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1004.3702
Lizhi Du
Lizhi Du
A Polynomial time Algorithm for Hamilton Cycle with maximum Degree 3, 3SAT
16 pages. This time, I add a detailed polynomial time algorithm and proof for 3SAT
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Based on the famous Rotation-Extension technique, by creating the new concepts and methods: broad cycle, main segment, useful cut and insert, destroying edges for a main segment, main goal Hamilton cycle, depth-first search tree, we develop a polynomial time algorithm for a famous NPC: the Hamilton cycle problem. Thu...
[ { "version": "v1", "created": "Mon, 12 Apr 2010 04:39:27 GMT" }, { "version": "v10", "created": "Mon, 5 Nov 2012 01:44:46 GMT" }, { "version": "v11", "created": "Thu, 31 Jan 2013 11:15:53 GMT" }, { "version": "v12", "created": "Mon, 4 Nov 2013 14:09:42 GMT" }, { "...
2023-10-06T00:00:00
[ [ "Du", "Lizhi", "" ] ]
not_new_dataset
0.997305
1912.05957
Hamid Mohammadi
Hamid Mohammadi, Seyed Hossein Khasteh
Text as Environment: A Deep Reinforcement Learning Text Readability Assessment Model
null
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Evaluating the readability of a text can significantly facilitate the precise expression of information in written form. The formulation of text readability assessment involves the identification of meaningful properties of the text regardless of its length. Sophisticated features and models are used to evaluate the ...
[ { "version": "v1", "created": "Thu, 12 Dec 2019 13:54:09 GMT" }, { "version": "v2", "created": "Sun, 15 Dec 2019 15:46:55 GMT" }, { "version": "v3", "created": "Wed, 4 Oct 2023 19:09:25 GMT" } ]
2023-10-06T00:00:00
[ [ "Mohammadi", "Hamid", "" ], [ "Khasteh", "Seyed Hossein", "" ] ]
not_new_dataset
0.997235
2004.05672
Julliano Rosa Nascimento
Flavia Bonomo-Braberman, Julliano R. Nascimento, Fabiano S. Oliveira, U\'everton S. Souza, and Jayme L. Szwarcfiter
Linear-time Algorithms for Eliminating Claws in Graphs
20 pages
International Transactions in Operational Research 31 (2024), 296--315
10.1111/itor.13100
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Since many NP-complete graph problems have been shown polynomial-time solvable when restricted to claw-free graphs, we study the problem of determining the distance of a given graph to a claw-free graph, considering vertex elimination as measure. CLAW-FREE VERTEX DELETION (CFVD) consists of determining the minimum nu...
[ { "version": "v1", "created": "Sun, 12 Apr 2020 18:49:41 GMT" } ]
2023-10-06T00:00:00
[ [ "Bonomo-Braberman", "Flavia", "" ], [ "Nascimento", "Julliano R.", "" ], [ "Oliveira", "Fabiano S.", "" ], [ "Souza", "Uéverton S.", "" ], [ "Szwarcfiter", "Jayme L.", "" ] ]
not_new_dataset
0.997512
2010.11559
Yangjing Zhang
Yangjing Zhang, Kim-Chuan Toh, Defeng Sun
Learning Graph Laplacian with MCP
32 pages
null
null
null
cs.LG math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of learning a graph under the Laplacian constraint with a non-convex penalty: minimax concave penalty (MCP). For solving the MCP penalized graphical model, we design an inexact proximal difference-of-convex algorithm (DCA) and prove its convergence to critical points. We note that each subprob...
[ { "version": "v1", "created": "Thu, 22 Oct 2020 09:33:49 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 08:56:20 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhang", "Yangjing", "" ], [ "Toh", "Kim-Chuan", "" ], [ "Sun", "Defeng", "" ] ]
not_new_dataset
0.997341
2011.15122
Willem van Jaarsveld
Tarkan Temiz\"oz, Christina Imdahl, Remco Dijkman, Douniel Lamghari-Idrissi, Willem van Jaarsveld
Deep Controlled Learning for Inventory Control
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Problem Definition: Are traditional deep reinforcement learning (DRL) algorithms, developed for a broad range of purposes including game-play and robotics, the most suitable machine learning algorithms for applications in inventory control? To what extent would DRL algorithms tailored to the unique characteristics of...
[ { "version": "v1", "created": "Mon, 30 Nov 2020 18:53:08 GMT" }, { "version": "v2", "created": "Thu, 9 Sep 2021 10:08:31 GMT" }, { "version": "v3", "created": "Tue, 9 Nov 2021 14:59:21 GMT" }, { "version": "v4", "created": "Fri, 12 Nov 2021 11:47:09 GMT" }, { "ver...
2023-10-06T00:00:00
[ [ "Temizöz", "Tarkan", "" ], [ "Imdahl", "Christina", "" ], [ "Dijkman", "Remco", "" ], [ "Lamghari-Idrissi", "Douniel", "" ], [ "van Jaarsveld", "Willem", "" ] ]
not_new_dataset
0.997478
2102.00696
Selim Furkan Tekin
Selim Furkan Tekin, Arda Fazla and Suleyman Serdar Kozat
Numerical Weather Forecasting using Convolutional-LSTM with Attention and Context Matcher Mechanisms
- In our journal submission, we removed the integration of the observational data section since it was not used in the experiments. Thus, we also removed the authors from the paper who were responsible for that section. - In the second version, we also performed an experiment on WeatherBench. We compare our res...
null
null
null
cs.LG cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Numerical weather forecasting using high-resolution physical models often requires extensive computational resources on supercomputers, which diminishes their wide usage in most real-life applications. As a remedy, applying deep learning methods has revealed innovative solutions within this field. To this end, we int...
[ { "version": "v1", "created": "Mon, 1 Feb 2021 08:30:42 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 18:56:52 GMT" } ]
2023-10-06T00:00:00
[ [ "Tekin", "Selim Furkan", "" ], [ "Fazla", "Arda", "" ], [ "Kozat", "Suleyman Serdar", "" ] ]
not_new_dataset
0.997217
2103.04904
Laszlo Csirmaz
Laszlo Csirmaz, Franti\v{s}ek Mat\'u\v{s} and Carles Padr\'o
Bipartite secret sharing and staircases
To appear in Discrete Mathematics
null
null
null
cs.CR cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bipartite secret sharing schemes have a bipartite access structure in which the set of participants is divided into two parts and all participants in the same part play an equivalent role. Such a bipartite scheme can be described by a \emph{staircase}: the collection of its minimal points. The complexity of a scheme ...
[ { "version": "v1", "created": "Mon, 8 Mar 2021 17:09:43 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 14:19:21 GMT" } ]
2023-10-06T00:00:00
[ [ "Csirmaz", "Laszlo", "" ], [ "Matúš", "František", "" ], [ "Padró", "Carles", "" ] ]
not_new_dataset
0.997313
2104.03937
Flavia Bonomo
Flavia Bonomo-Braberman and Gast\'on Abel Brito
Intersection models and forbidden pattern characterizations for 2-thin and proper 2-thin graphs
An extended abstract of this work, entitled "Intersection models for 2-thin and proper 2-thin graphs", was presented at LAGOS 2021 and appears in Procedia Computer Science 195 (2021), 221-229 (Proc. LAGOS'21, Sao Paulo, Brazil)
Discrete Applied Mathematics 339 (2023), 53-77
10.1016/j.dam.2023.06.013
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The \emph{thinness} of a graph is a width parameter that generalizes some properties of interval graphs, which are exactly the graphs of thinness one. Graphs with thinness at most two include, for example, bipartite convex graphs. Many NP-complete problems can be solved in polynomial time for graphs with bounded thin...
[ { "version": "v1", "created": "Thu, 8 Apr 2021 17:31:41 GMT" }, { "version": "v2", "created": "Sat, 1 Apr 2023 19:20:18 GMT" } ]
2023-10-06T00:00:00
[ [ "Bonomo-Braberman", "Flavia", "" ], [ "Brito", "Gastón Abel", "" ] ]
not_new_dataset
0.99737
2104.07454
Rohitash Chandra
Animesh Renanse, Alok Sharma, Rohitash Chandra
Memory Capacity of Recurrent Neural Networks with Matrix Representation
null
null
null
null
cs.LG cs.AI cs.CC
http://creativecommons.org/licenses/by/4.0/
It is well known that canonical recurrent neural networks (RNNs) face limitations in learning long-term dependencies which have been addressed by memory structures in long short-term memory (LSTM) networks. Neural Turing machines (NTMs) are novel RNNs that implement the notion of programmable computers with neural ne...
[ { "version": "v1", "created": "Sun, 11 Apr 2021 23:43:28 GMT" }, { "version": "v2", "created": "Sun, 30 Oct 2022 06:43:49 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 03:47:41 GMT" } ]
2023-10-06T00:00:00
[ [ "Renanse", "Animesh", "" ], [ "Sharma", "Alok", "" ], [ "Chandra", "Rohitash", "" ] ]
not_new_dataset
0.997475
2105.07099
Seyed Omid Davoudi
Omid Davoodi, Majid Komeili
Feature-Based Interpretable Reinforcement Learning based on State-Transition Models
null
null
10.1109/SMC52423.2021.9658917
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Growing concerns regarding the operational usage of AI models in the real-world has caused a surge of interest in explaining AI models' decisions to humans. Reinforcement Learning is not an exception in this regard. In this work, we propose a method for offering local explanations on risk in reinforcement learning. O...
[ { "version": "v1", "created": "Fri, 14 May 2021 23:43:11 GMT" } ]
2023-10-06T00:00:00
[ [ "Davoodi", "Omid", "" ], [ "Komeili", "Majid", "" ] ]
not_new_dataset
0.997394
2107.08086
Raman Goyal
Raman Goyal, Ran Wang, Mohamed Naveed Gul Mohamed, Aayushman Sharma, Suman Chakravorty
An Information-state based Approach to the Optimal Output Feedback Control of Nonlinear Systems
null
null
null
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
This paper develops a data-based approach to the closed-loop output feedback control of nonlinear dynamical systems with a partial nonlinear observation model. We propose an information state based approach to rigorously transform the partially observed problem into a fully observed problem where the information stat...
[ { "version": "v1", "created": "Fri, 16 Jul 2021 19:21:43 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 16:28:20 GMT" } ]
2023-10-06T00:00:00
[ [ "Goyal", "Raman", "" ], [ "Wang", "Ran", "" ], [ "Mohamed", "Mohamed Naveed Gul", "" ], [ "Sharma", "Aayushman", "" ], [ "Chakravorty", "Suman", "" ] ]
not_new_dataset
0.99729
2108.05641
Jinpeng Chen
Jinpeng Chen, Haiyang Li, Xudong Zhang, Fan Zhang, Senzhang Wang, Kaimin Wei and Jiaqi Ji
SR-HetGNN:Session-based Recommendation with Heterogeneous Graph Neural Network
null
null
null
null
cs.IR cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Session-Based Recommendation System aims to predict the user's next click based on their previous session sequence. The current studies generally learn user preferences according to the transitions of items in the user's session sequence. However, other effective information in the session sequence, such as user ...
