposes an identification algorithm for space-time block coding of a signal. The feature between spatial multiplexing and Alamou...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	150,348
2311.13507	Applying Dimensionality Reduction as Precursor to LSTM-CNN Models for Classifying Imagery and Motor Signals in ECoG-Based BCIs	Motor impairments, frequently caused by neurological incidents like strokes or traumatic brain injuries, present substantial obstacles in rehabilitation therapy. This research aims to elevate the field by optimizing motor imagery classification algorithms within Brain-Computer Interfaces (BCIs). By improving the effici...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	409,759
1906.00912	Temporal Density Extrapolation using a Dynamic Basis Approach	Density estimation is a versatile technique underlying many data mining tasks and techniques,ranging from exploration and presentation of static data, to probabilistic classification, or identifying changes or irregularities in streaming data. With the pervasiveness of embedded systems and digitisation, this latter typ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	133,542
1907.04924	Infer Implicit Contexts in Real-time Online-to-Offline Recommendation	Understanding users' context is essential for successful recommendations, especially for Online-to-Offline (O2O) recommendation, such as Yelp, Groupon, and Koubei. Different from traditional recommendation where individual preference is mostly static, O2O recommendation should be dynamic to capture variation of users' ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	138,235
2306.02015	Machine learning enabled experimental design and parameter estimation for ultrafast spin dynamics	Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and material physics, which often suffer from the scarcity of facility resources and increasing complexities. To address the limitations, we introduce a methodology that combines machine...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	370,719
2501.01981	Optical Character Recognition using Convolutional Neural Networks for Ashokan Brahmi Inscriptions	This research paper delves into the development of an Optical Character Recognition (OCR) system for the recognition of Ashokan Brahmi characters using Convolutional Neural Networks. It utilizes a comprehensive dataset of character images to train the models, along with data augmentation techniques to optimize the trai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	522,283
2008.02421	Cross-Model Image Annotation Platform with Active Learning	We have seen significant leapfrog advancement in machine learning in recent decades. The central idea of machine learnability lies on constructing learning algorithms that learn from good data. The availability of more data being made publicly available also accelerates the growth of AI in recent years. In the domain o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	190,606
2107.09770	Faster Matchings via Learned Duals	A recent line of research investigates how algorithms can be augmented with machine-learned predictions to overcome worst case lower bounds. This area has revealed interesting algorithmic insights into problems, with particular success in the design of competitive online algorithms. However, the question of improving a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	247,117
2310.05057	BRAINTEASER: Lateral Thinking Puzzles for Large Language Models	The success of language models has inspired the NLP community to attend to tasks that require implicit and complex reasoning, relying on human-like commonsense mechanisms. While such vertical thinking tasks have been relatively popular, lateral thinking puzzles have received little attention. To bridge this gap, we dev...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	397,959
2210.09721	An incremental input-to-state stability condition for a generic class of recurrent neural networks	This paper proposes a novel sufficient condition for the incremental input-to-state stability of a generic class of recurrent neural networks (RNNs). The established condition is compared with others available in the literature, showing to be less conservative. Moreover, it can be applied for the design of incremental ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	324,639
1007.3906	A colorful origin for the genetic code: Information theory, statistical mechanics and the emergence of molecular codes	The genetic code maps the sixty-four nucleotide triplets (codons) to twenty amino-acids. While the biochemical details of this code were unraveled long ago, its origin is still obscure. We review information-theoretic approaches to the problem of the code's origin and discuss the results of a recent work that treats th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,101
2012.03447	An Improved Benders Decomposition Algorithm for Steady-State Dispatch Problem in an Integrated Electricity-Gas System	Optimally operating an integrated electricity-gas system (IEGS) is significant for the energy sector. However, the IEGS operation model's nonconvexity makes it challenging to solve the optimal dispatch problem in the IEGS. This letter proposes an improved Benders decomposition (IBD) algorithm catering to a commonly use...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	210,117
2303.13703	End-to-End Diffusion Latent Optimization Improves Classifier Guidance	Classifier guidance -- using the gradients of an image classifier to steer the generations of a diffusion model -- has the potential to dramatically expand the creative control over image generation and editing. However, currently classifier guidance requires either training new noise-aware models to obtain accurate gr...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	353,784
