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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28,321 to 28,380 of 33,063

Learning to drive from a world on rails
Dian Chen, Vladlen Koltun, Philipp Krähenbühl
cs.ROcs.CVcs.LGarXiv:2105.00636v32021
Dynamic Pricing with Limited Supply
Moshe Babaioff, Shaddin Dughmi, Robert Kleinberg +1
cs.GTcs.DScs.LGarXiv:1108.4142v32011
InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs
Yujun Shen, Ceyuan Yang, Xiaoou Tang +1
cs.CVcs.LGeess.IVarXiv:2005.09635v22020
Agentic Learner with Grow-and-Refine Multimodal Semantic Memory
Weihao Bo, Shan Zhang, Yanpeng Sun +9
cs.AIcs.LGarXiv:2511.21678v22025
DynSHAP: Towards Explainable Dynamic Survival Analysis
Nastasya Anokhina, Jonas Jürß, Pietro Liò
cs.LGcs.AIarXiv:2609.13042v12026
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy, Matan Haroush, Nadav Merlis +2
cs.LGstat.MLarXiv:1809.02121v32018
Reading the Room: Implicit Confusion Encoding in Recurrent World Model States
Donald Aadithiyan
cs.LGarXiv:2608.21582v12026
Do Deep Generative Models Know What They Don't Know?
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh +2
stat.MLcs.LGarXiv:1810.09136v32018
Convergence of Muon with Newton-Schulz
Gyu Yeol Kim, Min-hwan Oh
stat.MLcs.LGmath.OCarXiv:2601.19156v12026
CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks
Michela Paganini, Luke de Oliveira, Benjamin Nachman
hep-excs.LGhep-pharXiv:1712.10321v12017
Diversity-oriented Data Augmentation with Large Language Models
Zaitian Wang, Jinghan Zhang, Xinhao Zhang +3
cs.CLcs.AIcs.LGarXiv:2502.11671v22025
Rethinking Graph Transformers with Spectral Attention
Devin Kreuzer, Dominique Beaini, William L. Hamilton +2
cs.LGarXiv:2106.03893v32021
Trainability of Dissipative Perceptron-Based Quantum Neural Networks
Kunal Sharma, M. Cerezo, Lukasz Cincio +1
quant-phcs.LGarXiv:2005.12458v22020
The Sharp Tail of Uniform Stability
Pahan Dewasurendra
cs.LGarXiv:2608.24098v12026
How Powerful are K-hop Message Passing Graph Neural Networks
Jiarui Feng, Yixin Chen, Fuhai Li +2
cs.LGcs.AIarXiv:2205.13328v42022
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Corinna Cortes, Xavi Gonzalvo, Vitaly Kuznetsov +2
cs.LGarXiv:1607.01097v32016
Rethinking Psychometric Evaluation of LLMs: When and Why Self-Reports Predict Behavior
Rafal Kocielnik, Pengrui Han, Peiyang Song +5
cs.AIcs.CLcs.CYarXiv:2606.12730v12026
Verifying Individual Fairness in Machine Learning Models
Philips George John, Deepak Vijaykeerthy, Diptikalyan Saha
cs.LGcs.AIstat.MLarXiv:2006.11737v12020
Self-attention summary networks for subsurface velocity-model building from common-image gathers
Shiqin Zeng, Yunlin Zeng, Abhinav Prakash Gahlot +2
cs.LGphysics.geo-pharXiv:2610.09282v12026
SMAT: Simple and Efficient Merge-Aware Training
Yanggan Gu, Yuanyi Wang, Zhen Li +5
cs.LGcs.CLarXiv:2609.33437v12026
Structured Pruning of Large Language Models
Ziheng Wang, Jeremy Wohlwend, Tao Lei
cs.CLcs.LGstat.MLarXiv:1910.04732v22019
Eliciting Latent Predictions from Transformers with the Tuned Lens
Nora Belrose, Igor Ostrovsky, Lev McKinney +5
cs.LGarXiv:2303.08112v62023
Hardware-aware Calibrated Clustered Attention for Efficient Visual Geometric Transformers
Weitian Wang, Shubham Rai, Cecilia De La Parra +1
cs.CVcs.LGarXiv:2610.09274v12026
On the Effectiveness of Least Squares Generative Adversarial Networks
Xudong Mao, Qing Li, Haoran Xie +3
cs.CVcs.LGstat.MLarXiv:1712.06391v22017
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging
Anastasios N Angelopoulos, Amit P Kohli, Stephen Bates +5
cs.LGcs.CVeess.IVarXiv:2202.05265v12022
FedProto: Federated Prototype Learning across Heterogeneous Clients
Yue Tan, Guodong Long, Lu Liu +4
cs.LGcs.DCarXiv:2105.00243v42021
Optimal Low-Rank Quantum State Tomography with Bounded-Sample Joint Measurements
Ashwin Nayak, Xingyu Zhou
quant-phcs.DScs.ITarXiv:2609.10514v12026
Evaluating ChatGPT and GPT-4 for Visual Programming
Adish Singla
cs.LGcs.AIcs.CYarXiv:2308.02522v12023
Personalized Wireless Federated Learning for Large Language Models
Feibo Jiang, Li Dong, Siwei Tu +5
cs.LGcs.AIcs.CLarXiv:2404.13238v22024
What Are Bayesian Neural Network Posteriors Really Like?
Pavel Izmailov, Sharad Vikram, Matthew D. Hoffman +1
cs.LGstat.MLarXiv:2104.14421v12021
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers +21