[ { "version": "v1", "created": "Thu, 12 Aug 2021 10:12:48 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 03:21:08 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 08:28:44 GMT" } ]
2023-10-06T00:00:00
[ [ "Chen", "Jinpeng", "" ], [ "Li", "Haiyang", "" ], [ "Zhang", "Xudong", "" ], [ "Zhang", "Fan", "" ], [ "Wang", "Senzhang", "" ], [ "Wei", "Kaimin", "" ], [ "Ji", "Jiaqi", "" ] ]
not_new_dataset
0.997301
2109.03890
Vignesh Viswanathan
Gagan Biradar, Vignesh Viswanathan, Yair Zick
Model Explanations via the Axiomatic Causal Lens
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Explaining the decisions of black-box models is a central theme in the study of trustworthy ML. Numerous measures have been proposed in the literature; however, none of them take an axiomatic approach to causal explainability. In this work, we propose three explanation measures which aggregate the set of all but-for ...
[ { "version": "v1", "created": "Wed, 8 Sep 2021 19:33:52 GMT" }, { "version": "v2", "created": "Fri, 17 Sep 2021 14:17:59 GMT" }, { "version": "v3", "created": "Mon, 31 Jan 2022 23:50:48 GMT" }, { "version": "v4", "created": "Mon, 11 Sep 2023 19:33:45 GMT" }, { "ve...
2023-10-06T00:00:00
[ [ "Biradar", "Gagan", "" ], [ "Viswanathan", "Vignesh", "" ], [ "Zick", "Yair", "" ] ]
not_new_dataset
0.997332
2109.04939
Ryo Yoshida
Ryo Yoshida, Hiroshi Noji, Yohei Oseki
Modeling Human Sentence Processing with Left-Corner Recurrent Neural Network Grammars
Accepted by EMNLP 2021
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In computational linguistics, it has been shown that hierarchical structures make language models (LMs) more human-like. However, the previous literature has been agnostic about a parsing strategy of the hierarchical models. In this paper, we investigated whether hierarchical structures make LMs more human-like, and ...
[ { "version": "v1", "created": "Fri, 10 Sep 2021 15:35:00 GMT" }, { "version": "v2", "created": "Thu, 11 May 2023 02:41:41 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 10:33:42 GMT" } ]
2023-10-06T00:00:00
[ [ "Yoshida", "Ryo", "" ], [ "Noji", "Hiroshi", "" ], [ "Oseki", "Yohei", "" ] ]
not_new_dataset
0.997377
2110.03991
John Stephan
Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Sebastien Rouault, and John Stephan
Combining Differential Privacy and Byzantine Resilience in Distributed SGD
null
null
null
null
cs.LG cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Privacy and Byzantine resilience (BR) are two crucial requirements of modern-day distributed machine learning. The two concepts have been extensively studied individually but the question of how to combine them effectively remains unanswered. This paper contributes to addressing this question by studying the extent t...
[ { "version": "v1", "created": "Fri, 8 Oct 2021 09:23:03 GMT" }, { "version": "v2", "created": "Wed, 20 Oct 2021 14:21:46 GMT" }, { "version": "v3", "created": "Tue, 26 Oct 2021 13:37:16 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 09:03:58 GMT" } ]
2023-10-06T00:00:00
[ [ "Guerraoui", "Rachid", "" ], [ "Gupta", "Nirupam", "" ], [ "Pinot", "Rafael", "" ], [ "Rouault", "Sebastien", "" ], [ "Stephan", "John", "" ] ]
not_new_dataset
0.997476
2110.14883
Yang You
Shenggui Li and Hongxin Liu and Zhengda Bian and Jiarui Fang and Haichen Huang and Yuliang Liu and Boxiang Wang and Yang You
Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training
null
null
null
null
cs.LG cs.AI cs.CL cs.CV cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The success of Transformer models has pushed the deep learning model scale to billions of parameters. Due to the limited memory resource of a single GPU, However, the best practice for choosing the optimal parallel strategy is still lacking, since it requires domain expertise in both deep learning and parallel comput...
[ { "version": "v1", "created": "Thu, 28 Oct 2021 04:45:55 GMT" }, { "version": "v2", "created": "Tue, 20 Sep 2022 12:54:20 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 04:09:09 GMT" } ]
2023-10-06T00:00:00
[ [ "Li", "Shenggui", "" ], [ "Liu", "Hongxin", "" ], [ "Bian", "Zhengda", "" ], [ "Fang", "Jiarui", "" ], [ "Huang", "Haichen", "" ], [ "Liu", "Yuliang", "" ], [ "Wang", "Boxiang", "" ], [ "You", "...
not_new_dataset
0.997264
2110.15497
Peiyu Yu
Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
Unsupervised Foreground Extraction via Deep Region Competition
NeurIPS 2021
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
We present Deep Region Competition (DRC), an algorithm designed to extract foreground objects from images in a fully unsupervised manner. Foreground extraction can be viewed as a special case of generic image segmentation that focuses on identifying and disentangling objects from the background. In this work, we reth...
[ { "version": "v1", "created": "Fri, 29 Oct 2021 02:32:44 GMT" }, { "version": "v2", "created": "Tue, 9 Nov 2021 01:40:02 GMT" }, { "version": "v3", "created": "Sat, 25 Dec 2021 14:18:17 GMT" }, { "version": "v4", "created": "Wed, 4 Oct 2023 22:05:42 GMT" } ]
2023-10-06T00:00:00
[ [ "Yu", "Peiyu", "" ], [ "Xie", "Sirui", "" ], [ "Ma", "Xiaojian", "" ], [ "Zhu", "Yixin", "" ], [ "Wu", "Ying Nian", "" ], [ "Zhu", "Song-Chun", "" ] ]
not_new_dataset
0.997399
2111.02062
Pio Calderon
Pio Calderon, Alexander Soen, Marian-Andrei Rizoiu
Linking Across Data Granularity: Fitting Multivariate Hawkes Processes to Partially Interval-Censored Data
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.LG cs.CE
http://creativecommons.org/licenses/by-nc-sa/4.0/
The multivariate Hawkes process (MHP) is widely used for analyzing data streams that interact with each other, where events generate new events within their own dimension (via self-excitation) or across different dimensions (via cross-excitation). However, in certain applications, the timestamps of individual events ...
[ { "version": "v1", "created": "Wed, 3 Nov 2021 08:25:35 GMT" }, { "version": "v2", "created": "Mon, 7 Feb 2022 04:01:58 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 04:55:06 GMT" } ]
2023-10-06T00:00:00
[ [ "Calderon", "Pio", "" ], [ "Soen", "Alexander", "" ], [ "Rizoiu", "Marian-Andrei", "" ] ]
not_new_dataset
0.997466
2111.12232
Katsuya Hotta
Katsuya Hotta, Takuya Akashi, Shogo Tokai, Chao Zhang
PMSSC: Parallelizable multi-subset based self-expressive model for subspace clustering
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Subspace clustering methods which embrace a self-expressive model that represents each data point as a linear combination of other data points in the dataset provide powerful unsupervised learning techniques. However, when dealing with large datasets, representation of each data point by referring to all data points ...
[ { "version": "v1", "created": "Wed, 24 Nov 2021 02:22:43 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 16:30:48 GMT" } ]
2023-10-06T00:00:00
[ [ "Hotta", "Katsuya", "" ], [ "Akashi", "Takuya", "" ], [ "Tokai", "Shogo", "" ], [ "Zhang", "Chao", "" ] ]
not_new_dataset
0.997267
2112.03379
Seungwoo Jeong
Seungwoo Jeong, Wonjun Ko, Ahmad Wisnu Mulyadi, Heung-Il Suk
Efficient Continuous Manifold Learning for Time Series Modeling
null
null
10.1109/TPAMI.2023.3320125
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modeling non-Euclidean data is drawing attention along with the unprecedented successes of deep neural networks in diverse fields. In particular, symmetric positive definite (SPD) matrix is being actively studied in computer vision, signal processing, and medical image analysis, thanks to its ability to learn appropr...
[ { "version": "v1", "created": "Fri, 3 Dec 2021 01:38:38 GMT" } ]
2023-10-06T00:00:00
[ [ "Jeong", "Seungwoo", "" ], [ "Ko", "Wonjun", "" ], [ "Mulyadi", "Ahmad Wisnu", "" ], [ "Suk", "Heung-Il", "" ] ]
not_new_dataset
0.997369
2112.08581
Weijie Zheng
Weijie Zheng, Benjamin Doerr
Mathematical Runtime Analysis for the Non-Dominated Sorting Genetic Algorithm II (NSGA-II)
Accepted for publication in "Artificial Intelligence". This is the journal version of the paper "Weijie Zheng, Yufei Liu, Benjamin Doerr: A First Mathematical Runtime Analysis of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). AAAI 2022. arXiv:2112.08581v3"
Artificial Intelligence 325 (2023), 104016
10.1016/j.artint.2023.104016
null
cs.NE cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The non-dominated sorting genetic algorithm II (NSGA-II) is the most intensively used multi-objective evolutionary algorithm (MOEA) in real-world applications. However, in contrast to several simple MOEAs analyzed also via mathematical means, no such study exists for the NSGA-II so far. In this work, we show that mat...
[ { "version": "v1", "created": "Thu, 16 Dec 2021 03:00:20 GMT" }, { "version": "v2", "created": "Fri, 11 Feb 2022 15:16:57 GMT" }, { "version": "v3", "created": "Mon, 20 Jun 2022 10:31:08 GMT" }, { "version": "v4", "created": "Fri, 24 Jun 2022 11:24:43 GMT" }, { "v...
2023-10-06T00:00:00
[ [ "Zheng", "Weijie", "" ], [ "Doerr", "Benjamin", "" ] ]
not_new_dataset
0.997388
2202.09573
Gabriel Turinici
Gabriel Turinici
Diversity in deep generative models and generative AI
null
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
The decoder-based machine learning generative algorithms such as Generative Adversarial Networks (GAN), Variational Auto-Encoders (VAE), Transformers show impressive results when constructing objects similar to those in a training ensemble. However, the generation of new objects builds mainly on the understanding of ...
[ { "version": "v1", "created": "Sat, 19 Feb 2022 10:52:52 GMT" }, { "version": "v2", "created": "Fri, 15 Sep 2023 16:55:40 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 13:32:57 GMT" } ]
2023-10-06T00:00:00
[ [ "Turinici", "Gabriel", "" ] ]
not_new_dataset
0.997369
2202.13103
Prerona Chatterjee
Prerona Chatterjee, Kshitij Gajjar, Anamay Tengse
Monotone Classes Beyond VNP
30 pages; made changes suggested by reviewers
null
null
null
cs.CC
http://creativecommons.org/licenses/by-nc-sa/4.0/
In this work, we study the natural monotone analogues of various equivalent definitions of VPSPACE: a well studied class (Poizat 2008, Koiran and Perifel 2009, Malod 2011, Mahajan and Rao 2013) that is believed to be larger than VNP. We observe that these monotone analogues are not equivalent unlike their non-monoton...