2104.14133	Text-to-Text Multi-view Learning for Passage Re-ranking	Recently, much progress in natural language processing has been driven by deep contextualized representations pretrained on large corpora. Typically, the fine-tuning on these pretrained models for a specific downstream task is based on single-view learning, which is however inadequate as a sentence can be interpreted d...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	232,730
2005.02068	Establishing Baselines for Text Classification in Low-Resource Languages	While transformer-based finetuning techniques have proven effective in tasks that involve low-resource, low-data environments, a lack of properly established baselines and benchmark datasets make it hard to compare different approaches that are aimed at tackling the low-resource setting. In this work, we provide three ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	175,748
1707.01219	Like What You Like: Knowledge Distill via Neuron Selectivity Transfer	Despite deep neural networks have demonstrated extraordinary power in various applications, their superior performances are at expense of high storage and computational costs. Consequently, the acceleration and compression of neural networks have attracted much attention recently. Knowledge Transfer (KT), which aims at...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	76,497
2109.08913	Intelligent Reflecting Surface Aided MIMO with Cascaded LoS Links: Channel Modelling and Full Multiplexing Region	This work studies the modelling and the optimization of intelligent reflecting surface (IRS) assisted multiple-input multiple-output (MIMO) systems through cascaded line-of-sight (LoS) links. In Part I of this work, we build up a new IRS-aided MIMO channel model, named the cascaded LoS MIMO channel. The proposed channe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	256,072
2102.00457	MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification	We propose MultiRocket, a fast time series classification (TSC) algorithm that achieves state-of-the-art performance with a tiny fraction of the time and without the complex ensembling structure of many state-of-the-art methods. MultiRocket improves on MiniRocket, one of the fastest TSC algorithms to date, by adding mu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	217,789
2302.13770	Mask Reference Image Quality Assessment	Understanding semantic information is an essential step in knowing what is being learned in both full-reference (FR) and no-reference (NR) image quality assessment (IQA) methods. However, especially for many severely distorted images, even if there is an undistorted image as a reference (FR-IQA), it is difficult to per...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	348,053
2307.06108	Fast Decoding of Lifted Interleaved Linearized Reed-Solomon Codes for Multishot Network Coding	Mart{\'\i}nez-Pe{\~n}as and Kschischang (IEEE Trans.\ Inf.\ Theory, 2019) proposed lifted linearized Reed--Solomon codes as suitable codes for error control in multishot network coding. We show how to construct and decode \ac{LILRS} codes. Compared to the construction by Mart{\'\i}nez-Pe{\~n}as--Kschischang, interleavi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	378,970
2307.05241	Does pre-training on brain-related tasks results in better deep-learning-based brain age biomarkers?	Brain age prediction using neuroimaging data has shown great potential as an indicator of overall brain health and successful aging, as well as a disease biomarker. Deep learning models have been established as reliable and efficient brain age estimators, being trained to predict the chronological age of healthy subjec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	378,668
2409.18866	MCUBench: A Benchmark of Tiny Object Detectors on MCUs	We introduce MCUBench, a benchmark featuring over 100 YOLO-based object detection models evaluated on the VOC dataset across seven different MCUs. This benchmark provides detailed data on average precision, latency, RAM, and Flash usage for various input resolutions and YOLO-based one-stage detectors. By conducting a c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	492,436
2202.06374	Holdouts set for safe predictive model updating	Predictive risk scores for adverse outcomes are increasingly crucial in guiding health interventions. Such scores may need to be periodically updated due to change in the distributions they model. However, directly updating risk scores used to guide intervention can lead to biased risk estimates. To address this, we pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	280,199
1707.06334	Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach	Learning cooperative policies for multi-agent systems is often challenged by partial observability and a lack of coordination. In some settings, the structure of a problem allows a distributed solution with limited communication. Here, we consider a scenario where no communication is available, and instead we learn loc...	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	false	false	77,400
1802.02721	Deep Image Super Resolution via Natural Image Priors	Single image super-resolution (SR) via deep learning has recently gained significant attention in the literature. Convolutional neural networks (CNNs) are typically learned to represent the mapping between low-resolution (LR) and high-resolution (HR) images/patches with the help of training examples. Most existing deep...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,831
2412.12583	Process-Supervised Reward Models for Verifying Clinical Note Generation: A Scalable Approach Guided by Domain Expertise	Process-supervised reward models (PRMs), which verify large language model (LLM) outputs step-by-step, have achieved significant success in mathematical and coding problems. However, their application to other domains remains largely unexplored. In this work, we train a PRM to provide step-level reward signals for clin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	517,933