cs.LGcs.CVarXiv:2210.04620v32022
Federated Learning Meets Multi-objective Optimization
Zeou Hu, Kiarash Shaloudegi, Guojun Zhang +1
cs.LGstat.MLarXiv:2006.11489v22020
Distributed Clustering of Linear Bandits in Peer to Peer Networks
Nathan Korda, Balazs Szorenyi, Shuai Li
cs.LGcs.AIstat.MLarXiv:1604.07706v32016
Knowing When to Ask for Help: Bayesian Self-Escalation in Hierarchical LLM Agents
Nadeem Shaikh
cs.LGcs.AIstat.MLarXiv:2608.24087v12026
Heterogeneous Graph Neural Networks for Malicious Account Detection
Ziqi Liu, Chaochao Chen, Xinxing Yang +3
cs.LGcs.CRstat.MLarXiv:2002.12307v12020
Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives
Zeyuan Allen-Zhu, Yang Yuan
cs.LGcs.DSmath.OCarXiv:1506.01972v32015
What graph neural networks cannot learn: depth vs width
Andreas Loukas
cs.LGstat.MLarXiv:1907.03199v22019
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar, Peyton Greenside, Anshul Kundaje
cs.CVcs.LGcs.NEarXiv:1704.02685v22017
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink
David Patterson, Joseph Gonzalez, Urs Hölzle +7
cs.LGcs.AIcs.GLarXiv:2204.05149v12022
Convergence of Update Aware Device Scheduling for Federated Learning at the Wireless Edge
Mohammad Mohammadi Amiri, Deniz Gunduz, Sanjeev R. Kulkarni +1
cs.ITcs.DCcs.LGarXiv:2001.10402v22020
optimize_anything: A Universal API for Optimizing any Text Parameter
Lakshya A Agrawal, Donghyun Lee, Shangyin Tan +11
cs.CLcs.AIcs.LGarXiv:2605.19633v12026
Position: Fairness Failure in Generative Models is an Evaluation Problem
Mariia Vladimirova, Jean-Yves Franceschi, Thibaut Issenhuth
cs.LGcs.AIarXiv:2608.16974v12026
PowerAttention: Exponentially Scaling of Receptive Fields for Effective Sparse Attention
Lida Chen, Dong Xu, Chenxin An +8
cs.CLcs.LGarXiv:2503.03588v12025
Self-Evaluation as a Defense Against Adversarial Attacks on LLMs
Hannah Brown, Leon Lin, Kenji Kawaguchi +1
cs.LGcs.CLcs.CRarXiv:2407.03234v32024
Cognitive Mapping and Planning for Visual Navigation
Saurabh Gupta, Varun Tolani, James Davidson +3
cs.CVcs.AIcs.LGarXiv:1702.03920v32017
Playing with Duality: An Overview of Recent Primal-Dual Approaches for Solving Large-Scale Optimization Problems
Nikos Komodakis, Jean-Christophe Pesquet
math.NAcs.CVcs.LGarXiv:1406.5429v22014
IdeaLens: Detecting AI Ideas in Long-form Writing
Rishanth Rajendhran, Minjoon Choi, Jenna Russell +5
cs.CLcs.AIcs.LGarXiv:2610.06778v12026
Repeat After Me: Transformers are Better than State Space Models at Copying
Samy Jelassi, David Brandfonbrener, Sham M. Kakade +1
cs.LGcs.AIcs.CLarXiv:2402.01032v22024
Optimizing Visual Generative Models via Distribution-wise Rewards
Ruihang Li, Mengde Xu, Shuyang Gu +4
cs.LGcs.CVarXiv:2607.02291v12026
Wasserstein Auto-Encoders
Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly +1
stat.MLcs.LGarXiv:1711.01558v42017
Label Propagation for Deep Semi-supervised Learning
Ahmet Iscen, Giorgos Tolias, Yannis Avrithis +1
cs.CVcs.LGarXiv:1904.04717v12019
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
Mohammed Ali Al-Garadi, Amr Mohamed, Abdulla Al-Ali +2
cs.CRcs.LGcs.NIarXiv:1807.11023v12018
Open-MOPD: Diagnosing and Fixing Capability Imbalance in Multi-Teacher On-Policy Distillation
Huan-ang Gao, Haohan Chi, Yong Yan +7
cs.LGcs.AIcs.CLarXiv:2608.19098v12026
Compression Trinity: Exploring Sparsity, Quantization, and Low-Rank Approximations for LLM Compression
Mohammad Mozaffari
cs.AIcs.DCcs.LGarXiv:2608.24070v12026
Fast and Effective On-policy Distillation from Reasoning Prefixes
Dongxu Zhang, Zhichao Yang, Sepehr Janghorbani +6
cs.LGcs.AIarXiv:2602.15260v12026
Document-level Relation Extraction as Semantic Segmentation
Ningyu Zhang, Xiang Chen, Xin Xie +6
cs.CLcs.AIcs.CVarXiv:2106.03618v22021
Values as Style: Disentangling Values from Semantics with One-Way Mixing for Low-Damage LLM Steering
Jiale Dai, Hongcan Deng, Liuxian Ma +2
cs.AIcs.CYcs.LGarXiv:2609.39701v12026
BazaarBench: Delegation Safety in Decentralized C2C Marketplaces Run by LLM Agents
Ziyan Wang, Shuqing Shi, James Oldfield +5
cs.MAcs.AIcs.LGarXiv:2610.06748v12026
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Ofir Nachum, Mohammad Norouzi, Kelvin Xu +1
cs.AIcs.LGstat.MLarXiv:1702.08892v32017
Probabilistic Prediction of Vehicle Semantic Intention and Motion
Yeping Hu, Wei Zhan, Masayoshi Tomizuka
cs.LGstat.MLarXiv:1804.03629v12018

