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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4,981 to 5,040 of 19,960

Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization
Hoi-To Wai, Zhuoran Yang, Zhaoran Wang +1
cs.LGmath.OCstat.MLarXiv:1806.00877v42018
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs
Saro Passaro, C. Lawrence Zitnick
cs.LGphysics.chem-phphysics.comp-pharXiv:2302.03655v22023
Hardness-Aware Deep Metric Learning
Wenzhao Zheng, Zhaodong Chen, Jiwen Lu +1
cs.CVcs.LGarXiv:1903.05503v22019
Single Model Deep Learning on Imbalanced Small Datasets for Skin Lesion Classification
Peng Yao, Shuwei Shen, Mengjuan Xu +6
cs.CVcs.LGarXiv:2102.01284v22021
Large Language Models to Enhance Bayesian Optimization
Tennison Liu, Nicolás Astorga, Nabeel Seedat +1
cs.LGcs.AIarXiv:2402.03921v22024
UserBench: An Interactive Gym Environment for User-Centric Agents
Cheng Qian, Zuxin Liu, Akshara Prabhakar +9
cs.AIcs.CLcs.LGarXiv:2507.22034v12025
Categorical Flow Maps
Daan Roos, Oscar Davis, Floor Eijkelboom +5
cs.LGarXiv:2602.12233v12026
PruneShift: A Framework for Evaluating Decision Reliability in Structured Pruning
Hao Ye, Gaopeng Zhang
cs.LGcs.NEarXiv:2608.29765v12026
Natural Compression for Distributed Deep Learning
Samuel Horvath, Chen-Yu Ho, Ludovit Horvath +3
cs.LGmath.OCstat.MLarXiv:1905.10988v32019
Unsupervised Learning by Competing Hidden Units
Dmitry Krotov, John Hopfield
cs.LGcs.CVcs.NEarXiv:1806.10181v22018
Purified OPSD: On-Policy Self-Distillation Without Losing How to Think
Zhanming Shen, Jintao Tong, Shaotian Yan +9
cs.AIcs.LGarXiv:2607.02234v12026
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads
Jialin Ding, Vikram Nathan, Mohammad Alizadeh +1
cs.DBcs.LGarXiv:2006.13282v12020
Are Reasoning Models More Prone to Hallucination?
Zijun Yao, Yantao Liu, Yanxu Chen +5
cs.CLcs.LGarXiv:2505.23646v12025
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks
Andy Zhou, Bo Li, Haohan Wang
cs.LGcs.AIcs.CLarXiv:2401.17263v52024
Generative Pre-Training for Speech with Autoregressive Predictive Coding
Yu-An Chung, James Glass
eess.AScs.CLcs.LGarXiv:1910.12607v22019
Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens
Chengshuai Zhao, Zhen Tan, Pingchuan Ma +5
cs.AIcs.CLcs.LGarXiv:2508.01191v62025
LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface
Yi Ding, Neethu Robinson, Chengxuan Tong +2
cs.NEcs.LGeess.SParXiv:2105.02786v32021
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning
Chi Zhang, Yujun Cai, Guosheng Lin +1
cs.CVcs.LGeess.IVarXiv:2003.06777v52020
Steering Large Language Model Activations in Sparse Spaces
Reza Bayat, Ali Rahimi-Kalahroudi, Mohammad Pezeshki +2
cs.LGcs.AIarXiv:2503.00177v12025
BEACON: Behavioral and Semantic Enrichment of AlphaEarth Embeddings through Tri-Modal Contrastive Learning
Hao Tian, Heng Cai, Yifan Yang
cs.LGarXiv:2608.29553v12026
Contrastive Code Representation Learning
Paras Jain, Ajay Jain, Tianjun Zhang +3
cs.LGcs.AIcs.PLarXiv:2007.04973v42020
The HSIC Bottleneck: Deep Learning without Back-Propagation
Wan-Duo Kurt Ma, J. P. Lewis, W. Bastiaan Kleijn
cs.LGstat.MLarXiv:1908.01580v32019
SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution
Hanlin Wang, Chak Tou Leong, Jiashuo Wang +2
cs.CLcs.LGarXiv:2505.20732v12025
Robustness of Graph Neural Networks at Scale
Simon Geisler, Tobias Schmidt, Hakan Şirin +3
cs.LGstat.MLarXiv:2110.14038v42021
Steer LLM Latents for Hallucination Detection
Seongheon Park, Xuefeng Du, Min-Hsuan Yeh +2
cs.LGcs.AIcs.CLarXiv:2503.01917v22025
A Note on Shumailov et al. (2024): `AI Models Collapse When Trained on Recursively Generated Data'
Ali Borji
cs.LGcs.AIarXiv:2410.12954v22024
Decoupling the Depth and Scope of Graph Neural Networks
Hanqing Zeng, Muhan Zhang, Yinglong Xia +6
cs.LGcs.AIarXiv:2201.07858v12022
Fast Training of Diffusion Models with Masked Transformers
Hongkai Zheng, Weili Nie, Arash Vahdat +1
cs.CVcs.AIcs.LGarXiv:2306.09305v22023
Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use
Kunvar Thaman
cs.LGcs.AIarXiv:2605.02964v12026
Learning Domain-Invariant Subspace using Domain Features and Independence Maximization
Ke Yan, Lu Kou, David Zhang
cs.CVcs.AIcs.LGarXiv:1603.04535v22016
GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras
Ye Yuan, Umar Iqbal, Pavlo Molchanov +2