1302.3564	Tail Sensitivity Analysis in Bayesian Networks	The paper presents an efficient method for simulating the tails of a target variable Z=h(X) which depends on a set of basic variables X=(X_1, ..., X_n). To this aim, variables X_i, i=1, ..., n are sequentially simulated in such a manner that Z=h(x_1, ..., x_i-1, X_i, ..., X_n) is guaranteed to be in the tail of Z. When...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,030
2109.07727	Secure Transmission for Hierarchical Information Accessibility in Downlink MU-MIMO	Physical layer security is a useful tool to prevent confidential information from wiretapping. In this paper, we consider a generalized model of conventional physical layer security, referred to as hierarchical information accessibility (HIA). A main feature of the HIA model is that a network has a hierarchy in informa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	255,628
1912.05184	Variational Learning with Disentanglement-PyTorch	Unsupervised learning of disentangled representations is an open problem in machine learning. The Disentanglement-PyTorch library is developed to facilitate research, implementation, and testing of new variational algorithms. In this modular library, neural architectures, dimensionality of the latent space, and the tra...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	157,044
2211.11690	Learn to explain yourself, when you can: Equipping Concept Bottleneck Models with the ability to abstain on their concept predictions	The Concept Bottleneck Models (CBMs) of Koh et al. [2020] provide a means to ensure that a neural network based classifier bases its predictions solely on human understandable concepts. The concept labels, or rationales as we refer to them, are learned by the concept labeling component of the CBM. Another component lea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,834
2012.15534	HopRetriever: Retrieve Hops over Wikipedia to Answer Complex Questions	Collecting supporting evidence from large corpora of text (e.g., Wikipedia) is of great challenge for open-domain Question Answering (QA). Especially, for multi-hop open-domain QA, scattered evidence pieces are required to be gathered together to support the answer extraction. In this paper, we propose a new retrieval ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	213,827
2112.09598	Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans	An automated robotic system needs to be as robust as possible and fail-safe in general while having relatively high precision and repeatability. Although deep learning-based methods are becoming research standard on how to approach 3D scan and image processing tasks, the industry standard for processing this data is st...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	272,196
2405.09477	Harmonizing Human Insights and AI Precision: Hand in Hand for Advancing Knowledge Graph Task	Knowledge graph embedding (KGE) has caught significant interest for its effectiveness in knowledge graph completion (KGC), specifically link prediction (LP), with recent KGE models cracking the LP benchmarks. Despite the rapidly growing literature, insufficient attention has been paid to the cooperation between humans ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	454,412
2007.10668	An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models	The use of sophisticated machine learning models for critical decision making is faced with a challenge that these models are often applied as a "black-box". This has led to an increased interest in interpretable machine learning, where post hoc interpretation presents a useful mechanism for generating interpretations ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	188,338
1911.12060	Reviewing and Improving the Gaussian Mechanism for Differential Privacy	Differential privacy provides a rigorous framework to quantify data privacy, and has received considerable interest recently. A randomized mechanism satisfying $(\epsilon, \delta)$-differential privacy (DP) roughly means that, except with a small probability $\delta$, altering a record in a dataset cannot change the pr...	false	false	false	false	true	false	true	false	false	false	false	false	true	true	false	false	true	false	155,304
2305.19650	Adverbs, Surprisingly	This paper begins with the premise that adverbs are neglected in computational linguistics. This view derives from two analyses: a literature review and a novel adverb dataset to probe a state-of-the-art language model, thereby uncovering systematic gaps in accounts for adverb meaning. We suggest that using Frame Seman...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	369,625
2202.02540	Science Facing Interoperability as a Necessary Condition of Success and Evil	Artificial intelligence (AI) systems, such as machine learning algorithms, have allowed scientists, marketers and governments to shed light on correlations that remained invisible until now. Beforehand, the dots that we had to connect in order to imagine a new knowledge were either too numerous, too sparse or not even ...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	278,852
1505.03991	Nonlinear-Programming-Based Model of Power System Marginal States: Theoretical Substantiation	In order to maintain the security of power system at an appropriate level and at low cost, it is essential to accurately assess the steady-state stability limits and power flow feasibility boundaries, i.e., the power system marginal states (MS). This paper is devoted to creation and theoretical substantiation of the MS...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	43,130