[ { "version": "v1", "created": "Sat, 26 Feb 2022 10:18:15 GMT" }, { "version": "v2", "created": "Mon, 26 Sep 2022 15:17:49 GMT" }, { "version": "v3", "created": "Sun, 23 Jul 2023 12:48:01 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 14:21:06 GMT" } ]
2023-10-06T00:00:00
[ [ "Chatterjee", "Prerona", "" ], [ "Gajjar", "Kshitij", "" ], [ "Tengse", "Anamay", "" ] ]
not_new_dataset
0.99735
2205.05250
Hao Ren
Hao Ren, Xiaojun Liang, Chunhua Yang, Zhiwen Chen, and Weihua Gui
Spatial-temporal associations representation and application for process monitoring using graph convolution neural network
null
null
null
null
cs.LG cs.AI cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Thank you very much for the attention and concern of colleagues and scholars in this work. With the comments and guidance of experts, editors, and reviewers, this work has been accepted for publishing in the journal "Process Safety and Environmental Protection". The theme of this paper relies on the Spatial-temporal ...
[ { "version": "v1", "created": "Wed, 11 May 2022 03:36:35 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 14:32:15 GMT" } ]
2023-10-06T00:00:00
[ [ "Ren", "Hao", "" ], [ "Liang", "Xiaojun", "" ], [ "Yang", "Chunhua", "" ], [ "Chen", "Zhiwen", "" ], [ "Gui", "Weihua", "" ] ]
not_new_dataset
0.997368
2205.09174
Ehud Shapiro
Idit Keidar, Oded Naor, Ouri Poupko, and Ehud Shapiro
Cordial Miners: Fast and Efficient Consensus for Every Eventuality
null
null
10.4230/LIPIcs.DISC.2023.26
null
cs.DC cs.MA cs.NI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Cordial Miners are a family of efficient Byzantine Atomic Broadcast protocols, with instances for asynchrony and eventual synchrony. They improve the latency of state-of-the-art DAG-based protocols by almost 2X and achieve optimal good-case complexity of O(n) by forgoing Reliable Broadcast as a building block. Ra...
[ { "version": "v1", "created": "Wed, 18 May 2022 18:45:20 GMT" }, { "version": "v2", "created": "Mon, 1 Aug 2022 02:28:16 GMT" }, { "version": "v3", "created": "Thu, 11 Aug 2022 19:19:31 GMT" }, { "version": "v4", "created": "Wed, 9 Nov 2022 19:34:18 GMT" }, { "ver...
2023-10-06T00:00:00
[ [ "Keidar", "Idit", "" ], [ "Naor", "Oded", "" ], [ "Poupko", "Ouri", "" ], [ "Shapiro", "Ehud", "" ] ]
not_new_dataset
0.996969
2206.05895
Peiyu Yu
Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, and Ying Nian Wu
Latent Diffusion Energy-Based Model for Interpretable Text Modeling
ICML 2022
null
null
null
cs.LG cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Latent space Energy-Based Models (EBMs), also known as energy-based priors, have drawn growing interests in generative modeling. Fueled by its flexibility in the formulation and strong modeling power of the latent space, recent works built upon it have made interesting attempts aiming at the interpretability of text ...
[ { "version": "v1", "created": "Mon, 13 Jun 2022 03:41:31 GMT" }, { "version": "v2", "created": "Tue, 14 Jun 2022 03:01:05 GMT" }, { "version": "v3", "created": "Mon, 4 Jul 2022 16:28:58 GMT" }, { "version": "v4", "created": "Wed, 4 Oct 2023 22:00:21 GMT" } ]
2023-10-06T00:00:00
[ [ "Yu", "Peiyu", "" ], [ "Xie", "Sirui", "" ], [ "Ma", "Xiaojian", "" ], [ "Jia", "Baoxiong", "" ], [ "Pang", "Bo", "" ], [ "Gao", "Ruiqi", "" ], [ "Zhu", "Yixin", "" ], [ "Zhu", "Song-Chun", ...
not_new_dataset
0.997415
2207.03299
Juan Bascur
Juan Pablo Bascur, Suzan Verberne, Nees Jan van Eck, Ludo Waltman
Academic information retrieval using citation clusters: In-depth evaluation based on systematic reviews
Final version
null
null
null
cs.DL
http://creativecommons.org/licenses/by/4.0/
The field of scientometrics has shown the power of citation-based clusters for literature analysis, yet this technique has barely been used for information retrieval tasks. This work evaluates the performance of citation based-clusters for information retrieval tasks. We simulated a search process using these cluster...
[ { "version": "v1", "created": "Thu, 7 Jul 2022 13:50:27 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 15:42:11 GMT" } ]
2023-10-06T00:00:00
[ [ "Bascur", "Juan Pablo", "" ], [ "Verberne", "Suzan", "" ], [ "van Eck", "Nees Jan", "" ], [ "Waltman", "Ludo", "" ] ]
not_new_dataset
0.997488
2207.05132
Arghavan Moradi Dakhel
Arghavan Moradi Dakhel, Michel C. Desmarais, Foutse Khomh
Dev2vec: Representing Domain Expertise of Developers in an Embedding Space
30 pages, 5 figures
null
10.1016/j.infsof.2023.107218
null
cs.SE cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurate assessment of the domain expertise of developers is important for assigning the proper candidate to contribute to a project or to attend a job role. Since the potential candidate can come from a large pool, the automated assessment of this domain expertise is a desirable goal. While previous methods have had...
[ { "version": "v1", "created": "Mon, 11 Jul 2022 18:56:49 GMT" } ]
2023-10-06T00:00:00
[ [ "Dakhel", "Arghavan Moradi", "" ], [ "Desmarais", "Michel C.", "" ], [ "Khomh", "Foutse", "" ] ]
not_new_dataset
0.996237
2207.11447
Xu Zhou
Xu Zhou, Xinyu Lei, Cong Yang, Yichun Shi, Xiao Zhang, Jingwen Shi
Handling Data Heterogeneity in Federated Learning via Knowledge Distillation and Fusion
15 pages, 3 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated learning (FL) supports distributed training of a global machine learning model across multiple devices with the help of a central server. However, data heterogeneity across different devices leads to the client model drift issue and results in model performance degradation and poor model fairness. To addres...
[ { "version": "v1", "created": "Sat, 23 Jul 2022 07:20:22 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 20:44:04 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhou", "Xu", "" ], [ "Lei", "Xinyu", "" ], [ "Yang", "Cong", "" ], [ "Shi", "Yichun", "" ], [ "Zhang", "Xiao", "" ], [ "Shi", "Jingwen", "" ] ]
not_new_dataset
0.997376
2207.11880
Huaxiong Li
Kaiyi Luo, Chao Zhang, Huaxiong Li, Xiuyi Jia, Chunlin Chen
Adaptive Marginalized Semantic Hashing for Unpaired Cross-Modal Retrieval
null
null
10.1109/TMM.2023.3245400
null
cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, Cross-Modal Hashing (CMH) has aroused much attention due to its fast query speed and efficient storage. Previous literatures have achieved promising results for Cross-Modal Retrieval (CMR) by discovering discriminative hash codes and modality-specific hash functions. Nonetheless, most existing CMR wo...
[ { "version": "v1", "created": "Mon, 25 Jul 2022 02:50:20 GMT" } ]
2023-10-06T00:00:00
[ [ "Luo", "Kaiyi", "" ], [ "Zhang", "Chao", "" ], [ "Li", "Huaxiong", "" ], [ "Jia", "Xiuyi", "" ], [ "Chen", "Chunlin", "" ] ]
not_new_dataset
0.997456
2207.14096
Shaun Yuan
Gong Cheng, Xiang Yuan, Xiwen Yao, Kebing Yan, Qinghua Zeng, Xingxing Xie, and Junwei Han
Towards Large-Scale Small Object Detection: Survey and Benchmarks
in IEEE Transactions on Pattern Analysis and Machine Intelligence (2023)
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 11, pp. 13467-13488, 1 Nov. 2023
10.1109/TPAMI.2023.3290594
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the rise of deep convolutional neural networks, object detection has achieved prominent advances in past years. However, such prosperity could not camouflage the unsatisfactory situation of Small Object Detection (SOD), one of the notoriously challenging tasks in computer vision, owing to the poor visual appeara...
[ { "version": "v1", "created": "Thu, 28 Jul 2022 14:02:18 GMT" }, { "version": "v2", "created": "Sun, 31 Jul 2022 08:33:25 GMT" }, { "version": "v3", "created": "Sat, 24 Dec 2022 15:43:44 GMT" }, { "version": "v4", "created": "Tue, 11 Apr 2023 03:58:28 GMT" } ]
2023-10-06T00:00:00
[ [ "Cheng", "Gong", "" ], [ "Yuan", "Xiang", "" ], [ "Yao", "Xiwen", "" ], [ "Yan", "Kebing", "" ], [ "Zeng", "Qinghua", "" ], [ "Xie", "Xingxing", "" ], [ "Han", "Junwei", "" ] ]
new_dataset
0.997998
2208.07708
Gyanendra Kumar Verma
Gyanendra K. Verma, Astha Agrawal, R. K. Sharma
Construction Methods for Galois LCD codes over Finite Fields
There are many typos and mathematical typos as well
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
In this article, first we present a method for constructing many Hermitian LCD codes from a given Hermitian LCD code, and then provide several methods which utilize either a given [n, k, d] linear code or a given [n, k, d] Galois LCD code to construct new Galois LCD codes with different parameters. Using these constr...
[ { "version": "v1", "created": "Tue, 16 Aug 2022 12:19:42 GMT" }, { "version": "v2", "created": "Fri, 2 Sep 2022 05:40:26 GMT" }, { "version": "v3", "created": "Tue, 3 Oct 2023 04:59:01 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 09:06:17 GMT" } ]
2023-10-06T00:00:00
[ [ "Verma", "Gyanendra K.", "" ], [ "Agrawal", "Astha", "" ], [ "Sharma", "R. K.", "" ] ]
not_new_dataset
0.997271
2209.05917
Sunkyung Lee
Eunseong Choi, Sunkyung Lee, Minjin Choi, Hyeseon Ko, Young-In Song and Jongwuk Lee
SpaDE: Improving Sparse Representations using a Dual Document Encoder for First-stage Retrieval
In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM '22). 13 pages
null
10.1145/3511808.3557456
null
cs.IR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Sparse document representations have been widely used to retrieve relevant documents via exact lexical matching. Owing to the pre-computed inverted index, it supports fast ad-hoc search but incurs the vocabulary mismatch problem. Although recent neural ranking models using pre-trained language models can address this...
[ { "version": "v1", "created": "Tue, 13 Sep 2022 12:06:01 GMT" }, { "version": "v2", "created": "Thu, 13 Apr 2023 05:57:34 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 02:33:49 GMT" } ]
2023-10-06T00:00:00
[ [ "Choi", "Eunseong", "" ], [ "Lee", "Sunkyung", "" ], [ "Choi", "Minjin", "" ], [ "Ko", "Hyeseon", "" ], [ "Song", "Young-In", "" ], [ "Lee", "Jongwuk", "" ] ]
not_new_dataset
0.997335
2209.12148
Radu Tudor Ionescu
Neelu Madan, Nicolae-Catalin Ristea, Radu Tudor Ionescu, Kamal Nasrollahi, Fahad Shahbaz Khan, Thomas B. Moeslund, Mubarak Shah
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection
Accepted in IEEE Transactions on Pattern Analysis and Machine Intelligence
null
10.1109/TPAMI.2023.3322604
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Anomaly detection has recently gained increasing attention in the field of computer vision, likely due to its broad set of applications ranging from product fault detection on industrial production lines and impending event detection in video surveillance to finding lesions in medical scans. Regardless of the domain,...