cs.CVcs.AIcs.GRarXiv:2112.01524v22021
Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs
Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov
cs.LGcs.AIcs.ROarXiv:2110.05038v32021
The Leaderboard Illusion
Shivalika Singh, Yiyang Nan, Alex Wang +10
cs.AIcs.CLcs.LGarXiv:2504.20879v22025
Keyword Transformer: A Self-Attention Model for Keyword Spotting
Axel Berg, Mark O'Connor, Miguel Tairum Cruz
eess.AScs.CLcs.LGarXiv:2104.00769v32021
Neural Graph Matching Network: Learning Lawler's Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching
Runzhong Wang, Junchi Yan, Xiaokang Yang
cs.LGcs.CVstat.MLarXiv:1911.11308v32019
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
Vijay Ekambaram, Arindam Jati, Pankaj Dayama +5
cs.LGcs.AIarXiv:2401.03955v82024
A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization
Kejun Huang, Nicholas D. Sidiropoulos, Athanasios P. Liavas
stat.MLcs.LGmath.OCarXiv:1506.04209v22015
Deep Multimodal Subspace Clustering Networks
Mahdi Abavisani, Vishal M. Patel
cs.LGcs.AIcs.CVarXiv:1804.06498v32018
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data
Tian Guo, Tao Lin, Nino Antulov-Fantulin
cs.LGstat.MLarXiv:1905.12034v12019
A foundation model of vision, audition, and language for in-silico neuroscience
Stéphane d'Ascoli, Jérémy Rapin, Yohann Benchetrit +5
q-bio.NCcs.LGarXiv:2605.04326v12026
MentalChat16K: A Benchmark Dataset for Conversational Mental Health Assistance
Jia Xu, Tianyi Wei, Bojian Hou +7
cs.LGcs.AIcs.CLarXiv:2503.13509v22025
Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs
Kyle O'Brien, Stephen Casper, Quentin Anthony +7
cs.LGcs.AIarXiv:2508.06601v22025
OptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modeling
Hongliang Lu, Zhonglin Xie, Yaoyu Wu +3
cs.AIcs.LGarXiv:2502.11102v22025
D-FROST: Decentralized Federated pRompt-tuning via Optimal tranSporT for Non-IID and Imbalanced Data
Quan Minh Nguyen, Hoang M. Ngo, Trong Nghia Hoang +1
cs.LGarXiv:2609.01802v12026
When Do Larger Batches Help Scale LLM Reinforcement Learning?
Ziniu Li, Jinbo Wang, Guanhua Huang +3
cs.LGcs.AIarXiv:2608.29296v12026
Blink: Fast and Generic Collectives for Distributed ML
Guanhua Wang, Shivaram Venkataraman, Amar Phanishayee +3
cs.DCcs.LGarXiv:1910.04940v12019
It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization
Ali Behrouz, Meisam Razaviyayn, Peilin Zhong +1
cs.LGcs.AIarXiv:2504.13173v12025
The Emergence of Spectral Universality in Deep Networks
Jeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli
stat.MLcs.LGarXiv:1802.09979v12018
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Víctor Campos, Alexander Trott, Caiming Xiong +3
cs.LGcs.AIstat.MLarXiv:2002.03647v42020
Recurrent Pixel Embedding for Instance Grouping
Shu Kong, Charless Fowlkes
cs.CVcs.LGcs.MMarXiv:1712.08273v12017
Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classification
Simon Graham, Mostafa Jahanifar, Ayesha Azam +14
cs.CVcs.LGarXiv:2108.11195v22021
SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM
Xiaojiang Zhang, Jinghui Wang, Zifei Cheng +14
cs.LGarXiv:2504.14286v22025
Unsupervised Detection of Anomalous Sound based on Deep Learning and the Neyman-Pearson Lemma
Yuma Koizumi, Shoichiro Saito, Hisashi Uematsum Yuta Kawachi +1
stat.MLcs.LGcs.SDarXiv:1810.09133v12018
Bonsai -- Diverse and Shallow Trees for Extreme Multi-label Classification
Sujay Khandagale, Han Xiao, Rohit Babbar
cs.LGstat.MLarXiv:1904.08249v22019
Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets
Summaiya Unnisa Begum, Mohammed Nadeem Ullah, Mohammed Abdul Ghani Khan
cs.LGarXiv:2609.01765v12026
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods
Xiangfei Qiu, Zhe Li, Wanghui Qiu +10
cs.LGarXiv:2506.18046v22025
Graphical-model based estimation and inference for differential privacy
Ryan McKenna, Daniel Sheldon, Gerome Miklau
cs.LGcs.CRstat.MLarXiv:1901.09136v12019
Provably Consistent Partial-Label Learning
Lei Feng, Jiaqi Lv, Bo Han +5
cs.LGstat.MLarXiv:2007.08929v22020
Representation Learning for Tabular Data: A Comprehensive Survey
Jun-Peng Jiang, Si-Yang Liu, Hao-Run Cai +2
cs.LGarXiv:2504.16109v12025
Interpretable Symptom Vectors for Depression in a Large Language Model
Fangyi Zhu, Ajay Subramanian, Allison Constant +3
cs.CLcs.AIcs.LGarXiv:2609.01832v12026