2203.05813	Averaging Spatio-temporal Signals using Optimal Transport and Soft Alignments	Several fields in science, from genomics to neuroimaging, require monitoring populations (measures) that evolve with time. These complex datasets, describing dynamics with both time and spatial components, pose new challenges for data analysis. We propose in this work a new framework to carry out averaging of these dat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	284,922
1903.09950	Periphery-Fovea Multi-Resolution Driving Model guided by Human Attention	Inspired by human vision, we propose a new periphery-fovea multi-resolution driving model that predicts vehicle speed from dash camera videos. The peripheral vision module of the model processes the full video frames in low resolution. Its foveal vision module selects sub-regions and uses high-resolution input from tho...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	125,172
2203.11633	Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis	Model poisoning attacks on federated learning (FL) intrude in the entire system via compromising an edge model, resulting in malfunctioning of machine learning models. Such compromised models are tampered with to perform adversary-desired behaviors. In particular, we considered a semi-targeted situation where the sourc...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	286,981
1303.2446	Broadening the Scope of Nanopublications	In this paper, we present an approach for extending the existing concept of nanopublications --- tiny entities of scientific results in RDF representation --- to broaden their application range. The proposed extension uses English sentences to represent informal and underspecified scientific claims. These sentences fol...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	22,836
2111.07341	On Optimizing Rate Splitting in Laser-based Optical Wireless Networks	Optical wireless communication (OWC) is a promising technology that has the potential to provide Tb/s aggregate rates. In this paper, interference management is studied in a Laser-based optical wireless network where vertical-cavity surface-emitting (VCSEL) lasers are used for data transmission. In particular, rate spl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	266,336
2203.00648	Measuring the Impact of Individual Domain Factors in Self-Supervised Pre-Training	Human speech data comprises a rich set of domain factors such as accent, syntactic and semantic variety, or acoustic environment. Previous work explores the effect of domain mismatch in automatic speech recognition between pre-training and fine-tuning as a whole but does not dissect the contribution of individual facto...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	283,076
2404.11889	Multi-view X-ray Image Synthesis with Multiple Domain Disentanglement from CT Scans	X-ray images play a vital role in the intraoperative processes due to their high resolution and fast imaging speed and greatly promote the subsequent segmentation, registration and reconstruction. However, over-dosed X-rays superimpose potential risks to human health to some extent. Data-driven algorithms from volume s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	447,651
2208.06110	Automatically Creating a Large Number of New Bilingual Dictionaries	This paper proposes approaches to automatically create a large number of new bilingual dictionaries for low-resource languages, especially resource-poor and endangered languages, from a single input bilingual dictionary. Our algorithms produce translations of words in a source language to plentiful target languages usi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	312,601
2110.12984	Generative Residual Attention Network for Disease Detection	Accurate identification and localization of abnormalities from radiology images serve as a critical role in computer-aided diagnosis (CAD) systems. Building a highly generalizable system usually requires a large amount of data with high-quality annotations, including disease-specific global and localization information...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	263,035
1904.02892	WaveCycleGAN2: Time-domain Neural Post-filter for Speech Waveform Generation	WaveCycleGAN has recently been proposed to bridge the gap between natural and synthesized speech waveforms in statistical parametric speech synthesis and provides fast inference with a moving average model rather than an autoregressive model and high-quality speech synthesis with the adversarial training. However, the ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,560
2103.03773	A Geometric Algebra Solution to Wahba's Problem	We retrace Davenport's solution to Wahba's classic problem of aligning two pointclouds using the formalism of Geometric Algebra (GA). GA proves to be a natural backdrop for this problem involving three-dimensional rotations due to the isomorphism between unit-length quaternions and rotors. While the solution to this pr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	223,410
2011.06058	Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds	Predicting patient volumes in a hospital setting is a well-studied application of time series forecasting. Existing tools usually make forecasts at the daily or weekly level to assist in planning for staffing requirements. Prompted by new COVID-related capacity constraints placed on our pediatric hospital's emergency d...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	206,123
2112.14084	Embodied Learning for Lifelong Visual Perception	We study lifelong visual perception in an embodied setup, where we develop new models and compare various agents that navigate in buildings and occasionally request annotations which, in turn, are used to refine their visual perception capabilities. The purpose of the agents is to recognize objects and other semantic c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	273,445
