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.

Search paper metadata (including unsummarized papers)

24,421 to 24,480 of 33,218

Bellman-consistent Pessimism for Offline Reinforcement Learning
Tengyang Xie, Ching-An Cheng, Nan Jiang +2
cs.LGcs.AIstat.MLarXiv:2106.06926v62021
DaCe-DT: Data-Centric Offline Multi-Task Reinforcement Learning via Adaptive Prompts and Trajectory Correction for Heterogeneous Tasks
Xinfei Wang, Shanchen Pang, Chenhao Zhang +5
cs.LGarXiv:2610.11085v12026
Constrained Policy Optimization
Joshua Achiam, David Held, Aviv Tamar +1
cs.LGarXiv:1705.10528v12017
The jamming transition as a paradigm to understand the loss landscape of deep neural networks
Mario Geiger, Stefano Spigler, Stéphane d'Ascoli +4
cond-mat.dis-nncs.LGarXiv:1809.09349v42018
Optimally Pacing Budget Spending and Learning
Mark Braverman, Jingyi Liu, Jieming Mao +2
cs.LGcs.GTarXiv:2610.11074v12026
Multiple Instance Learning with Bag Dissimilarities
Veronika Cheplygina, David M. J. Tax, Marco Loog
stat.MLcs.LGarXiv:1309.5643v32013
Survey on the attention based RNN model and its applications in computer vision
Feng Wang, David M. J. Tax
cs.CVcs.LGarXiv:1601.06823v12016
ADDA: a Modular Framework for Representing, Simulating and Assimilating Dynamics with End-to-end Differentiability
Anthony Frion, Vien Minh Nguyen-Thanh, Ali Can Bekar +3
cs.MScs.LGarXiv:2608.23297v12026
Adversarial Regularizers in Inverse Problems
Sebastian Lunz, Ozan Öktem, Carola-Bibiane Schönlieb
cs.CVcs.LGmath.NAarXiv:1805.11572v22018
Generative Multi-Adversarial Networks
Ishan Durugkar, Ian Gemp, Sridhar Mahadevan
cs.LGcs.MAcs.NEarXiv:1611.01673v32016
Fast Calculation of Probabilistic Power Flow: A Model-based Deep Learning Approach
Yan Yang, Zhifang Yang, Juan Yu +1
eess.SPcs.LGcs.SYarXiv:1906.06017v22019
Latent mixed-effect models for high-dimensional longitudinal data
Priscilla Ong, Manuel Haußmann, Otto Lönnroth +1
cs.LGstat.APstat.MLarXiv:2409.11008v12024
Recovering Irreducible Three-Body Interactions with Lagrangian Neural Networks
Sena Kalabalik, Sukru Caglar, Abdullah Umut Hamzaogullari +1
cs.LGphysics.atom-phphysics.comp-pharXiv:2610.13292v12026
Improving Generalization via Scalable Neighborhood Component Analysis
Zhirong Wu, Alexei A. Efros, Stella X. Yu
cs.CVcs.LGarXiv:1808.04699v12018
DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback
Yangyi Chen, Karan Sikka, Michael Cogswell +2
cs.CVcs.CLcs.LGarXiv:2311.10081v22023
Learning What to Trust in Multimodal Learning under Noisy Supervision
Jiashuo Zou, Xiaobo Xia
cs.CVcs.LGarXiv:2610.11057v12026
Scaling Instruction-Finetuned Language Models
Hyung Won Chung, Le Hou, Shayne Longpre +32
cs.LGcs.CLarXiv:2210.11416v52022
Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
Morteza Mardani, Enhao Gong, Joseph Y. Cheng +8
cs.CVcs.LGstat.MLarXiv:1706.00051v12017
Conditional molecular design with deep generative models
Seokho Kang, Kyunghyun Cho
cs.LGstat.MLarXiv:1805.00108v32018
Front-Loading Reasoning: The Synergy between Pretraining and Post-Training Data
Syeda Nahida Akter, Shrimai Prabhumoye, Eric Nyberg +4
cs.LGcs.AIarXiv:2510.03264v12025
Deep Learning in Photoacoustic Tomography: Current approaches and future directions
Andreas Hauptmann, Ben Cox
eess.IVcs.CVcs.LGarXiv:2009.07608v12020
Cross-Benchmark Transfer from RL on Agentic Coding Tasks
Sushant Mehta, Logan Ritchie, Edwin Chen
cs.LGcs.AIcs.SEarXiv:2610.00890v12026
Random sampling of bandlimited signals on graphs
Gilles Puy, Nicolas Tremblay, Rémi Gribonval +1
cs.SIcs.LGstat.MLarXiv:1511.05118v22015
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
Peixiang Zhong, Di Wang, Chunyan Miao
cs.CVcs.AIcs.HCarXiv:1907.07835v42019
Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning
Neil R. Bramley, Peter Dayan, Thomas L. Griffiths +1
cs.LGarXiv:1609.04212v32016
Support Topology and Gradient Mixing in Sinkhorn Layers
Dylan Forde
cs.AIcs.LGarXiv:2609.07954v12026
Cache-to-Cache: Direct Semantic Communication Between Large Language Models
Tianyu Fu, Zihan Min, Hanling Zhang +4
cs.CLcs.LGarXiv:2510.03215v22025
A Quantum Variational Approach to Prototypical Recurrent Unit
Mahyar Sadeghi Garjan, Tommaso Cesari, Michel Barbeau
cs.LGarXiv:2609.04354v12026
FedAlphaEdit: Null-Space-Aligned Merging for Collaborative Knowledge Editing
Sota Sugawara, Yukihiko Okada
cs.CLcs.LGarXiv:2610.11033v12026
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee +2
cs.LGcs.AIarXiv:2106.10783v12021