[ { "version": "v1", "created": "Sun, 25 Sep 2022 04:56:10 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 10:37:39 GMT" } ]
2023-10-06T00:00:00
[ [ "Madan", "Neelu", "" ], [ "Ristea", "Nicolae-Catalin", "" ], [ "Ionescu", "Radu Tudor", "" ], [ "Nasrollahi", "Kamal", "" ], [ "Khan", "Fahad Shahbaz", "" ], [ "Moeslund", "Thomas B.", "" ], [ "Shah", "Mubarak"...
not_new_dataset
0.988627
2210.01422
Rasool Fakoor
Rasool Fakoor and Jonas Mueller and Zachary C. Lipton and Pratik Chaudhari and Alexander J. Smola
Time-Varying Propensity Score to Bridge the Gap between the Past and Present
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Real-world deployment of machine learning models is challenging because data evolves over time. While no model can work when data evolves in an arbitrary fashion, if there is some pattern to these changes, we might be able to design methods to address it. This paper addresses situations when data evolves gradually. W...
[ { "version": "v1", "created": "Tue, 4 Oct 2022 07:21:49 GMT" }, { "version": "v2", "created": "Mon, 30 Jan 2023 17:52:10 GMT" }, { "version": "v3", "created": "Wed, 14 Jun 2023 17:47:50 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 17:38:13 GMT" } ]
2023-10-06T00:00:00
[ [ "Fakoor", "Rasool", "" ], [ "Mueller", "Jonas", "" ], [ "Lipton", "Zachary C.", "" ], [ "Chaudhari", "Pratik", "" ], [ "Smola", "Alexander J.", "" ] ]
not_new_dataset
0.997504
2210.01944
Sajad Darabi
Sajad Darabi, Piotr Bigaj, Dawid Majchrowski, Artur Kasymov, Pawel Morkisz, Alex Fit-Florea
A Framework for Large Scale Synthetic Graph Dataset Generation
null
null
null
null
cs.LG cs.SI
http://creativecommons.org/licenses/by/4.0/
Recently there has been increasing interest in developing and deploying deep graph learning algorithms for many tasks, such as fraud detection and recommender systems. Albeit, there is a limited number of publicly available graph-structured datasets, most of which are tiny compared to production-sized applications or...
[ { "version": "v1", "created": "Tue, 4 Oct 2022 22:41:33 GMT" }, { "version": "v2", "created": "Thu, 6 Oct 2022 15:17:02 GMT" }, { "version": "v3", "created": "Tue, 28 Feb 2023 23:05:44 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 05:22:43 GMT" } ]
2023-10-06T00:00:00
[ [ "Darabi", "Sajad", "" ], [ "Bigaj", "Piotr", "" ], [ "Majchrowski", "Dawid", "" ], [ "Kasymov", "Artur", "" ], [ "Morkisz", "Pawel", "" ], [ "Fit-Florea", "Alex", "" ] ]
not_new_dataset
0.997341
2210.17505
Roberto Casadei PhD
Roberto Casadei, Stefano Mariani, Danilo Pianini, Mirko Viroli, Franco Zambonelli
Space-Fluid Adaptive Sampling by Self-Organisation
33 pages, 16 figures
null
null
null
cs.DC cs.AI cs.MA cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
A recurrent task in coordinated systems is managing (estimating, predicting, or controlling) signals that vary in space, such as distributed sensed data or computation outcomes. Especially in large-scale settings, the problem can be addressed through decentralised and situated computing systems: nodes can locally sen...
[ { "version": "v1", "created": "Mon, 31 Oct 2022 17:29:41 GMT" }, { "version": "v2", "created": "Thu, 16 Mar 2023 17:31:22 GMT" }, { "version": "v3", "created": "Tue, 1 Aug 2023 07:38:51 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 10:46:56 GMT" } ]
2023-10-06T00:00:00
[ [ "Casadei", "Roberto", "" ], [ "Mariani", "Stefano", "" ], [ "Pianini", "Danilo", "" ], [ "Viroli", "Mirko", "" ], [ "Zambonelli", "Franco", "" ] ]
not_new_dataset
0.997303
2211.00635
Yihan Wang
Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit S Dhillon, Sanjiv Kumar
Two-stage LLM Fine-tuning with Less Specialization and More Generalization
null
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Pretrained large language models (LLMs) are general purpose problem solvers applicable to a diverse set of tasks with prompts. They can be further improved towards a specific task by fine-tuning on a specialized dataset. However, fine-tuning usually makes the model narrowly specialized on this dataset with reduced ge...
[ { "version": "v1", "created": "Tue, 1 Nov 2022 17:56:57 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 20:27:57 GMT" } ]
2023-10-06T00:00:00
[ [ "Wang", "Yihan", "" ], [ "Si", "Si", "" ], [ "Li", "Daliang", "" ], [ "Lukasik", "Michal", "" ], [ "Yu", "Felix", "" ], [ "Hsieh", "Cho-Jui", "" ], [ "Dhillon", "Inderjit S", "" ], [ "Kumar", "S...
not_new_dataset
0.997431
2211.01856
Shihan Ma
Shihan Ma, Alexander Kenneth Clarke, Kostiantyn Maksymenko, Samuel Deslauriers-Gauthier, Xinjun Sheng, Xiangyang Zhu, Dario Farina
Conditional Generative Models for Simulation of EMG During Naturalistic Movements
null
null
null
null
cs.LG cs.CE eess.SP physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Numerical models of electromyographic (EMG) signals have provided a huge contribution to our fundamental understanding of human neurophysiology and remain a central pillar of motor neuroscience and the development of human-machine interfaces. However, whilst modern biophysical simulations based on finite element meth...
[ { "version": "v1", "created": "Thu, 3 Nov 2022 14:49:02 GMT" }, { "version": "v2", "created": "Wed, 15 Feb 2023 15:29:54 GMT" }, { "version": "v3", "created": "Thu, 13 Jul 2023 16:07:33 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 17:26:48 GMT" } ]
2023-10-06T00:00:00
[ [ "Ma", "Shihan", "" ], [ "Clarke", "Alexander Kenneth", "" ], [ "Maksymenko", "Kostiantyn", "" ], [ "Deslauriers-Gauthier", "Samuel", "" ], [ "Sheng", "Xinjun", "" ], [ "Zhu", "Xiangyang", "" ], [ "Farina", "Dar...
not_new_dataset
0.997392
2211.03660
Jiawang Bian
Libo Sun, Jia-Wang Bian, Huangying Zhan, Wei Yin, Ian Reid, Chunhua Shen
SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenes
Accepted for publication in TPAMI; The code will be available at https://github.com/JiawangBian/sc_depth_pl
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Self-supervised monocular depth estimation has shown impressive results in static scenes. It relies on the multi-view consistency assumption for training networks, however, that is violated in dynamic object regions and occlusions. Consequently, existing methods show poor accuracy in dynamic scenes, and the estimated...
[ { "version": "v1", "created": "Mon, 7 Nov 2022 16:17:47 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 08:53:01 GMT" } ]
2023-10-06T00:00:00
[ [ "Sun", "Libo", "" ], [ "Bian", "Jia-Wang", "" ], [ "Zhan", "Huangying", "" ], [ "Yin", "Wei", "" ], [ "Reid", "Ian", "" ], [ "Shen", "Chunhua", "" ] ]
not_new_dataset
0.997263
2211.07091
Yefei He
Yefei He, Zhenyu Lou, Luoming Zhang, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang
BiViT: Extremely Compressed Binary Vision Transformer
Accepted by ICCV 2023
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Model binarization can significantly compress model size, reduce energy consumption, and accelerate inference through efficient bit-wise operations. Although binarizing convolutional neural networks have been extensively studied, there is little work on exploring binarization of vision Transformers which underpin mos...
[ { "version": "v1", "created": "Mon, 14 Nov 2022 03:36:38 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 07:59:22 GMT" } ]
2023-10-06T00:00:00
[ [ "He", "Yefei", "" ], [ "Lou", "Zhenyu", "" ], [ "Zhang", "Luoming", "" ], [ "Liu", "Jing", "" ], [ "Wu", "Weijia", "" ], [ "Zhou", "Hong", "" ], [ "Zhuang", "Bohan", "" ] ]
not_new_dataset
0.997118
2211.11961
Arghya Chakraborty
Arghya Chakraborty, Rahul Vaze
Online facility location with timed-requests and congestion
32 pages, 6 figures
null
null
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
The classic online facility location problem deals with finding the optimal set of facilities in an online fashion when demand requests arrive one at a time and facilities need to be opened to service these requests. In this work, we study two variants of the online facility location problem; (1) weighted requests an...
[ { "version": "v1", "created": "Tue, 22 Nov 2022 02:50:51 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 15:49:18 GMT" } ]
2023-10-06T00:00:00
[ [ "Chakraborty", "Arghya", "" ], [ "Vaze", "Rahul", "" ] ]
not_new_dataset
0.997388
2211.13118
Vianney Copp\'e
Vianney Copp\'e, Xavier Gillard, Pierre Schaus
Decision Diagram-Based Branch-and-Bound with Caching for Dominance and Suboptimality Detection
Submitted to INFORMS Journal on Computing
null
null
null
cs.DS cs.AI cs.DM math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The branch-and-bound algorithm based on decision diagrams introduced by Bergman et al. in 2016 is a framework for solving discrete optimization problems with a dynamic programming formulation. It works by compiling a series of bounded-width decision diagrams that can provide lower and upper bounds for any given subpr...
[ { "version": "v1", "created": "Tue, 22 Nov 2022 10:18:33 GMT" }, { "version": "v2", "created": "Fri, 26 May 2023 15:51:22 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 13:50:18 GMT" } ]
2023-10-06T00:00:00
[ [ "Coppé", "Vianney", "" ], [ "Gillard", "Xavier", "" ], [ "Schaus", "Pierre", "" ] ]
not_new_dataset
0.997333
2212.00431
Violetta Weger
Markus Grassl, Anna-Lena Horlemann, Violetta Weger
The Subfield Metric and its Application to Quantum Error Correction
null
null
10.1142/S021949882550063X
null
cs.IT math.IT quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a new weight and corresponding metric over finite extension fields for asymmetric error correction. The weight distinguishes between elements from the base field and the ones outside of it, which is motivated by asymmetric quantum codes. We set up the theoretic framework for this weight and metric, inclu...
[ { "version": "v1", "created": "Thu, 1 Dec 2022 11:02:31 GMT" } ]
2023-10-06T00:00:00
[ [ "Grassl", "Markus", "" ], [ "Horlemann", "Anna-Lena", "" ], [ "Weger", "Violetta", "" ] ]
not_new_dataset
0.997357
2212.02648
Mazda Moayeri
Mazda Moayeri, Wenxiao Wang, Sahil Singla, Soheil Feizi
Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases
Accepted to NeurIPS '23 (Spotlight)
null
null
null
cs.CV cs.AI cs.HC cs.LG
http://creativecommons.org/licenses/by/4.0/
We present a simple but effective method to measure and mitigate model biases caused by reliance on spurious cues. Instead of requiring costly changes to one's data or model training, our method better utilizes the data one already has by sorting them. Specifically, we rank images within their classes based on spurio...