2411.13284	DATTA: Domain-Adversarial Test-Time Adaptation for Cross-Domain WiFi-Based Human Activity Recognition	Cross-domain generalization is an open problem in WiFi-based sensing due to variations in environments, devices, and subjects, causing domain shifts in channel state information. To address this, we propose Domain-Adversarial Test-Time Adaptation (DATTA), a novel framework combining domain-adversarial training (DAT), t...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	509,742
2206.13959	Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts	Dealing with uncertain, contradicting, and ambiguous information is still a central issue in Artificial Intelligence (AI). As a result, many formalisms have been proposed or adapted so as to consider non-monotonicity, with only a limited number of works and researchers performing any sort of comparison among them. A no...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	305,131
2202.03843	A Unified Multi-Task Learning Framework of Real-Time Drone Supervision for Crowd Counting	In this paper, a novel Unified Multi-Task Learning Framework of Real-Time Drone Supervision for Crowd Counting (MFCC) is proposed, which utilizes an image fusion network architecture to fuse images from the visible and thermal infrared image, and a crowd counting network architecture to estimate the density map. The pu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	279,360
2407.08909	KGpose: Keypoint-Graph Driven End-to-End Multi-Object 6D Pose Estimation via Point-Wise Pose Voting	This letter presents KGpose, a novel end-to-end framework for 6D pose estimation of multiple objects. Our approach combines keypoint-based method with learnable pose regression through `keypoint-graph', which is a graph representation of the keypoints. KGpose first estimates 3D keypoints for each object using an attent...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	472,355
2404.19296	Octopus v4: Graph of language models	Language models have been effective in a wide range of applications, yet the most sophisticated models are often proprietary. For example, GPT-4 by OpenAI and various models by Anthropic are expensive and consume substantial energy. In contrast, the open-source community has produced competitive models, like Llama3. Fu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	450,587
2412.10749	Patch-level Sounding Object Tracking for Audio-Visual Question Answering	Answering questions related to audio-visual scenes, i.e., the AVQA task, is becoming increasingly popular. A critical challenge is accurately identifying and tracking sounding objects related to the question along the timeline. In this paper, we present a new Patch-level Sounding Object Tracking (PSOT) method. It begin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	517,086
1905.11475	GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification	The vulnerabilities of deep neural networks against adversarial examples have become a significant concern for deploying these models in sensitive domains. Devising a definitive defense against such attacks is proven to be challenging, and the methods relying on detecting adversarial samples are only valid when the att...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	132,430
1906.09551	Confidence Calibration for Convolutional Neural Networks Using Structured Dropout	In classification applications, we often want probabilistic predictions to reflect confidence or uncertainty. Dropout, a commonly used training technique, has recently been linked to Bayesian inference, yielding an efficient way to quantify uncertainty in neural network models. However, as previously demonstrated, conf...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	136,203
2004.14254	Hierarchical Reinforcement Learning for Automatic Disease Diagnosis	Motivation: Disease diagnosis oriented dialogue system models the interactive consultation procedure as Markov Decision Process and reinforcement learning algorithms are used to solve the problem. Existing approaches usually employ a flat policy structure that treat all symptoms and diseases equally for action making. ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	174,823
2407.10807	Employing Sentence Space Embedding for Classification of Data Stream from Fake News Domain	Tabular data is considered the last unconquered castle of deep learning, yet the task of data stream classification is stated to be an equally important and demanding research area. Due to the temporal constraints, it is assumed that deep learning methods are not the optimal solution for application in this field. Howe...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	473,137
2402.09587	DeepATLAS: One-Shot Localization for Biomedical Data	This paper introduces the DeepATLAS foundational model for localization tasks in the domain of high-dimensional biomedical data. Upon convergence of the proposed self-supervised objective, a pretrained model maps an input to an anatomically-consistent embedding from which any point or set of points (e.g., boxes or segm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	429,586
1803.10336	Graph Convolutions on Spectral Embeddings: Learning of Cortical Surface Data	Neuronal cell bodies mostly reside in the cerebral cortex. The study of this thin and highly convoluted surface is essential for understanding how the brain works. The analysis of surface data is, however, challenging due to the high variability of the cortical geometry. This paper presents a novel approach for learnin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,676