LastOPD: Taming Collapse in Latent On-Policy Distillation
Jie Yang, Zhengyu Fang, Zelin Xu +7
cs.LGcs.CLarXiv:2609.28845v12026
Adaptive Attention Span in Transformers
Sainbayar Sukhbaatar, Edouard Grave, Piotr Bojanowski +1
cs.LGstat.MLarXiv:1905.07799v22019
Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram
Yeongyeon Na, Minje Park, Yunwon Tae +1
eess.SPcs.AIcs.LGarXiv:2402.09450v32024
On-Device Language Models for Privacy-Preserving Stress Prediction: A Multimodal Evaluation on Mobile Health
Ibukunoluwa Soyebo, Alyssa Donawa, Rodrigo Aguilar Barrios +2
cs.LGcs.HCarXiv:2609.11961v12026
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
Rafael Rafailov, Yaswanth Chittepu, Ryan Park +5
cs.LGcs.AIcs.CLarXiv:2406.02900v22024
Curating Always-Loaded Context for LLM Agents: A Capacitated Assortment Model with Censored Feedback
Zexuan Liu, Yuning Yang, Tiancheng Zhao
cs.AIcs.LGmath.OCarXiv:2610.11007v12026
Cycle-Aware Autoencoder with Cross-SignalConsistency for Railway Door Anomaly Detection
Ammar Bouketta, Smail Niar, Hamza Ouarnoughi +1
cs.LGcs.AIarXiv:2609.39035v12026
Quantum-enhanced machine learning
Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel
quant-phcs.AIcs.LGarXiv:1610.08251v12016
Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models
Lin Zheng, Vasilisa Bashlovkina, Timothy Dozat +3
cs.CLcs.LGarXiv:2605.09630v12026
Charting the Right Manifold: Manifold Mixup for Few-shot Learning
Puneet Mangla, Mayank Singh, Abhishek Sinha +3
cs.LGcs.CVstat.MLarXiv:1907.12087v42019
Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
Tianbao Xie, Siheng Zhao, Chen Henry Wu +5
cs.LGcs.AIcs.CLarXiv:2309.11489v32023
Synchronous Multi-view Neural Diffusion
Yongquan Shi, Weijun Huang, Yueyang Pi +3
cs.LGarXiv:2609.39019v12026
Heterogeneous Scientific Foundation Model Collaboration
Zihao Li, Jiaru Zou, Feihao Fang +6
cs.AIcs.CLcs.LGarXiv:2604.27351v12026
Keyformer: KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference
Muhammad Adnan, Akhil Arunkumar, Gaurav Jain +3
cs.LGcs.AIcs.ARarXiv:2403.09054v22024
Multi-Bandwidth Distribution Matching Distillation: On the Equivalence of Distribution Matching Distillation and Drifting Models
Jialin Zhu, Xing Liu, Feixiang He +1
cs.LGcs.CVarXiv:2610.10989v12026
TACIT-Switch: Cost-Aware Model Escalation for LLM Agents from Censored Supervision
Ji'an Lei, Jian Huang
cs.LGarXiv:2608.27911v12026
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation
Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda +1
cs.LGcs.CVstat.MLarXiv:2005.01807v12020
Deep Generative Models for Distribution-Preserving Lossy Compression
Michael Tschannen, Eirikur Agustsson, Mario Lucic
cs.LGstat.MLarXiv:1805.11057v22018
Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Survey
Mohamad A. Hady, Siyi Hu, Mahardhika Pratama +2
cs.MAcs.AIcs.LGarXiv:2504.21048v12025
Robust Reinforcement Learning for Continuous Control with Model Misspecification
Daniel J. Mankowitz, Nir Levine, Rae Jeong +7
cs.LGcs.AIstat.MLarXiv:1906.07516v22019
Adam Can Converge Without Any Modification On Update Rules
Yushun Zhang, Congliang Chen, Naichen Shi +2
cs.LGmath.OCarXiv:2208.09632v52022
Flow Matching for Scalable Simulation-Based Inference
Maximilian Dax, Jonas Wildberger, Simon Buchholz +3
cs.LGarXiv:2305.17161v22023
KGATE : a Knowledge Graph Embedding Training Environment
Benjamin Loire, Galadriel Brière, Célia Brahimi +2
cs.LGcs.AIarXiv:2610.09927v12026
Gradient-Update Mismatch: Rethinking Conflict-Free Training of Physics-Informed Neural Networks
Jing Xiao, Xinhai Chen, Qinglin Wang +5
cs.LGarXiv:2609.01558v12026
Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey
Zhichen Dong, Zhanhui Zhou, Chao Yang +2
cs.CLcs.AIcs.CYarXiv:2402.09283v32024
ASPIRE: Saddle-Point Discovery through Set Prediction and Physical Refinement
Yucheng Zhao, Quanyou Zhang, Shaoxiang Qin +2
cs.LGarXiv:2610.10969v12026
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
DeepSeek-AI, :, Xiao Bi +85
cs.CLcs.AIcs.LGarXiv:2401.02954v12024
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cisse, Piotr Bojanowski, Edouard Grave +2
stat.MLcs.AIcs.CRarXiv:1704.08847v22017
Online Estimation of Dynamic Origin-Destination Matrices Using Reinforcement Learning with Link-Flow Propagation Guidance
Donggyu Min, Dong-Kyu Kim
cs.LGcs.AIarXiv:2608.30317v12026
Federated Optimization: Distributed Machine Learning for On-Device Intelligence
Jakub Konečný, H. Brendan McMahan, Daniel Ramage +1
cs.LGarXiv:1610.02527v12016

