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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6,421 to 6,480 of 20,199

Repository-Level Prompt Generation for Large Language Models of Code
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
cs.LGcs.AIcs.PLarXiv:2206.12839v32022
InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory
Chaojun Xiao, Pengle Zhang, Xu Han +5
cs.CLcs.AIcs.LGarXiv:2402.04617v22024
Model Organisms for Emergent Misalignment
Edward Turner, Anna Soligo, Mia Taylor +2
cs.LGcs.AIarXiv:2506.11613v12025
SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference
Jintao Zhang, Chendong Xiang, Haofeng Huang +4
cs.LGcs.AIcs.CVarXiv:2502.18137v82025
Learning Action Representations for Reinforcement Learning
Yash Chandak, Georgios Theocharous, James Kostas +2
cs.LGstat.MLarXiv:1902.00183v22019
End-to-End Adversarial Text-to-Speech
Jeff Donahue, Sander Dieleman, Mikołaj Bińkowski +2
cs.SDcs.LGeess.ASarXiv:2006.03575v32020
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination
Nathan Kallus, Xiaojie Mao, Angela Zhou
stat.MLcs.LGmath.OCarXiv:1906.00285v22019
Moirai 2.0: When Less Is More for Time Series Forecasting
Chenghao Liu, Taha Aksu, Juncheng Liu +7
cs.LGarXiv:2511.11698v32025
Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality
Mark Braverman, Ankit Garg, Tengyu Ma +2
cs.LGcs.CCcs.ITarXiv:1506.07216v32015
How Important is Weight Symmetry in Backpropagation?
Qianli Liao, Joel Z. Leibo, Tomaso Poggio
cs.LGarXiv:1510.05067v42015
Personalized Federated Learning with Feature Alignment and Classifier Collaboration
Jian Xu, Xinyi Tong, Shao-Lun Huang
cs.LGcs.DCarXiv:2306.11867v12023
Deep Learning Approach to Diabetic Retinopathy Detection
Borys Tymchenko, Philip Marchenko, Dmitry Spodarets
cs.LGstat.MLarXiv:2003.02261v12020
Jointly Reinforcing Diversity and Quality in Language Model Generations
Tianjian Li, Yiming Zhang, Ping Yu +5
cs.CLcs.LGarXiv:2509.02534v12025
Curriculum Adversarial Training
Qi-Zhi Cai, Min Du, Chang Liu +1
cs.LGcs.CRstat.MLarXiv:1805.04807v12018
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
André Barreto, Diana Borsa, John Quan +6
cs.LGcs.AIarXiv:1901.10964v12019
Probabilistic Logic Neural Networks for Reasoning
Meng Qu, Jian Tang
cs.LGcs.AIstat.MLarXiv:1906.08495v22019
PCGRL: Procedural Content Generation via Reinforcement Learning
Ahmed Khalifa, Philip Bontrager, Sam Earle +1
cs.LGcs.AIstat.MLarXiv:2001.09212v32020
Behind the Curtain: Learning Occluded Shapes for 3D Object Detection
Qiangeng Xu, Yiqi Zhong, Ulrich Neumann
cs.CVcs.AIcs.LGarXiv:2112.02205v12021
AdaWorld: Learning Adaptable World Models with Latent Actions
Shenyuan Gao, Siyuan Zhou, Yilun Du +2
cs.AIcs.CVcs.LGarXiv:2503.18938v42025
All You Need is Beyond a Good Init: Exploring Better Solution for Training Extremely Deep Convolutional Neural Networks with Orthonormality and Modulation
Di Xie, Jiang Xiong, Shiliang Pu
cs.CVcs.LGcs.NEarXiv:1703.01827v32017
No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces
Daniel Marczak, Simone Magistri, Sebastian Cygert +3
cs.LGarXiv:2502.04959v32025
Learning Mixed Graphical Models
Jason D. Lee, Trevor J. Hastie
stat.MLcs.CVcs.LGarXiv:1205.5012v32012
MEM: Multi-Scale Embodied Memory for Vision Language Action Models
Marcel Torne, Karl Pertsch, Homer Walke +14
cs.ROcs.LGarXiv:2603.03596v22026
Regularizing Deep Networks with Semantic Data Augmentation
Yulin Wang, Gao Huang, Shiji Song +3
cs.CVcs.LGarXiv:2007.10538v52020
DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures
Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan +2
cs.CVcs.LGarXiv:1806.08198v22018
Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos
Hao Luo, Yicheng Feng, Wanpeng Zhang +7
cs.CVcs.LGcs.ROarXiv:2507.15597v12025
On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting
Wenhao Zhang, Yuexiang Xie, Yuchang Sun +5
cs.LGcs.AIarXiv:2508.11408v32025
Unifying Vision, Text, and Layout for Universal Document Processing
Zineng Tang, Ziyi Yang, Guoxin Wang +6
cs.CVcs.AIcs.CLarXiv:2212.02623v32022
SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning
Yuqian Fu, Tinghong Chen, Jiajun Chai +7
cs.CLcs.AIcs.LGarXiv:2506.19767v12025
Machine Learning for a Sustainable Energy Future
Zhenpeng Yao, Yanwei Lum, Andrew Johnston +6