2004.02178	FastBERT: a Self-distilling BERT with Adaptive Inference Time	Pre-trained language models like BERT have proven to be highly performant. However, they are often computationally expensive in many practical scenarios, for such heavy models can hardly be readily implemented with limited resources. To improve their efficiency with an assured model performance, we propose a novel spee...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	171,147
2210.10041	Hidden State Variability of Pretrained Language Models Can Guide Computation Reduction for Transfer Learning	While transferring a pretrained language model, common approaches conventionally attach their task-specific classifiers to the top layer and adapt all the pretrained layers. We investigate whether one could make a task-specific selection on which subset of the layers to adapt and where to place the classifier. The goal...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	324,768
1911.01608	AReN: Assured ReLU NN Architecture for Model Predictive Control of LTI Systems	In this paper, we consider the problem of automatically designing a Rectified Linear Unit (ReLU) Neural Network (NN) architecture that is sufficient to implement the optimal Model Predictive Control (MPC) strategy for an LTI system with quadratic cost. Specifically, we propose AReN, an algorithm to generate Assured ReL...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	152,150
1712.02917	Using Intermittent Synchronization to Compensate for Rhythmic Body Motion During Autonomous Surgical Cutting and Debridement	Anatomical structures are rarely static during a surgical procedure due to breathing, heartbeats, and peristaltic movements. Inspired by observing an expert surgeon, we propose an intermittent synchronization with the extrema of the rhythmic motion (i.e., the lowest velocity windows). We performed 2 experiments: (1) pa...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	86,366
2405.03969	Speak the Same Language: Global LiDAR Registration on BIM Using Pose Hough Transform	The construction and robotic sensing data originate from disparate sources and are associated with distinct frames of reference. The primary objective of this study is to align LiDAR point clouds with building information modeling (BIM) using a global point cloud registration approach, aimed at establishing a shared un...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	452,385
2009.11050	Robust and efficient post-processing for video object detection	Object recognition in video is an important task for plenty of applications, including autonomous driving perception, surveillance tasks, wearable devices or IoT networks. Object recognition using video data is more challenging than using still images due to blur, occlusions or rare object poses. Specific video detecto...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	197,057
2312.00506	Generative artificial intelligence enhances creativity but reduces the diversity of novel content	Creativity is core to being human. Generative artificial intelligence (GenAI) holds promise for humans to be more creative by offering new ideas, or less creative by anchoring on GenAI ideas. We study the causal impact of GenAI on the production of a creative output in an online experimental study where some writers ar...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	412,073
2405.15992	Data Complexity Estimates for Operator Learning	Operator learning has emerged as a new paradigm for the data-driven approximation of nonlinear operators. Despite its empirical success, the theoretical underpinnings governing the conditions for efficient operator learning remain incomplete. The present work develops theory to study the data complexity of operator lea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	457,199
1608.04467	Operations- and Uncertainty-Aware Installation of FACTS Devices in a Large Transmission System	Decentralized electricity markets and more integration of renewables demand expansion of the existing transmission infrastructure to accommodate inflected variabilities in power flows. However, such expansion is severely limited in many countries because of political and environmental issues. Furthermore, high renewabl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	59,834
2101.10451	Evolution of Small Cell from 4G to 6G: Past, Present, and Future	To boost the capacity of the cellular system, the operators have started to reuse the same licensed spectrum by deploying 4G LTE small cells (Femto Cells) in the past. But in time, these small cell licensed spectrum is not sufficient to satisfy future applications like augmented reality (AR)and virtual reality (VR). He...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	216,937
2206.14076	Reasoning about Moving Target Defense in Attack Modeling Formalisms	Since 2009, Moving Target Defense (MTD) has become a new paradigm of defensive mechanism that frequently changes the state of the target system to confuse the attacker. This frequent change is costly and leads to a trade-off between misleading the attacker and disrupting the quality of service. Optimizing the MTD activ...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	305,169
2403.01529	Deep Incremental Model Based Reinforcement Learning: A One-Step Lookback Approach for Continuous Robotics Control	Model-based reinforcement learning (MBRL) attempts to use an available or a learned model to improve the data efficiency of reinforcement learning. This work proposes a one-step lookback approach that jointly learns the latent-space model and the policy to realize the sample-efficient continuous robotic control, wherei...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	434,465
2204.10818	Convergence of the Riemannian Langevin Algorithm	We study the Riemannian Langevin Algorithm for the problem of sampling from a distribution with density $\nu$ with respect to the natural measure on a manifold with metric $g$. We assume that the target density satisfies a log-Sobolev inequality with respect to the metric and prove that the manifold generalization of t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	292,927