Machine Learning

Bellman-consistent Pessimism for Offline Reinforcement Learning

DaCe-DT: Data-Centric Offline Multi-Task Reinforcement Learning via Adaptive Prompts and Trajectory Correction for Heterogeneous Tasks

Constrained Policy Optimization

The jamming transition as a paradigm to understand the loss landscape of deep neural networks

Optimally Pacing Budget Spending and Learning

Multiple Instance Learning with Bag Dissimilarities

Survey on the attention based RNN model and its applications in computer vision

ADDA: a Modular Framework for Representing, Simulating and Assimilating Dynamics with End-to-end Differentiability

Adversarial Regularizers in Inverse Problems

Generative Multi-Adversarial Networks

Fast Calculation of Probabilistic Power Flow: A Model-based Deep Learning Approach

Latent mixed-effect models for high-dimensional longitudinal data

Recovering Irreducible Three-Body Interactions with Lagrangian Neural Networks

Improving Generalization via Scalable Neighborhood Component Analysis

DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback

Learning What to Trust in Multimodal Learning under Noisy Supervision

Scaling Instruction-Finetuned Language Models

Deep Generative Adversarial Networks for Compressed Sensing Automates MRI

Conditional molecular design with deep generative models

Front-Loading Reasoning: The Synergy between Pretraining and Post-Training Data

Deep Learning in Photoacoustic Tomography: Current approaches and future directions

Cross-Benchmark Transfer from RL on Agentic Coding Tasks

Random sampling of bandlimited signals on graphs

EEG-Based Emotion Recognition Using Regularized Graph Neural Networks

Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning

Support Topology and Gradient Mixing in Sinkhorn Layers

Cache-to-Cache: Direct Semantic Communication Between Large Language Models

A Quantum Variational Approach to Prototypical Recurrent Unit

FedAlphaEdit: Null-Space-Aligned Merging for Collaborative Knowledge Editing

OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation

LastOPD: Taming Collapse in Latent On-Policy Distillation

Adaptive Attention Span in Transformers

Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram

On-Device Language Models for Privacy-Preserving Stress Prediction: A Multimodal Evaluation on Mobile Health

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Curating Always-Loaded Context for LLM Agents: A Capacitated Assortment Model with Censored Feedback

Cycle-Aware Autoencoder with Cross-SignalConsistency for Railway Door Anomaly Detection

Quantum-enhanced machine learning

Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models

Charting the Right Manifold: Manifold Mixup for Few-shot Learning

Text2Reward: Reward Shaping with Language Models for Reinforcement Learning

Synchronous Multi-view Neural Diffusion

Heterogeneous Scientific Foundation Model Collaboration

Keyformer: KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference

Multi-Bandwidth Distribution Matching Distillation: On the Equivalence of Distribution Matching Distillation and Drifting Models

TACIT-Switch: Cost-Aware Model Escalation for LLM Agents from Censored Supervision

Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation

Deep Generative Models for Distribution-Preserving Lossy Compression

Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Survey

Robust Reinforcement Learning for Continuous Control with Model Misspecification

Adam Can Converge Without Any Modification On Update Rules

Flow Matching for Scalable Simulation-Based Inference

KGATE : a Knowledge Graph Embedding Training Environment

Gradient-Update Mismatch: Rethinking Conflict-Free Training of Physics-Informed Neural Networks

Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey

ASPIRE: Saddle-Point Discovery through Set Prediction and Physical Refinement

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Parseval Networks: Improving Robustness to Adversarial Examples

Online Estimation of Dynamic Origin-Destination Matrices Using Reinforcement Learning with Link-Flow Propagation Guidance

Federated Optimization: Distributed Machine Learning for On-Device Intelligence