[ { "version": "v1", "created": "Mon, 5 Dec 2022 23:15:43 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 17:59:06 GMT" } ]
2023-10-06T00:00:00
[ [ "Moayeri", "Mazda", "" ], [ "Wang", "Wenxiao", "" ], [ "Singla", "Sahil", "" ], [ "Feizi", "Soheil", "" ] ]
not_new_dataset
0.996785
2212.06074
Chiyuan Zhang
Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V Varadarajan, Chiyuan Zhang
Regression with Label Differential Privacy
Appeared at ICLR '23, 28 pages, 6 figures
null
null
null
cs.LG cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the task of training regression models with the guarantee of label differential privacy (DP). Based on a global prior distribution on label values, which could be obtained privately, we derive a label DP randomization mechanism that is optimal under a given regression loss function. We prove that the optimal...
[ { "version": "v1", "created": "Mon, 12 Dec 2022 17:41:32 GMT" }, { "version": "v2", "created": "Tue, 29 Aug 2023 22:30:15 GMT" }, { "version": "v3", "created": "Wed, 4 Oct 2023 18:45:53 GMT" } ]
2023-10-06T00:00:00
[ [ "Ghazi", "Badih", "" ], [ "Kamath", "Pritish", "" ], [ "Kumar", "Ravi", "" ], [ "Leeman", "Ethan", "" ], [ "Manurangsi", "Pasin", "" ], [ "Varadarajan", "Avinash V", "" ], [ "Zhang", "Chiyuan", "" ] ]
not_new_dataset
0.997422
2212.06921
Dylan Sam
Dylan Sam, J. Zico Kolter
Losses over Labels: Weakly Supervised Learning via Direct Loss Construction
13 pages, 3 figures, AAAI 2023
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Owing to the prohibitive costs of generating large amounts of labeled data, programmatic weak supervision is a growing paradigm within machine learning. In this setting, users design heuristics that provide noisy labels for subsets of the data. These weak labels are combined (typically via a graphical model) to form ...
[ { "version": "v1", "created": "Tue, 13 Dec 2022 22:29:14 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 23:32:44 GMT" } ]
2023-10-06T00:00:00
[ [ "Sam", "Dylan", "" ], [ "Kolter", "J. Zico", "" ] ]
not_new_dataset
0.997452
2212.12055
Haiyuan Li
Haiyuan Li, Amin Emami, Karcius Assis, Antonis Vafeas, Ruizhi Yang, Reza Nejabati, Shuangyi Yan, and Dimitra Simeonidou
DRL-based Energy-Efficient Baseband Function Deployments for Service-Oriented Open RAN
null
null
null
null
cs.NI cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
Open Radio Access Network (Open RAN) has gained tremendous attention from industry and academia with decentralized baseband functions across multiple processing units located at different places. However, the ever-expanding scope of RANs, along with fluctuations in resource utilization across different locations and ...
[ { "version": "v1", "created": "Thu, 22 Dec 2022 22:07:26 GMT" }, { "version": "v2", "created": "Fri, 30 Dec 2022 21:51:34 GMT" }, { "version": "v3", "created": "Tue, 6 Jun 2023 09:00:24 GMT" }, { "version": "v4", "created": "Sun, 18 Jun 2023 13:54:38 GMT" }, { "ve...
2023-10-06T00:00:00
[ [ "Li", "Haiyuan", "" ], [ "Emami", "Amin", "" ], [ "Assis", "Karcius", "" ], [ "Vafeas", "Antonis", "" ], [ "Yang", "Ruizhi", "" ], [ "Nejabati", "Reza", "" ], [ "Yan", "Shuangyi", "" ], [ "Simeonido...
not_new_dataset
0.997202
2301.04142
Fadime Bekmambetova
Fadime Bekmambetova and Piero Triverio
Conservation properties of a leapfrog finite-difference time-domain method for the Schr\"odinger equation
36 pages, 11 figures, 5 tables
null
10.1109/TMTT.2023.3308198.
null
cs.CE physics.comp-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the probability and energy conservation properties of a leap-frog finite-difference time-domain (FDTD) method for solving the Schr\"odinger equation. We propose expressions for the total numerical probability and energy contained in a region, and for the flux of probability current and power through its boun...
[ { "version": "v1", "created": "Tue, 10 Jan 2023 16:38:58 GMT" }, { "version": "v2", "created": "Wed, 12 Jul 2023 03:45:26 GMT" } ]
2023-10-06T00:00:00
[ [ "Bekmambetova", "Fadime", "" ], [ "Triverio", "Piero", "" ] ]
not_new_dataset
0.997226
2301.04494
Inder Pal Singh
Indel Pal Singh, Enjie Ghorbel, Oyebade Oyedotun, Djamila Aouada
Multi-label Image Classification using Adaptive Graph Convolutional Networks: from a Single Domain to Multiple Domains
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
This paper proposes an adaptive graph-based approach for multi-label image classification. Graph-based methods have been largely exploited in the field of multi-label classification, given their ability to model label correlations. Specifically, their effectiveness has been proven not only when considering a single d...
[ { "version": "v1", "created": "Wed, 11 Jan 2023 14:42:47 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 09:28:57 GMT" } ]
2023-10-06T00:00:00
[ [ "Singh", "Indel Pal", "" ], [ "Ghorbel", "Enjie", "" ], [ "Oyedotun", "Oyebade", "" ], [ "Aouada", "Djamila", "" ] ]
not_new_dataset
0.997144
2301.04554
Wei Guo
Wei Guo, Benedetta Tondi, Mauro Barni
Universal Detection of Backdoor Attacks via Density-based Clustering and Centroids Analysis
null
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
We propose a Universal Defence against backdoor attacks based on Clustering and Centroids Analysis (CCA-UD). The goal of the defence is to reveal whether a Deep Neural Network model is subject to a backdoor attack by inspecting the training dataset. CCA-UD first clusters the samples of the training set by means of de...
[ { "version": "v1", "created": "Wed, 11 Jan 2023 16:31:38 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 13:26:33 GMT" } ]
2023-10-06T00:00:00
[ [ "Guo", "Wei", "" ], [ "Tondi", "Benedetta", "" ], [ "Barni", "Mauro", "" ] ]
not_new_dataset
0.99736
2301.05603
Shiye Lei
Shiye Lei and Dacheng Tao
A Comprehensive Survey of Dataset Distillation
Accepted by IEEE TPAMI
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning technology has developed unprecedentedly in the last decade and has become the primary choice in many application domains. This progress is mainly attributed to a systematic collaboration in which rapidly growing computing resources encourage advanced algorithms to deal with massive data. However, it ha...
[ { "version": "v1", "created": "Fri, 13 Jan 2023 15:11:38 GMT" }, { "version": "v2", "created": "Tue, 7 Feb 2023 09:21:44 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 01:09:29 GMT" } ]
2023-10-06T00:00:00
[ [ "Lei", "Shiye", "" ], [ "Tao", "Dacheng", "" ] ]
not_new_dataset
0.997412
2301.06421
Pei-Yu Chen
Pei-Yu Chen, Myrthe L. Tielman, Dirk K.J. Heylen, Catholijn M. Jonker, M. Birna van Riemsdijk
AI Alignment Dialogues: An Interactive Approach to AI Alignment in Support Agents
Withdraw because the content of the paper has been largely revised. The newest version is very different than the submitted one
null
null
null
cs.AI cs.HC
http://creativecommons.org/licenses/by/4.0/
AI alignment is about ensuring AI systems only pursue goals and activities that are beneficial to humans. Most of the current approach to AI alignment is to learn what humans value from their behavioural data. This paper proposes a different way of looking at the notion of alignment, namely by introducing AI Alignmen...
[ { "version": "v1", "created": "Mon, 16 Jan 2023 13:19:53 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 11:15:23 GMT" } ]
2023-10-06T00:00:00
[ [ "Chen", "Pei-Yu", "" ], [ "Tielman", "Myrthe L.", "" ], [ "Heylen", "Dirk K. J.", "" ], [ "Jonker", "Catholijn M.", "" ], [ "van Riemsdijk", "M. Birna", "" ] ]
not_new_dataset
0.99743
2301.07305
Mohammed Shafae
Md Habibor Rahman (1), Erfan Yazdandoost Hamedani (1), Young-Jun Son (2), Mohammed Shafae (1) ((1) The University of Arizona, (2) Purdue University)
Graph-Theoretic Approach for Manufacturing Cybersecurity Risk Modeling and Assessment
25 pages, 10 figures
null
null
null
cs.CR cs.SY eess.SY math.OC
http://creativecommons.org/licenses/by-nc-nd/4.0/
Identifying, analyzing, and evaluating cybersecurity risks are essential to assess the vulnerabilities of modern manufacturing infrastructures and to devise effective decision-making strategies to secure critical manufacturing against potential cyberattacks. In response, this work proposes a graph-theoretic approach ...
[ { "version": "v1", "created": "Wed, 18 Jan 2023 04:54:00 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 22:42:06 GMT" } ]
2023-10-06T00:00:00
[ [ "Rahman", "Md Habibor", "" ], [ "Hamedani", "Erfan Yazdandoost", "" ], [ "Son", "Young-Jun", "" ], [ "Shafae", "Mohammed", "" ] ]
not_new_dataset
0.997348
2301.09350
Anastasios Nentidis
Anastasios Nentidis, Thomas Chatzopoulos, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras
Large-scale investigation of weakly-supervised deep learning for the fine-grained semantic indexing of biomedical literature
26 pages, 5 figures, 4 tables. A more concise version
Journal of Biomedical Informatics, Volume 146, 2023, 104499, ISSN 1532-0464
10.1016/j.jbi.2023.104499
null
cs.CL cs.DL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Objective: Semantic indexing of biomedical literature is usually done at the level of MeSH descriptors with several related but distinct biomedical concepts often grouped together and treated as a single topic. This study proposes a new method for the automated refinement of subject annotations at the level of MeSH c...
[ { "version": "v1", "created": "Mon, 23 Jan 2023 10:33:22 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 14:17:39 GMT" } ]
2023-10-06T00:00:00
[ [ "Nentidis", "Anastasios", "" ], [ "Chatzopoulos", "Thomas", "" ], [ "Krithara", "Anastasia", "" ], [ "Tsoumakas", "Grigorios", "" ], [ "Paliouras", "Georgios", "" ] ]
not_new_dataset
0.997367
2302.00589
Ghazal Kalhor
Ghazal Kalhor, Tanin Zeraati, Behnam Bahrak
Diversity dilemmas: uncovering gender and nationality biases in graduate admissions across top North American computer science programs
null
null
10.1140/epjds/s13688-023-00422-5
null
cs.CY cs.SI
http://creativecommons.org/licenses/by/4.0/
Although different organizations have defined policies towards diversity in academia, many argue that minorities are still disadvantaged in university admissions due to biases. Extensive research has been conducted on detecting partiality patterns in the academic community. However, in the last few decades, limited r...