0903.3114	Markov Random Field Segmentation of Brain MR Images	We describe a fully-automatic 3D-segmentation technique for brain MR images. Using Markov random fields the segmentation algorithm captures three important MR features, i.e. non-parametric distributions of tissue intensities, neighborhood correlations and signal inhomogeneities. Detailed simulations and real MR images ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	3,376
1909.06154	A Swash Mass Unmanned Aerial Vehicle: Design, Modeling and Control	In this paper, a new unmanned aerial vehicle (UAV) structure, referred to as swash mass UAV, is presented. It consists of a double blade coaxial shaft rotor and four swash masses that allow changing the orientation and maneuvering the UAV. The dynamical system model is derived from the Newton\textquotesingle s law fram...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	145,306
2409.07904	FACT: Feature Adaptive Continual-learning Tracker for Multiple Object Tracking	Multiple object tracking (MOT) involves identifying multiple targets and assigning them corresponding IDs within a video sequence, where occlusions are often encountered. Recent methods address occlusions using appearance cues through online learning techniques to improve adaptivity or offline learning techniques to ut...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,702
2209.12243	Safety-compliant Generative Adversarial Networks for Human Trajectory Forecasting	Human trajectory forecasting in crowds presents the challenges of modelling social interactions and outputting collision-free multimodal distribution. Following the success of Social Generative Adversarial Networks (SGAN), recent works propose various GAN-based designs to better model human motion in crowds. Despite su...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	319,464
1810.09732	A Generalization of Smillie's Theorem on Strongly Cooperative Tridiagonal Systems	Smillie (1984) proved an interesting result on the stability of nonlinear, time-invariant, strongly cooperative, and tridiagonal dynamical systems. This result has found many applications in models from various fields including biology, ecology, and chemistry. Smith (1991) has extended Smillie's result and proved entra...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	111,118
2203.17105	A Computationally Informed Realisation Algorithm for Lithium-Ion Batteries Implemented with LiiBRA.jl	Real-time battery modelling advancements have quickly become a requirement as the adoption of battery electric vehicles (BEVs) has rapidly increased. In this paper an open-source, improved discrete realisation algorithm, implemented in Julia for creation and simulation of reduced-order, real-time capable physics-based ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	289,041
2210.00923	Masked Supervised Learning for Semantic Segmentation	Self-attention is of vital importance in semantic segmentation as it enables modeling of long-range context, which translates into improved performance. We argue that it is equally important to model short-range context, especially to tackle cases where not only the regions of interest are small and ambiguous, but also...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	321,059
2312.03041	Transformer-Based Deep Learning Model for Bored Pile Load-Deformation Prediction in Bangkok Subsoil	This paper presents a novel deep learning model based on the transformer architecture to predict the load-deformation behavior of large bored piles in Bangkok subsoil. The model encodes the soil profile and pile features as tokenization input, and generates the load-deformation curve as output. The model also incorpora...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	413,113
2406.02197	A Pipelined Memristive Neural Network Analog-to-Digital Converter	With the advent of high-speed, high-precision, and low-power mixed-signal systems, there is an ever-growing demand for accurate, fast, and energy-efficient analog-to-digital (ADCs) and digital-to-analog converters (DACs). Unfortunately, with the downscaling of CMOS technology, modern ADCs trade off speed, power and acc...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	460,662
2202.11133	Continual Auxiliary Task Learning	Learning auxiliary tasks, such as multiple predictions about the world, can provide many benefits to reinforcement learning systems. A variety of off-policy learning algorithms have been developed to learn such predictions, but as yet there is little work on how to adapt the behavior to gather useful data for those off...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	281,775
1909.09096	Vision-Based Proprioceptive Sensing for Soft Inflatable Actuators	This paper presents a vision-based sensing approach for a soft linear actuator, which is equipped with an integrated camera. The proposed vision-based sensing pipeline predicts the three-dimensional position of a point of interest on the actuator. To train and evaluate the algorithm, predictions are compared to ground ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	146,149
2003.13827	Co-occurrence of deep convolutional features for image search	Image search can be tackled using deep features from pre-trained Convolutional Neural Networks (CNN). The feature map from the last convolutional layer of a CNN encodes descriptive information from which a discriminative global descriptor can be obtained. We propose a new representation of co-occurrences from deep conv...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	170,316

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