cond-mat.mtrl-scics.LGarXiv:2210.10391v12022
Patterning in Practice: Debiasing Reward Models with Susceptibilities
George Wang, Elizabeth Donoway, Daniel Murfet
cs.LGarXiv:2609.00699v12026
COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability
Xingang Guo, Fangxu Yu, Huan Zhang +2
cs.LGcs.AIcs.CLarXiv:2402.08679v22024
CWM: An Open-Weights LLM for Research on Code Generation with World Models
FAIR CodeGen team, Jade Copet, Quentin Carbonneaux +48
cs.SEcs.AIcs.LGarXiv:2510.02387v12025
Combinatorial Sleeping Bandits with Fairness Constraints
Fengjiao Li, Jia Liu, Bo Ji
cs.LGcs.PFstat.MLarXiv:1901.04891v32019
Sub-sampled Cubic Regularization for Non-convex Optimization
Jonas Moritz Kohler, Aurelien Lucchi
cs.LGmath.OCstat.MLarXiv:1705.05933v32017
Can LLMs Discover Scientific Laws in Real and Parallel Worlds?
Yiming Huang, Ziche Liu, Zhuohang Wu +11
cs.AIcs.LGarXiv:2609.01552v12026
A Checklist to assess the energy and carbon impacts of ML/AI applications in Earth System Modeling
Filippo Dainelli, Amirpasha Mozaffari, Marina Castaño +5
physics.ao-phcs.AIcs.LGarXiv:2609.00847v12026
Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory
Mirac Suzgun, Mert Yuksekgonul, Federico Bianchi +2
cs.LGcs.CLarXiv:2504.07952v12025
Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions
Lu Ma, Hao Liang, Meiyi Qiang +9
cs.AIcs.LGarXiv:2506.07527v32025
Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
Shigang Li, Torsten Hoefler
cs.DCcs.LGarXiv:2107.06925v52021
OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling
Zengzhi Wang, Fan Zhou, Xuefeng Li +1
cs.CLcs.AIcs.LGarXiv:2506.20512v12025
Artificial Neural Networks Applied to Taxi Destination Prediction
Alexandre de Brébisson, Étienne Simon, Alex Auvolat +2
cs.LGcs.NEarXiv:1508.00021v22015
Generalization in diffusion models arises from geometry-adaptive harmonic representations
Zahra Kadkhodaie, Florentin Guth, Eero P. Simoncelli +1
cs.CVcs.LGarXiv:2310.02557v32023
Active Learning for Regression Using Greedy Sampling
Dongrui Wu, Chin-Teng Lin, Jian Huang
cs.LGcs.AIstat.MLarXiv:1808.04245v12018
Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
Zhixuan Liang, Yizhuo Li, Tianshuo Yang +9
cs.CVcs.LGcs.ROarXiv:2508.20072v42025
What Can RL Bring to VLA Generalization? An Empirical Study
Jijia Liu, Feng Gao, Bingwen Wei +5
cs.LGarXiv:2505.19789v42025
Better than classical? The subtle art of benchmarking quantum machine learning models
Joseph Bowles, Shahnawaz Ahmed, Maria Schuld
quant-phcs.LGarXiv:2403.07059v22024
A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation
Xinyu Chen, Jinming Yang, Lijun Sun
stat.MLcs.LGarXiv:2003.10271v22020
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Nilesh Tripuraneni, Mitchell Stern, Chi Jin +2
cs.LGmath.OCstat.MLarXiv:1711.02838v22017
Neural Networks can Learn Representations with Gradient Descent
Alex Damian, Jason D. Lee, Mahdi Soltanolkotabi
cs.LGcs.ITstat.MLarXiv:2206.15144v12022
Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directions
Anil Rahate, Rahee Walambe, Sheela Ramanna +1
cs.LGcs.AIarXiv:2107.13782v32021
PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models
Mingyang Song, Zhaochen Su, Xiaoye Qu +2
cs.CLcs.AIcs.LGarXiv:2501.03124v52025
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
Armin Lederer, Jonas Umlauft, Sandra Hirche
cs.LGeess.SYstat.MLarXiv:1906.01376v22019
PHYRE: A New Benchmark for Physical Reasoning
Anton Bakhtin, Laurens van der Maaten, Justin Johnson +2
cs.LGcs.AIstat.MLarXiv:1908.05656v12019
Adaptive Gradient Descent without Descent
Yura Malitsky, Konstantin Mishchenko
math.OCcs.LGmath.NAarXiv:1910.09529v22019
Interactive Post-Training for Vision-Language-Action Models
Shuhan Tan, Kairan Dou, Yue Zhao +1
cs.LGcs.AIcs.CVarXiv:2505.17016v12025
Self-supervised Video Object Segmentation by Motion Grouping
Charig Yang, Hala Lamdouar, Erika Lu +2
cs.CVcs.LGarXiv:2104.07658v22021
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali +50
cond-mat.mtrl-scics.LGphysics.chem-pharXiv:2306.06283v42023
Gated Graph Recurrent Neural Networks
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
eess.SPcs.LGarXiv:2002.01038v22020
A Large Scale Event-based Detection Dataset for Automotive
Pierre de Tournemire, Davide Nitti, Etienne Perot +2
cs.CVcs.LGcs.ROarXiv:2001.08499v32020