Machine Learning

Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization

Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs

Hardness-Aware Deep Metric Learning

Single Model Deep Learning on Imbalanced Small Datasets for Skin Lesion Classification

Large Language Models to Enhance Bayesian Optimization

UserBench: An Interactive Gym Environment for User-Centric Agents

Categorical Flow Maps

PruneShift: A Framework for Evaluating Decision Reliability in Structured Pruning

Natural Compression for Distributed Deep Learning

Unsupervised Learning by Competing Hidden Units

Purified OPSD: On-Policy Self-Distillation Without Losing How to Think

Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads

Are Reasoning Models More Prone to Hallucination?

Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks

Generative Pre-Training for Speech with Autoregressive Predictive Coding

Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens

LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface

DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning

Steering Large Language Model Activations in Sparse Spaces

BEACON: Behavioral and Semantic Enrichment of AlphaEarth Embeddings through Tri-Modal Contrastive Learning

Contrastive Code Representation Learning

The HSIC Bottleneck: Deep Learning without Back-Propagation

SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution

Robustness of Graph Neural Networks at Scale

Steer LLM Latents for Hallucination Detection

A Note on Shumailov et al. (2024): `AI Models Collapse When Trained on Recursively Generated Data'

Decoupling the Depth and Scope of Graph Neural Networks

Fast Training of Diffusion Models with Masked Transformers

Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use

Learning Domain-Invariant Subspace using Domain Features and Independence Maximization

GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras

Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs

The Leaderboard Illusion

Keyword Transformer: A Self-Attention Model for Keyword Spotting

Neural Graph Matching Network: Learning Lawler's Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization

Deep Multimodal Subspace Clustering Networks

Exploring Interpretable LSTM Neural Networks over Multi-Variable Data

A foundation model of vision, audition, and language for in-silico neuroscience

MentalChat16K: A Benchmark Dataset for Conversational Mental Health Assistance

Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs

OptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modeling

D-FROST: Decentralized Federated pRompt-tuning via Optimal tranSporT for Non-IID and Imbalanced Data

When Do Larger Batches Help Scale LLM Reinforcement Learning?

Blink: Fast and Generic Collectives for Distributed ML

It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization

The Emergence of Spectral Universality in Deep Networks

Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills

Recurrent Pixel Embedding for Instance Grouping

Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classification

SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM

Unsupervised Detection of Anomalous Sound based on Deep Learning and the Neyman-Pearson Lemma

Bonsai -- Diverse and Shallow Trees for Extreme Multi-label Classification

Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets

TAB: Unified Benchmarking of Time Series Anomaly Detection Methods

Graphical-model based estimation and inference for differential privacy

Provably Consistent Partial-Label Learning

Representation Learning for Tabular Data: A Comprehensive Survey

Interpretable Symptom Vectors for Depression in a Large Language Model