Machine Learning

Learning to drive from a world on rails

Dynamic Pricing with Limited Supply

InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs

Agentic Learner with Grow-and-Refine Multimodal Semantic Memory

DynSHAP: Towards Explainable Dynamic Survival Analysis

Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning

Reading the Room: Implicit Confusion Encoding in Recurrent World Model States

Do Deep Generative Models Know What They Don't Know?

Convergence of Muon with Newton-Schulz

CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks

Diversity-oriented Data Augmentation with Large Language Models

Rethinking Graph Transformers with Spectral Attention

Trainability of Dissipative Perceptron-Based Quantum Neural Networks

The Sharp Tail of Uniform Stability

How Powerful are K-hop Message Passing Graph Neural Networks

AdaNet: Adaptive Structural Learning of Artificial Neural Networks

Rethinking Psychometric Evaluation of LLMs: When and Why Self-Reports Predict Behavior

Verifying Individual Fairness in Machine Learning Models

Self-attention summary networks for subsurface velocity-model building from common-image gathers

SMAT: Simple and Efficient Merge-Aware Training

Structured Pruning of Large Language Models

Eliciting Latent Predictions from Transformers with the Tuned Lens

Hardware-aware Calibrated Clustered Attention for Efficient Visual Geometric Transformers

On the Effectiveness of Least Squares Generative Adversarial Networks

Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging

FedProto: Federated Prototype Learning across Heterogeneous Clients

Optimal Low-Rank Quantum State Tomography with Bounded-Sample Joint Measurements

Evaluating ChatGPT and GPT-4 for Visual Programming

Personalized Wireless Federated Learning for Large Language Models

What Are Bayesian Neural Network Posteriors Really Like?

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings

Federated Learning Meets Multi-objective Optimization

Distributed Clustering of Linear Bandits in Peer to Peer Networks

Knowing When to Ask for Help: Bayesian Self-Escalation in Hierarchical LLM Agents

Heterogeneous Graph Neural Networks for Malicious Account Detection

Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives

What graph neural networks cannot learn: depth vs width

Learning Important Features Through Propagating Activation Differences

The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink

Convergence of Update Aware Device Scheduling for Federated Learning at the Wireless Edge

optimize_anything: A Universal API for Optimizing any Text Parameter

Position: Fairness Failure in Generative Models is an Evaluation Problem

PowerAttention: Exponentially Scaling of Receptive Fields for Effective Sparse Attention

Self-Evaluation as a Defense Against Adversarial Attacks on LLMs

Cognitive Mapping and Planning for Visual Navigation

Playing with Duality: An Overview of Recent Primal-Dual Approaches for Solving Large-Scale Optimization Problems

IdeaLens: Detecting AI Ideas in Long-form Writing

Repeat After Me: Transformers are Better than State Space Models at Copying

Optimizing Visual Generative Models via Distribution-wise Rewards

Wasserstein Auto-Encoders

Label Propagation for Deep Semi-supervised Learning

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Open-MOPD: Diagnosing and Fixing Capability Imbalance in Multi-Teacher On-Policy Distillation

Compression Trinity: Exploring Sparsity, Quantization, and Low-Rank Approximations for LLM Compression

Fast and Effective On-policy Distillation from Reasoning Prefixes

Document-level Relation Extraction as Semantic Segmentation

Values as Style: Disentangling Values from Semantics with One-Way Mixing for Low-Damage LLM Steering

BazaarBench: Delegation Safety in Decentralized C2C Marketplaces Run by LLM Agents

Bridging the Gap Between Value and Policy Based Reinforcement Learning

Probabilistic Prediction of Vehicle Semantic Intention and Motion