Machine Learning

Papers filed under cs.LG on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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17,521 to 17,580 of 20,193

EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
Yuxin Fang, Wen Wang, Binhui Xie +6
cs.CVcs.CLcs.LGarXiv:2211.07636v22022
Spark: Strategic Policy-Aware Exploration via Dynamic Branching for Long-Horizon Agentic Learning
Jinyang Wu, Shuo Yang, Changpeng Yang +4
cs.LGcs.CLarXiv:2601.20209v22026
Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection
Yisroel Mirsky, Tomer Doitshman, Yuval Elovici +1
cs.CRcs.AIcs.LGarXiv:1802.09089v22018
Scaling Embeddings Outperforms Scaling Experts in Language Models
Hong Liu, Jiaqi Zhang, Chao Wang +13
cs.CLcs.AIcs.LGarXiv:2601.21204v22026
Agentic Very Long Video Understanding
Aniket Rege, Arka Sadhu, Yuliang Li +5
cs.CVcs.LGarXiv:2601.18157v32026
MASS: Masked Sequence to Sequence Pre-training for Language Generation
Kaitao Song, Xu Tan, Tao Qin +2
cs.CLcs.AIcs.LGarXiv:1905.02450v52019
Multiagent Cooperation and Competition with Deep Reinforcement Learning
Ardi Tampuu, Tambet Matiisen, Dorian Kodelja +5
cs.AIcs.LGq-bio.NCarXiv:1511.08779v12015
SERA: Soft-Verified Efficient Repository Agents
Ethan Shen, Daniel Tormoen, Saurabh Shah +2
cs.CLcs.LGcs.SEarXiv:2601.20789v32026
PACEvolve: Enabling Long-Horizon Progress-Aware Consistent Evolution
Minghao Yan, Bo Peng, Benjamin Coleman +13
cs.NEcs.LGarXiv:2601.10657v22026
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values
Kjersti Aas, Martin Jullum, Anders Løland
stat.MLcs.LGstat.MEarXiv:1903.10464v32019
Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning
Lukas Brunke, Melissa Greeff, Adam W. Hall +4
cs.ROcs.LGeess.SYarXiv:2108.06266v22021
Robust Aggregation for Federated Learning
Krishna Pillutla, Sham M. Kakade, Zaid Harchaoui
stat.MLcs.CRcs.LGarXiv:1912.13445v22019
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation
Nima Tajbakhsh, Laura Jeyaseelan, Qian Li +3
eess.IVcs.CVcs.LGarXiv:1908.10454v22019
Noisy Networks for Exploration
Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot +9
cs.LGstat.MLarXiv:1706.10295v32017
Inductive Representation Learning on Temporal Graphs
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
cs.LGstat.MLarXiv:2002.07962v12020
Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram
Ryuichi Yamamoto, Eunwoo Song, Jae-Min Kim
eess.AScs.LGcs.SDarXiv:1910.11480v22019
Gibson Env: Real-World Perception for Embodied Agents
Fei Xia, Amir Zamir, Zhi-Yang He +3
cs.AIcs.CVcs.GRarXiv:1808.10654v12018
SLA2: Sparse-Linear Attention with Learnable Routing and QAT
Jintao Zhang, Haoxu Wang, Kai Jiang +6
cs.LGcs.AIcs.CVarXiv:2602.12675v12026
SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
Jintao Zhang, Kai Jiang, Chendong Xiang +5
cs.CVcs.LGarXiv:2602.13515v12026
Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems
Wang Ling, Dani Yogatama, Chris Dyer +1
cs.AIcs.CLcs.LGarXiv:1705.04146v32017
Benchmarking Reward Hack Detection in Code Environments via Contrastive Analysis
Darshan Deshpande, Anand Kannappan, Rebecca Qian
cs.SEcs.AIcs.LGarXiv:2601.20103v12026
TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models
Fangxu Yu, Xingang Guo, Lingzhi Yuan +6
cs.AIcs.LGarXiv:2601.18744v22026
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
Jiaxuan You, Rex Ying, Xiang Ren +2
cs.LGcs.AIcs.SIarXiv:1802.08773v32018
On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon, Eran Yahav
cs.LGstat.MLarXiv:2006.05205v42020
Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization
Haocheng Xi, Shuo Yang, Yilong Zhao +13
cs.LGarXiv:2602.02958v52026
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data
Nick Erickson, Jonas Mueller, Alexander Shirkov +4
stat.MLcs.LGarXiv:2003.06505v12020
Domain Adaptation for Medical Image Analysis: A Survey
Hao Guan, Mingxia Liu
cs.CVcs.LGeess.IVarXiv:2102.09508v12021
The PokeAgent Challenge: Competitive and Long-Context Learning at Scale
Seth Karten, Jake Grigsby, Tersoo Upaa +28
cs.LGcs.AIarXiv:2603.15563v22026
InfoNCE Induces Gaussian Distribution
Roy Betser, Eyal Gofer, Meir Yossef Levi +1
cs.LGeess.SParXiv:2602.24012v22026