[ { "version": "v1", "created": "Wed, 1 Feb 2023 17:02:08 GMT" }, { "version": "v2", "created": "Tue, 29 Aug 2023 19:30:27 GMT" } ]
2023-10-06T00:00:00
[ [ "Kalhor", "Ghazal", "" ], [ "Zeraati", "Tanin", "" ], [ "Bahrak", "Behnam", "" ] ]
new_dataset
0.996857
2302.00942
Han Lin
Krzysztof Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Avinava Dubey, Deepali Jain, Tamas Sarlos, Snigdha Chaturvedi, Adrian Weller
Efficient Graph Field Integrators Meet Point Clouds
null
ICML 2023
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
We present two new classes of algorithms for efficient field integration on graphs encoding point clouds. The first class, SeparatorFactorization(SF), leverages the bounded genus of point cloud mesh graphs, while the second class, RFDiffusion(RFD), uses popular epsilon-nearest-neighbor graph representations for point...
[ { "version": "v1", "created": "Thu, 2 Feb 2023 08:33:36 GMT" }, { "version": "v2", "created": "Sun, 5 Feb 2023 20:12:24 GMT" }, { "version": "v3", "created": "Wed, 12 Apr 2023 22:27:17 GMT" }, { "version": "v4", "created": "Sat, 10 Jun 2023 01:29:45 GMT" }, { "ver...
2023-10-06T00:00:00
[ [ "Choromanski", "Krzysztof", "" ], [ "Sehanobish", "Arijit", "" ], [ "Lin", "Han", "" ], [ "Zhao", "Yunfan", "" ], [ "Berger", "Eli", "" ], [ "Parshakova", "Tetiana", "" ], [ "Pan", "Alvin", "" ], [ ...
not_new_dataset
0.997327
2302.02394
Zuopeng Yang
Zuopeng Yang, Tianshu Chu, Xin Lin, Erdun Gao, Daqing Liu, Jie Yang, Chaoyue Wang
Eliminating Contextual Prior Bias for Semantic Image Editing via Dual-Cycle Diffusion
This paper has been accepted by the IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
The recent success of text-to-image generation diffusion models has also revolutionized semantic image editing, enabling the manipulation of images based on query/target texts. Despite these advancements, a significant challenge lies in the potential introduction of contextual prior bias in pre-trained models during ...
[ { "version": "v1", "created": "Sun, 5 Feb 2023 14:30:22 GMT" }, { "version": "v2", "created": "Tue, 7 Feb 2023 02:57:45 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 14:35:08 GMT" } ]
2023-10-06T00:00:00
[ [ "Yang", "Zuopeng", "" ], [ "Chu", "Tianshu", "" ], [ "Lin", "Xin", "" ], [ "Gao", "Erdun", "" ], [ "Liu", "Daqing", "" ], [ "Yang", "Jie", "" ], [ "Wang", "Chaoyue", "" ] ]
not_new_dataset
0.99726
2302.02787
Lena Mangold
Lena Mangold and Camille Roth
Generative models for two-ground-truth partitions in networks
null
null
null
null
cs.SI cond-mat.stat-mech cs.LG physics.data-an physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A myriad of approaches have been proposed to characterise the mesoscale structure of networks - most often as a partition based on patterns variously called communities, blocks, or clusters. Clearly, distinct methods designed to detect different types of patterns may provide a variety of answers to the network's meso...
[ { "version": "v1", "created": "Mon, 6 Feb 2023 14:02:28 GMT" }, { "version": "v2", "created": "Tue, 4 Jul 2023 19:01:52 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 13:00:34 GMT" } ]
2023-10-06T00:00:00
[ [ "Mangold", "Lena", "" ], [ "Roth", "Camille", "" ] ]
not_new_dataset
0.997372
2302.02936
Alex Bie
Alex Bie, Gautam Kamath, Guojun Zhang
Private GANs, Revisited
28 pages; revisions and new experiments from TMLR camera-ready + code release at https://github.com/alexbie98/dpgan-revisit
null
null
null
cs.LG cs.CR cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We show that the canonical approach for training differentially private GANs -- updating the discriminator with differentially private stochastic gradient descent (DPSGD) -- can yield significantly improved results after modifications to training. Specifically, we propose that existing instantiations of this approach...
[ { "version": "v1", "created": "Mon, 6 Feb 2023 17:11:09 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 04:47:52 GMT" } ]
2023-10-06T00:00:00
[ [ "Bie", "Alex", "" ], [ "Kamath", "Gautam", "" ], [ "Zhang", "Guojun", "" ] ]
not_new_dataset
0.997418
2302.04054
Michael Hagmann
Michael Hagmann, Philipp Meier and Stefan Riezler
Towards Inferential Reproducibility of Machine Learning Research
Published at ICLR 2023
null
null
null
cs.LG cs.AI cs.CL stat.AP stat.ML
http://creativecommons.org/licenses/by/4.0/
Reliability of machine learning evaluation -- the consistency of observed evaluation scores across replicated model training runs -- is affected by several sources of nondeterminism which can be regarded as measurement noise. Current tendencies to remove noise in order to enforce reproducibility of research results n...
[ { "version": "v1", "created": "Wed, 8 Feb 2023 13:47:00 GMT" }, { "version": "v2", "created": "Fri, 10 Feb 2023 10:45:09 GMT" }, { "version": "v3", "created": "Thu, 16 Feb 2023 13:56:26 GMT" }, { "version": "v4", "created": "Wed, 8 Mar 2023 11:37:27 GMT" }, { "ver...
2023-10-06T00:00:00
[ [ "Hagmann", "Michael", "" ], [ "Meier", "Philipp", "" ], [ "Riezler", "Stefan", "" ] ]
not_new_dataset
0.997504
2302.11791
Gyanendra Kumar Verma
Gyanendra K. Verma and R. K. Sharma
Additive complementary dual codes over $\mathbb{F}_{q^2}$
There has been major changes in this manuscript we will submit new one
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Shi et al. [Additive complementary dual codes over F4. Designs, Codes and Cryptography, 2022.] studied additive codes over the finite field F4 with respect to trace Hermitian and trace Euclidean inner products. In this article, we define additive codes of length n over finite field Fq2 as additive subgroups of Fn q2 ...
[ { "version": "v1", "created": "Thu, 23 Feb 2023 06:12:14 GMT" }, { "version": "v2", "created": "Sat, 6 May 2023 17:38:14 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 09:08:46 GMT" } ]
2023-10-06T00:00:00
[ [ "Verma", "Gyanendra K.", "" ], [ "Sharma", "R. K.", "" ] ]
not_new_dataset
0.996993
2303.00047
Indranil Saha
Ratijit Mitra and Indranil Saha
Online On-Demand Multi-Robot Coverage Path Planning
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an online centralized path planning algorithm to cover a large, complex, unknown workspace with multiple homogeneous mobile robots. Our algorithm is horizon-based, synchronous, and on-demand. The recently proposed horizon-based synchronous algorithms compute all the robots' paths in each horizon, significa...
[ { "version": "v1", "created": "Tue, 28 Feb 2023 19:43:23 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 10:02:31 GMT" } ]
2023-10-06T00:00:00
[ [ "Mitra", "Ratijit", "" ], [ "Saha", "Indranil", "" ] ]
not_new_dataset
0.997114
2303.01338
Amira Guesmi
Amira Guesmi, Muhammad Abdullah Hanif, and Muhammad Shafique
AdvRain: Adversarial Raindrops to Attack Camera-based Smart Vision Systems
null
null
null
null
cs.CV cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vision-based perception modules are increasingly deployed in many applications, especially autonomous vehicles and intelligent robots. These modules are being used to acquire information about the surroundings and identify obstacles. Hence, accurate detection and classification are essential to reach appropriate deci...
[ { "version": "v1", "created": "Thu, 2 Mar 2023 15:14:46 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 11:55:37 GMT" } ]
2023-10-06T00:00:00
[ [ "Guesmi", "Amira", "" ], [ "Hanif", "Muhammad Abdullah", "" ], [ "Shafique", "Muhammad", "" ] ]
not_new_dataset
0.997012
2303.02950
Ying Gao
Ying Gao, Qingqing Wu, Wen Chen, Celimuge Wu, Derrick Wing Kwan Ng, Naofal Al-Dhahir
Exploiting Intelligent Reflecting Surfaces for Interference Channels with SWIPT
30 pages, accepted by IEEE Transactions on Wireless Communications
null
10.1109/TWC.2023.3318795
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper considers intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) in a multi-user multiple-input single-output (MISO) interference channel (IFC), where multiple transmitters (Txs) serve their corresponding receivers (Rxs) in a shared spectrum with the aid of ...
[ { "version": "v1", "created": "Mon, 6 Mar 2023 07:44:05 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 17:09:30 GMT" } ]
2023-10-06T00:00:00
[ [ "Gao", "Ying", "" ], [ "Wu", "Qingqing", "" ], [ "Chen", "Wen", "" ], [ "Wu", "Celimuge", "" ], [ "Ng", "Derrick Wing Kwan", "" ], [ "Al-Dhahir", "Naofal", "" ] ]
not_new_dataset
0.997425
2303.06088
Marin Scalbert
Marin Scalbert and Maria Vakalopoulou and Florent Couzini\'e-Devy
Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization
Under review as conference paper
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
In Self-Supervised Learning (SSL), models are typically pretrained, fine-tuned, and evaluated on the same domains. However, they tend to perform poorly when evaluated on unseen domains, a challenge that Unsupervised Domain Generalization (UDG) seeks to address. Current UDG methods rely on domain labels, which are oft...
[ { "version": "v1", "created": "Fri, 10 Mar 2023 17:09:04 GMT" }, { "version": "v2", "created": "Mon, 13 Mar 2023 10:05:01 GMT" }, { "version": "v3", "created": "Mon, 24 Apr 2023 10:04:08 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 09:55:46 GMT" } ]
2023-10-06T00:00:00
[ [ "Scalbert", "Marin", "" ], [ "Vakalopoulou", "Maria", "" ], [ "Couzinié-Devy", "Florent", "" ] ]
not_new_dataset
0.99744
2303.09230
Xie Yi
Yi Xie, Huaidong Zhang, Xuemiao Xu, Jianqing Zhu, Shengfeng He
Towards a Smaller Student: Capacity Dynamic Distillation for Efficient Image Retrieval
Accepted by CVPR2023
Towards a Smaller Student: Capacity Dynamic Distillation for Efficient Image Retrieval, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023,16006-16015
10.1109/CVPR52729.2023.01536
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Previous Knowledge Distillation based efficient image retrieval methods employs a lightweight network as the student model for fast inference. However, the lightweight student model lacks adequate representation capacity for effective knowledge imitation during the most critical early training period, causing final p...
[ { "version": "v1", "created": "Thu, 16 Mar 2023 11:09:22 GMT" }, { "version": "v2", "created": "Wed, 31 May 2023 15:32:48 GMT" } ]
2023-10-06T00:00:00
[ [ "Xie", "Yi", "" ], [ "Zhang", "Huaidong", "" ], [ "Xu", "Xuemiao", "" ], [ "Zhu", "Jianqing", "" ], [ "He", "Shengfeng", "" ] ]
not_new_dataset
0.997303
2303.09234
Yining Jiao
Yining Jiao, Carlton Zdanski, Julia Kimbell, Andrew Prince, Cameron Worden, Samuel Kirse, Christopher Rutter, Benjamin Shields, William Dunn, Jisan Mahmud, Marc Niethammer
NAISR: A 3D Neural Additive Model for Interpretable Shape Representation
28 pages
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Deep implicit functions (DIFs) have emerged as a powerful paradigm for many computer vision tasks such as 3D shape reconstruction, generation, registration, completion, editing, and understanding. However, given a set of 3D shapes with associated covariates there is at present no shape representation method which all...
[ { "version": "v1", "created": "Thu, 16 Mar 2023 11:18:04 GMT" }, { "version": "v2", "created": "Sat, 18 Mar 2023 12:13:19 GMT" }, { "version": "v3", "created": "Tue, 28 Mar 2023 20:07:21 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 09:25:26 GMT" } ]
2023-10-06T00:00:00
[ [ "Jiao", "Yining", "" ], [ "Zdanski", "Carlton", "" ], [ "Kimbell", "Julia", "" ], [ "Prince", "Andrew", "" ], [ "Worden", "Cameron", "" ], [ "Kirse", "Samuel", "" ], [ "Rutter", "Christopher", "" ], [ ...
not_new_dataset
0.996392
2303.09874
Alexander Hepburn
Alexander Hepburn, Valero Laparra, Ra\'ul Santos-Rodriguez, Jes\'us Malo
Disentangling the Link Between Image Statistics and Human Perception
null
null
null
null
cs.CV cs.LG q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the 1950s, Barlow and Attneave hypothesised a link between biological vision and information maximisation. Following Shannon, information was defined using the probability of natural images. A number of physiological and psychophysical phenomena have been derived ever since from principles like info-max, efficient...
[ { "version": "v1", "created": "Fri, 17 Mar 2023 10:38:27 GMT" }, { "version": "v2", "created": "Mon, 2 Oct 2023 09:40:54 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 14:06:32 GMT" } ]
2023-10-06T00:00:00
[ [ "Hepburn", "Alexander", "" ], [ "Laparra", "Valero", "" ], [ "Santos-Rodriguez", "Raúl", "" ], [ "Malo", "Jesús", "" ] ]
not_new_dataset
0.997416
2303.10650
Natalia \'Slusarz
Natalia \'Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert Stewart, Kathrin Stark
Logic of Differentiable Logics: Towards a Uniform Semantics of DL
LPAR'23
null
null
null
cs.LO cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Differentiable logics (DL) have recently been proposed as a method of training neural networks to satisfy logical specifications. A DL consists of a syntax in which specifications are stated and an interpretation function that translates expressions in the syntax into loss functions. These loss functions can then be ...
[ { "version": "v1", "created": "Sun, 19 Mar 2023 13:03:51 GMT" }, { "version": "v2", "created": "Mon, 15 May 2023 13:30:45 GMT" }, { "version": "v3", "created": "Wed, 24 May 2023 13:33:37 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 11:17:08 GMT" } ]
2023-10-06T00:00:00
[ [ "Ślusarz", "Natalia", "" ], [ "Komendantskaya", "Ekaterina", "" ], [ "Daggitt", "Matthew L.", "" ], [ "Stewart", "Robert", "" ], [ "Stark", "Kathrin", "" ] ]
not_new_dataset
0.997339
2303.12214
Jingwei Zhang
Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Joel Saltz, Maria Vakalopoulou, Dimitris Samaras
Prompt-MIL: Boosting Multi-Instance Learning Schemes via Task-specific Prompt Tuning
Accepted to MICCAI 2023 (Oral)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Whole slide image (WSI) classification is a critical task in computational pathology, requiring the processing of gigapixel-sized images, which is challenging for current deep-learning methods. Current state of the art methods are based on multi-instance learning schemes (MIL), which usually rely on pretrained featur...
[ { "version": "v1", "created": "Tue, 21 Mar 2023 22:24:27 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 03:50:19 GMT" } ]
2023-10-06T00:00:00
[ [ "Zhang", "Jingwei", "" ], [ "Kapse", "Saarthak", "" ], [ "Ma", "Ke", "" ], [ "Prasanna", "Prateek", "" ], [ "Saltz", "Joel", "" ], [ "Vakalopoulou", "Maria", "" ], [ "Samaras", "Dimitris", "" ] ]
not_new_dataset
0.99728
2303.14655
Ji Qi
Ji Qi, Jifan Yu, Teng Tu, Kunyu Gao, Yifan Xu, Xinyu Guan, Xiaozhi Wang, Yuxiao Dong, Bin Xu, Lei Hou, Juanzi Li, Jie Tang, Weidong Guo, Hui Liu, Yu Xu
GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation
Accepted by CIKM 2023
null
null
null
cs.CV cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the recent emergence of video captioning models, how to generate vivid, fine-grained video descriptions based on the background knowledge (i.e., long and informative commentary about the domain-specific scenes with appropriate reasoning) is still far from being solved, which however has great applications suc...
[ { "version": "v1", "created": "Sun, 26 Mar 2023 08:43:36 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 06:55:13 GMT" } ]
2023-10-06T00:00:00
[ [ "Qi", "Ji", "" ], [ "Yu", "Jifan", "" ], [ "Tu", "Teng", "" ], [ "Gao", "Kunyu", "" ], [ "Xu", "Yifan", "" ], [ "Guan", "Xinyu", "" ], [ "Wang", "Xiaozhi", "" ], [ "Dong", "Yuxiao", "" ], ...
new_dataset
0.997324
2303.15375
Yan Sun
Yan Sun, Yifan Yuan, Zeduo Yu, Reese Kuper, Chihun Song, Jinghan Huang, Houxiang Ji, Siddharth Agarwal, Jiaqi Lou, Ipoom Jeong, Ren Wang, Jung Ho Ahn, Tianyin Xu, Nam Sung Kim
Demystifying CXL Memory with Genuine CXL-Ready Systems and Devices
This paper has been accepted by MICRO'23. Please refer to the https://doi.org/10.1145/3613424.3614256 for the official version of this paper
null
10.1145/3613424.3614256
null
cs.PF cs.AR
http://creativecommons.org/licenses/by/4.0/
The ever-growing demands for memory with larger capacity and higher bandwidth have driven recent innovations on memory expansion and disaggregation technologies based on Compute eXpress Link (CXL). Especially, CXL-based memory expansion technology has recently gained notable attention for its ability not only to econ...
[ { "version": "v1", "created": "Mon, 27 Mar 2023 16:51:26 GMT" }, { "version": "v2", "created": "Tue, 4 Apr 2023 04:25:32 GMT" }, { "version": "v3", "created": "Sun, 30 Jul 2023 22:40:13 GMT" }, { "version": "v4", "created": "Thu, 5 Oct 2023 03:58:56 GMT" } ]
2023-10-06T00:00:00
[ [ "Sun", "Yan", "" ], [ "Yuan", "Yifan", "" ], [ "Yu", "Zeduo", "" ], [ "Kuper", "Reese", "" ], [ "Song", "Chihun", "" ], [ "Huang", "Jinghan", "" ], [ "Ji", "Houxiang", "" ], [ "Agarwal", "Siddha...
not_new_dataset
0.997382
2303.16887
Guan Zhe Hong
Guan Zhe Hong, Yin Cui, Ariel Fuxman, Stanley H. Chan, Enming Luo
Towards Understanding the Effect of Pretraining Label Granularity
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we study how the granularity of pretraining labels affects the generalization of deep neural networks in image classification tasks. We focus on the "fine-to-coarse" transfer learning setting, where the pretraining label space is more fine-grained than that of the target problem. Empirically, we show t...
[ { "version": "v1", "created": "Wed, 29 Mar 2023 17:56:36 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 17:32:26 GMT" } ]
2023-10-06T00:00:00
[ [ "Hong", "Guan Zhe", "" ], [ "Cui", "Yin", "" ], [ "Fuxman", "Ariel", "" ], [ "Chan", "Stanley H.", "" ], [ "Luo", "Enming", "" ] ]
not_new_dataset
0.997515
2304.03752
Jiaqi Wang
Jiaqi Wang, Pan Zhang, Tao Chu, Yuhang Cao, Yujie Zhou, Tong Wu, Bin Wang, Conghui He, Dahua Lin
V3Det: Vast Vocabulary Visual Detection Dataset
ICCV 2023 Oral Camera Ready
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in detecting arbitrary objects in the real world are trained and evaluated on object detection datasets with a relatively restricted vocabulary. To facilitate the development of more general visual object detection, we propose V3Det, a vast vocabulary visual detection dataset with precisely annotated ...
[ { "version": "v1", "created": "Fri, 7 Apr 2023 17:45:35 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 12:18:14 GMT" } ]
2023-10-06T00:00:00
[ [ "Wang", "Jiaqi", "" ], [ "Zhang", "Pan", "" ], [ "Chu", "Tao", "" ], [ "Cao", "Yuhang", "" ], [ "Zhou", "Yujie", "" ], [ "Wu", "Tong", "" ], [ "Wang", "Bin", "" ], [ "He", "Conghui", "" ],...
new_dataset
0.997916
2304.04327
Jinyi Ye
Jinyi Ye, Nikhil Jindal, Francesco Pierri, Luca Luceri
Online Networks of Support in Distressed Environments: Solidarity and Mobilization during the Russian Invasion of Ukraine
Presented at ICWSM2023 Workshop "Data for the Wellbeing of Most Vulnerable"
Proceedings of the ICWSM Workshops 2023
10.36190/2023.05
null
cs.SI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Despite their drawbacks and unintended consequences, social media networks have recently emerged as a crucial resource for individuals in distress, particularly during times of crisis. These platforms serve as a means to seek assistance and support, share reliable information, and appeal for action and solidarity. In...
[ { "version": "v1", "created": "Sun, 9 Apr 2023 23:27:59 GMT" }, { "version": "v2", "created": "Mon, 15 May 2023 22:17:40 GMT" }, { "version": "v3", "created": "Wed, 4 Oct 2023 21:59:32 GMT" } ]
2023-10-06T00:00:00
[ [ "Ye", "Jinyi", "" ], [ "Jindal", "Nikhil", "" ], [ "Pierri", "Francesco", "" ], [ "Luceri", "Luca", "" ] ]
not_new_dataset
0.99743
2304.05128
Xinyun Chen
Xinyun Chen, Maxwell Lin, Nathanael Sch\"arli, Denny Zhou
Teaching Large Language Models to Self-Debug
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Large language models (LLMs) have achieved impressive performance on code generation. However, for complex programming tasks, generating the correct solution in one go becomes challenging, thus some prior works have designed program repair approaches to improve code generation performance. In this work, we propose Se...
[ { "version": "v1", "created": "Tue, 11 Apr 2023 10:43:43 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 09:12:07 GMT" } ]
2023-10-06T00:00:00
[ [ "Chen", "Xinyun", "" ], [ "Lin", "Maxwell", "" ], [ "Schärli", "Nathanael", "" ], [ "Zhou", "Denny", "" ] ]
not_new_dataset
0.977384
2304.06715
Jonathan Crabb\'e
Jonathan Crabb\'e, Mihaela van der Schaar
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance
Presented at NeurIPS 2023
null
null
null
cs.LG cs.AI cs.CG
http://creativecommons.org/licenses/by/4.0/
Interpretability methods are valuable only if their explanations faithfully describe the explained model. In this work, we consider neural networks whose predictions are invariant under a specific symmetry group. This includes popular architectures, ranging from convolutional to graph neural networks. Any explanation...