Machine Learning

Repository-Level Prompt Generation for Large Language Models of Code

InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory

Model Organisms for Emergent Misalignment

SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference

Learning Action Representations for Reinforcement Learning

End-to-End Adversarial Text-to-Speech

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

Moirai 2.0: When Less Is More for Time Series Forecasting

Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality

How Important is Weight Symmetry in Backpropagation?

Personalized Federated Learning with Feature Alignment and Classifier Collaboration

Deep Learning Approach to Diabetic Retinopathy Detection

Jointly Reinforcing Diversity and Quality in Language Model Generations

Curriculum Adversarial Training

Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement

Probabilistic Logic Neural Networks for Reasoning

PCGRL: Procedural Content Generation via Reinforcement Learning

Behind the Curtain: Learning Occluded Shapes for 3D Object Detection

AdaWorld: Learning Adaptable World Models with Latent Actions

All You Need is Beyond a Good Init: Exploring Better Solution for Training Extremely Deep Convolutional Neural Networks with Orthonormality and Modulation

No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces

Learning Mixed Graphical Models

MEM: Multi-Scale Embodied Memory for Vision Language Action Models

Regularizing Deep Networks with Semantic Data Augmentation

DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures

Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos

On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting

Unifying Vision, Text, and Layout for Universal Document Processing

SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning

Machine Learning for a Sustainable Energy Future

Patterning in Practice: Debiasing Reward Models with Susceptibilities

COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability

CWM: An Open-Weights LLM for Research on Code Generation with World Models

Combinatorial Sleeping Bandits with Fairness Constraints

Sub-sampled Cubic Regularization for Non-convex Optimization

Can LLMs Discover Scientific Laws in Real and Parallel Worlds?

A Checklist to assess the energy and carbon impacts of ML/AI applications in Earth System Modeling

Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory

Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions

Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines

OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling

Artificial Neural Networks Applied to Taxi Destination Prediction

Generalization in diffusion models arises from geometry-adaptive harmonic representations

Active Learning for Regression Using Greedy Sampling

Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies

What Can RL Bring to VLA Generalization? An Empirical Study

Better than classical? The subtle art of benchmarking quantum machine learning models

A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation

Stochastic Cubic Regularization for Fast Nonconvex Optimization

Neural Networks can Learn Representations with Gradient Descent

Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directions

PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control

PHYRE: A New Benchmark for Physical Reasoning

Adaptive Gradient Descent without Descent

Interactive Post-Training for Vision-Language-Action Models

Self-supervised Video Object Segmentation by Motion Grouping

14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon

Gated Graph Recurrent Neural Networks

A Large Scale Event-based Detection Dataset for Automotive