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes +3
cs.LGstat.MLarXiv:1812.05159v32018
Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning
Bin Li, Yin Li, Kevin W. Eliceiri
cs.CVcs.LGarXiv:2011.08939v32020
On the Direction of RLVR Updates for LLM Reasoning: Identification and Exploitation
Kexin Huang, Haoming Meng, Junkang Wu +10
cs.LGcs.AIarXiv:2603.22117v12026
Safe Model-based Reinforcement Learning with Stability Guarantees
Felix Berkenkamp, Matteo Turchetta, Angela P. Schoellig +1
stat.MLcs.AIcs.LGarXiv:1705.08551v32017
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
Matthew D. Zeiler, Rob Fergus
cs.LGcs.NEstat.MLarXiv:1301.3557v12013
Spherical CNNs
Taco S. Cohen, Mario Geiger, Jonas Koehler +1
cs.LGstat.MLarXiv:1801.10130v32018
Toward Controlled Generation of Text
Zhiting Hu, Zichao Yang, Xiaodan Liang +2
cs.LGcs.AIcs.CLarXiv:1703.00955v42017
Distributional Reinforcement Learning with Quantile Regression
Will Dabney, Mark Rowland, Marc G. Bellemare +1
cs.AIcs.LGstat.MLarXiv:1710.10044v12017
Confident Learning: Estimating Uncertainty in Dataset Labels
Curtis G. Northcutt, Lu Jiang, Isaac L. Chuang
stat.MLcs.LGarXiv:1911.00068v62019
Towards a Human-like Open-Domain Chatbot
Daniel Adiwardana, Minh-Thang Luong, David R. So +8
cs.CLcs.LGcs.NEarXiv:2001.09977v32020
PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning
Jingcheng Hu, Yinmin Zhang, Shijie Shang +17
cs.LGarXiv:2601.05593v12026
AgenticPay: A Multi-Agent LLM Negotiation System for Buyer-Seller Transactions
Xianyang Liu, Shangding Gu, Dawn Song
cs.AIcs.LGarXiv:2602.06008v12026
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
Fan-Yun Sun, Jordan Hoffmann, Vikas Verma +1
cs.LGcs.AIstat.MLarXiv:1908.01000v32019
On Lazy Training in Differentiable Programming
Lenaic Chizat, Edouard Oyallon, Francis Bach
math.OCcs.LGarXiv:1812.07956v52018
Long-tail learning via logit adjustment
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat +3
cs.LGstat.MLarXiv:2007.07314v22020
An Algorithmic Perspective on Imitation Learning
Takayuki Osa, Joni Pajarinen, Gerhard Neumann +3
cs.ROcs.LGarXiv:1811.06711v12018
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Zhuangdi Zhu, Junyuan Hong, Jiayu Zhou
cs.LGcs.DCarXiv:2105.10056v22021
fastai: A Layered API for Deep Learning
Jeremy Howard, Sylvain Gugger
cs.LGcs.CVcs.NEarXiv:2002.04688v22020
On Detecting Adversarial Perturbations
Jan Hendrik Metzen, Tim Genewein, Volker Fischer +1
stat.MLcs.AIcs.CVarXiv:1702.04267v22017
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy +2
cs.LGstat.MLarXiv:1906.03671v22019
Tool-R0: Self-Evolving LLM Agents for Tool-Learning from Zero Data
Emre Can Acikgoz, Cheng Qian, Jonas Hübotter +3
cs.LGarXiv:2602.21320v12026
MONAI: An open-source framework for deep learning in healthcare
M. Jorge Cardoso, Wenqi Li, Richard Brown +54
cs.LGcs.AIcs.CVarXiv:2211.02701v12022
Hybrid Linear Attention Done Right: Efficient Distillation and Effective Architectures for Extremely Long Contexts
Yingfa Chen, Zhen Leng Thai, Zihan Zhou +6
cs.CLcs.AIcs.LGarXiv:2601.22156v12026
On Evaluation of Embodied Navigation Agents
Peter Anderson, Angel Chang, Devendra Singh Chaplot +8
cs.AIcs.CVcs.LGarXiv:1807.06757v12018
Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning
Shaotian Yan, Kaiyuan Liu, Chen Shen +6
cs.LGcs.CLarXiv:2601.09088v12026
Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models
Yu Zeng, Wenxuan Huang, Zhen Fang +14
cs.CVcs.AIcs.CLarXiv:2602.02185v22026
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
Tim Salimans, Andrej Karpathy, Xi Chen +1
cs.LGstat.MLarXiv:1701.05517v12017
Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning
Nikita Rudin, David Hoeller, Philipp Reist +1
cs.ROcs.LGarXiv:2109.11978v32021
Implicit Geometric Regularization for Learning Shapes
Amos Gropp, Lior Yariv, Niv Haim +2
cs.LGcs.CVcs.GRarXiv:2002.10099v22020
Deep Learning Scaling is Predictable, Empirically
Joel Hestness, Sharan Narang, Newsha Ardalani +6
cs.LGstat.MLarXiv:1712.00409v12017
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You, Bowen Liu, Rex Ying +2
cs.LGcs.AIstat.MLarXiv:1806.02473v32018