[ { "version": "v1", "created": "Thu, 13 Apr 2023 17:59:03 GMT" }, { "version": "v2", "created": "Fri, 12 May 2023 17:59:25 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 15:29:01 GMT" } ]
2023-10-06T00:00:00
[ [ "Crabbé", "Jonathan", "" ], [ "van der Schaar", "Mihaela", "" ] ]
not_new_dataset
0.997409
2304.08247
Keno Bressem
Tianyu Han and Lisa C. Adams and Jens-Michalis Papaioannou and Paul Grundmann and Tom Oberhauser and Alexander L\"oser and Daniel Truhn and Keno K. Bressem
MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
As large language models (LLMs) like OpenAI's GPT series continue to make strides, we witness the emergence of artificial intelligence applications in an ever-expanding range of fields. In medicine, these LLMs hold considerable promise for improving medical workflows, diagnostics, patient care, and education. Yet, th...
[ { "version": "v1", "created": "Fri, 14 Apr 2023 11:28:08 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 23:28:00 GMT" } ]
2023-10-06T00:00:00
[ [ "Han", "Tianyu", "" ], [ "Adams", "Lisa C.", "" ], [ "Papaioannou", "Jens-Michalis", "" ], [ "Grundmann", "Paul", "" ], [ "Oberhauser", "Tom", "" ], [ "Löser", "Alexander", "" ], [ "Truhn", "Daniel", "" ]...
new_dataset
0.997839
2304.08979
Xinyue Shen
Xinyue Shen and Zeyuan Chen and Michael Backes and Yang Zhang
In ChatGPT We Trust? Measuring and Characterizing the Reliability of ChatGPT
null
null
null
null
cs.CR cs.LG
http://creativecommons.org/licenses/by/4.0/
The way users acquire information is undergoing a paradigm shift with the advent of ChatGPT. Unlike conventional search engines, ChatGPT retrieves knowledge from the model itself and generates answers for users. ChatGPT's impressive question-answering (QA) capability has attracted more than 100 million users within a...
[ { "version": "v1", "created": "Tue, 18 Apr 2023 13:20:45 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 13:27:12 GMT" } ]
2023-10-06T00:00:00
[ [ "Shen", "Xinyue", "" ], [ "Chen", "Zeyuan", "" ], [ "Backes", "Michael", "" ], [ "Zhang", "Yang", "" ] ]
not_new_dataset
0.997463
2304.09666
Marc Fuchs
Marc Fuchs and Fabian Kuhn
List Defective Colorings: Distributed Algorithms and Applications
null
null
10.4230/LIPIcs.DISC.2023.22
null
cs.DC cs.DS
http://creativecommons.org/licenses/by/4.0/
The distributed coloring problem is at the core of the area of distributed graph algorithms and it is a problem that has seen tremendous progress over the last few years. Much of the remarkable recent progress on deterministic distributed coloring algorithms is based on two main tools: a) defective colorings in which...
[ { "version": "v1", "created": "Wed, 19 Apr 2023 13:52:47 GMT" }, { "version": "v2", "created": "Mon, 7 Aug 2023 14:23:40 GMT" } ]
2023-10-06T00:00:00
[ [ "Fuchs", "Marc", "" ], [ "Kuhn", "Fabian", "" ] ]
not_new_dataset
0.997405
2304.11004
Huayu Li
Huayu Li, Xiwen Chen, Gregory Ditzler, Janet Roveda, Ao Li
Knowledge Distillation Under Ideal Joint Classifier Assumption
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge distillation constitutes a potent methodology for condensing substantial neural networks into more compact and efficient counterparts. Within this context, softmax regression representation learning serves as a widely embraced approach, leveraging a pre-established teacher network to guide the learning proc...
[ { "version": "v1", "created": "Wed, 19 Apr 2023 21:06:00 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 23:33:35 GMT" } ]
2023-10-06T00:00:00
[ [ "Li", "Huayu", "" ], [ "Chen", "Xiwen", "" ], [ "Ditzler", "Gregory", "" ], [ "Roveda", "Janet", "" ], [ "Li", "Ao", "" ] ]
not_new_dataset
0.997422
2304.14420
Albert Lam
Albert Lam, Mihai Anitescu, Anirudh Subramanyam
Network Cascade Vulnerability using Constrained Bayesian Optimization
13 pages, 5 figures
null
null
null
cs.SI cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Measures of power grid vulnerability are often assessed by the amount of damage an adversary can exact on the network. However, the cascading impact of such attacks is often overlooked, even though cascades are one of the primary causes of large-scale blackouts. This paper explores modifications of transmission line ...
[ { "version": "v1", "created": "Thu, 27 Apr 2023 02:31:20 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 02:19:18 GMT" } ]
2023-10-06T00:00:00
[ [ "Lam", "Albert", "" ], [ "Anitescu", "Mihai", "" ], [ "Subramanyam", "Anirudh", "" ] ]
not_new_dataset
0.997363
2304.14993
Dhruv Kumar
Ishika Joshi, Ritvik Budhiraja, Harshal Dev, Jahnvi Kadia, M. Osama Ataullah, Sayan Mitra, Dhruv Kumar, Harshal D. Akolekar
ChatGPT in the Classroom: An Analysis of Its Strengths and Weaknesses for Solving Undergraduate Computer Science Questions
Accepted in SIGCSE TS 2024
null
null
null
cs.HC cs.AI cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
ChatGPT is an AI language model developed by OpenAI that can understand and generate human-like text. It can be used for a variety of use cases such as language generation, question answering, text summarization, chatbot development, language translation, sentiment analysis, content creation, personalization, text co...
[ { "version": "v1", "created": "Fri, 28 Apr 2023 17:26:32 GMT" }, { "version": "v2", "created": "Wed, 17 May 2023 14:44:32 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 04:18:28 GMT" } ]
2023-10-06T00:00:00
[ [ "Joshi", "Ishika", "" ], [ "Budhiraja", "Ritvik", "" ], [ "Dev", "Harshal", "" ], [ "Kadia", "Jahnvi", "" ], [ "Ataullah", "M. Osama", "" ], [ "Mitra", "Sayan", "" ], [ "Kumar", "Dhruv", "" ], [ "Ak...
not_new_dataset
0.997434
2305.06410
Hsueh-Ti Derek Liu
Hsueh-Ti Derek Liu, Mark Gillespie, Benjamin Chislett, Nicholas Sharp, Alec Jacobson, Keenan Crane
Surface Simplification using Intrinsic Error Metrics
SIGGRAPH 2023
ACM Transactions on Graphics, Vol.42, No. 4, August 2023
null
null
cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper describes a method for fast simplification of surface meshes. Whereas past methods focus on visual appearance, our goal is to solve equations on the surface. Hence, rather than approximate the extrinsic geometry, we construct a coarse intrinsic triangulation of the input domain. In the spirit of the quadri...
[ { "version": "v1", "created": "Wed, 10 May 2023 18:41:48 GMT" }, { "version": "v2", "created": "Wed, 4 Oct 2023 18:11:24 GMT" } ]
2023-10-06T00:00:00
[ [ "Liu", "Hsueh-Ti Derek", "" ], [ "Gillespie", "Mark", "" ], [ "Chislett", "Benjamin", "" ], [ "Sharp", "Nicholas", "" ], [ "Jacobson", "Alec", "" ], [ "Crane", "Keenan", "" ] ]
not_new_dataset
0.996532
2305.07962
Constantin Runge
Constantin Runge and Thomas Wiegart and Diego Lentner
Improved List Decoding for Polar-Coded Probabilistic Shaping
5 pages, 3 figures; as presented at ISTC 2023
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A modified successive cancellation list (SCL) decoder is proposed for polar-coded probabilistic shaping. The decoder exploits the deterministic encoding rule for shaping bits to rule out candidate code words that the encoder would not generate. This provides error detection and decreases error rates compared to stand...
[ { "version": "v1", "created": "Sat, 13 May 2023 16:41:56 GMT" }, { "version": "v2", "created": "Tue, 22 Aug 2023 08:38:12 GMT" }, { "version": "v3", "created": "Thu, 5 Oct 2023 14:37:51 GMT" } ]
2023-10-06T00:00:00
[ [ "Runge", "Constantin", "" ], [ "Wiegart", "Thomas", "" ], [ "Lentner", "Diego", "" ] ]
not_new_dataset
0.996789
2305.11779
Huitong Pan
Huitong Pan, Qi Zhang, Eduard Dragut, Cornelia Caragea, Longin Jan Latecki
DMDD: A Large-Scale Dataset for Dataset Mentions Detection
Pre-MIT Press publication version. Submitted to TACL
Transactions of the Association for Computational Linguistics. 11 (2023) 1132-1146
10.1162/tacl_a_00592
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
The recognition of dataset names is a critical task for automatic information extraction in scientific literature, enabling researchers to understand and identify research opportunities. However, existing corpora for dataset mention detection are limited in size and naming diversity. In this paper, we introduce the D...
[ { "version": "v1", "created": "Fri, 19 May 2023 16:18:00 GMT" } ]
2023-10-06T00:00:00
[ [ "Pan", "Huitong", "" ], [ "Zhang", "Qi", "" ], [ "Dragut", "Eduard", "" ], [ "Caragea", "Cornelia", "" ], [ "Latecki", "Longin Jan", "" ] ]
new_dataset
0.997837
2305.12081
Zifeng Wang
Zifeng Wang and Chufan Gao and Cao Xiao and Jimeng Sun
MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Tabular data prediction has been employed in medical applications such as patient health risk prediction. However, existing methods usually revolve around the algorithm design while overlooking the significance of data engineering. Medical tabular datasets frequently exhibit significant heterogeneity across different...
[ { "version": "v1", "created": "Sat, 20 May 2023 03:37:09 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 05:40:00 GMT" } ]
2023-10-06T00:00:00
[ [ "Wang", "Zifeng", "" ], [ "Gao", "Chufan", "" ], [ "Xiao", "Cao", "" ], [ "Sun", "Jimeng", "" ] ]
not_new_dataset
0.99709
2305.12766
Chi Han
Chi Han, Ziqi Wang, Han Zhao, Heng Ji
Explaining Emergent In-Context Learning as Kernel Regression
9 pages, 4 figures
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Large language models (LLMs) have initiated a paradigm shift in transfer learning. In contrast to the classic pretraining-then-finetuning procedure, in order to use LLMs for downstream prediction tasks, one only needs to provide a few demonstrations, known as in-context examples, without adding more or updating exist...
[ { "version": "v1", "created": "Mon, 22 May 2023 06:45:02 GMT" }, { "version": "v2", "created": "Thu, 5 Oct 2023 16:04:43 GMT" } ]
2023-10-06T00:00:00
[ [ "Han", "Chi", "" ], [ "Wang", "Ziqi", "" ], [ "Zhao", "Han", "" ], [ "Ji", "Heng", "" ] ]
not_new_dataset
0.99746
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