Machine Learning

EVA: Exploring the Limits of Masked Visual Representation Learning at Scale

Spark: Strategic Policy-Aware Exploration via Dynamic Branching for Long-Horizon Agentic Learning

Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection

Scaling Embeddings Outperforms Scaling Experts in Language Models

Agentic Very Long Video Understanding

MASS: Masked Sequence to Sequence Pre-training for Language Generation

Multiagent Cooperation and Competition with Deep Reinforcement Learning

SERA: Soft-Verified Efficient Repository Agents

PACEvolve: Enabling Long-Horizon Progress-Aware Consistent Evolution

Explaining individual predictions when features are dependent: More accurate approximations to Shapley values

Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning

Robust Aggregation for Federated Learning

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation

Noisy Networks for Exploration

Inductive Representation Learning on Temporal Graphs

Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram

Gibson Env: Real-World Perception for Embodied Agents

SLA2: Sparse-Linear Attention with Learnable Routing and QAT

SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning

Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems

Benchmarking Reward Hack Detection in Code Environments via Contrastive Analysis

TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

On the Bottleneck of Graph Neural Networks and its Practical Implications

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization

AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Domain Adaptation for Medical Image Analysis: A Survey

The PokeAgent Challenge: Competitive and Long-Context Learning at Scale

InfoNCE Induces Gaussian Distribution

An Empirical Study of Example Forgetting during Deep Neural Network Learning

Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning

On the Direction of RLVR Updates for LLM Reasoning: Identification and Exploitation

Safe Model-based Reinforcement Learning with Stability Guarantees

Stochastic Pooling for Regularization of Deep Convolutional Neural Networks

Spherical CNNs

Toward Controlled Generation of Text

Distributional Reinforcement Learning with Quantile Regression

Confident Learning: Estimating Uncertainty in Dataset Labels

Towards a Human-like Open-Domain Chatbot

PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning

AgenticPay: A Multi-Agent LLM Negotiation System for Buyer-Seller Transactions

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization

On Lazy Training in Differentiable Programming

Long-tail learning via logit adjustment

An Algorithmic Perspective on Imitation Learning

Data-Free Knowledge Distillation for Heterogeneous Federated Learning

fastai: A Layered API for Deep Learning

On Detecting Adversarial Perturbations

Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Tool-R0: Self-Evolving LLM Agents for Tool-Learning from Zero Data

MONAI: An open-source framework for deep learning in healthcare

Hybrid Linear Attention Done Right: Efficient Distillation and Effective Architectures for Extremely Long Contexts

On Evaluation of Embodied Navigation Agents

Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning

Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models

PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications

Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Implicit Geometric Regularization for Learning Shapes

Deep Learning Scaling is Predictable, Empirically

Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation