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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26,401 to 26,460 of 33,123

CiteWorth: Cite-Worthiness Detection for Improved Scientific Document Understanding
Dustin Wright, Isabelle Augenstein
cs.CLcs.DLcs.LGarXiv:2105.10912v22021
Federated Transfer Reinforcement Learning for Autonomous Driving
Xinle Liang, Yang Liu, Tianjian Chen +2
cs.LGcs.AIcs.ROarXiv:1910.06001v12019
TreePO: Bridging the Gap of Policy Optimization and Efficacy and Inference Efficiency with Heuristic Tree-based Modeling
Yizhi Li, Qingshui Gu, Zhoufutu Wen +14
cs.LGcs.CLarXiv:2508.17445v12025
Model-free prediction of spatiotemporal dynamical systems with recurrent neural networks: Role of network spectral radius
Junjie Jiang, Ying-Cheng Lai
cs.LGnlin.CDphysics.data-anarXiv:1910.04426v12019
The Geometry of Ignorance: LLMs Know When to Temper Bayesian Priors
Toni J. B. Liu, Jiajun Bao, Yizhou Liu +4
cs.LGcs.AIcs.CLarXiv:2609.02959v12026
GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification
Jie Zhou, Xu Han, Cheng Yang +4
cs.CLcs.AIcs.LGarXiv:1908.01843v12019
Autonomous Research for Open-Ended Problems: A Case Study on Telecom Ticket Retrieval
Junghyun Min, Huseyin Uzunalioglu, Mohamed Trabelsi
cs.AIcs.IRcs.LGarXiv:2609.13073v12026
Stabilizing Generative Adversarial Networks: A Survey
Maciej Wiatrak, Stefano V. Albrecht, Andrew Nystrom
cs.LGarXiv:1910.00927v22019
CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models
Hyungjin Chung, Jeongsol Kim, Geon Yeong Park +2
cs.CVcs.AIcs.LGarXiv:2406.08070v22024
Scaling data-driven robotics with reward sketching and batch reinforcement learning
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov +13
cs.ROcs.LGarXiv:1909.12200v22019
Meta-HAR: Federated Representation Learning for Human Activity Recognition
Chenglin Li, Di Niu, Bei Jiang +2
eess.SPcs.LGarXiv:2106.00615v12021
Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining
Rajeev Yasarla, Vishal M. Patel
cs.CVcs.LGeess.IVarXiv:1906.11129v12019
Sharp Monocular View Synthesis in Less Than a Second
Lars Mescheder, Wei Dong, Shiwei Li +10
cs.CVcs.LGarXiv:2512.10685v22025
RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback
Yufei Wang, Zhanyi Sun, Jesse Zhang +4
cs.ROcs.AIcs.LGarXiv:2402.03681v42024
Probabilistic Ship Trajectory Forecasting using Transformer Models on AIS Data
Frederik E. T. Schöller
cs.LGcs.ROarXiv:2610.13557v12026
Federated Learning for Ultra-Reliable Low-Latency V2V Communications
Sumudu Samarakoon, Mehdi Bennis, Walid Saad +1
cs.NIcs.LGstat.MLarXiv:1805.09253v12018
ProxQuant: Quantized Neural Networks via Proximal Operators
Yu Bai, Yu-Xiang Wang, Edo Liberty
cs.LGstat.MLarXiv:1810.00861v32018
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection
Yingjie Zhou, Xucheng Song, Yanru Zhang +3
cs.LGcs.NIarXiv:2105.10500v32021
Judging by the Cover: Cleaning LLM Truthfulness Benchmarks to Avoid Surface-Level Feature Leakage
Foad Namjoo, Remy Ogasawara, Amirali Abdullah +3
cs.CLcs.LGarXiv:2609.13003v12026
Adaptive Least Mean Squares Estimation of Graph Signals
Paolo Di Lorenzo, Sergio Barbarossa, Paolo Banelli +1
cs.LGcs.SYeess.SYarXiv:1602.05703v32016
Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data
Sohei Itahara, Takayuki Nishio, Yusuke Koda +2
cs.DCcs.LGarXiv:2008.06180v22020
Learning Latent Space Energy-Based Prior Model
Bo Pang, Tian Han, Erik Nijkamp +2
stat.MLcs.LGarXiv:2006.08205v22020
Training Agents using Upside-Down Reinforcement Learning
Rupesh Kumar Srivastava, Pranav Shyam, Filipe Mutz +2
cs.LGcs.AIcs.ROarXiv:1912.02877v22019
Predicting Process Behaviour using Deep Learning
Joerg Evermann, Jana-Rebecca Rehse, Peter Fettke
cs.LGstat.MLarXiv:1612.04600v22016
AR-Omni: A Unified Autoregressive Model for Any-to-Any Generation
Dongjie Cheng, Ruifeng Yuan, Yongqi Li +5
cs.LGcs.AIcs.CLarXiv:2601.17761v12026
Provably Efficient Q-Learning with Low Switching Cost
Yu Bai, Tengyang Xie, Nan Jiang +1
cs.LGcs.AIstat.MLarXiv:1905.12849v32019
Automatically Extracting Challenge Sets for Non local Phenomena in Neural Machine Translation
Leshem Choshen, Omri Abend
cs.CLcs.LGarXiv:1909.06814v42019
Sample Selection Bias Correction Theory
Corinna Cortes, Mehryar Mohri, Michael Riley +1
cs.LGarXiv:0805.2775v12008
Wrong but Useful: Trajectory Value Beyond Answer Correctness in Multi-Agent Messages
Chih-Hsuan Yang, Anjir Ahmed Chowdhury, Cheng-Hau Yang +7
cs.AIcs.CLcs.LGarXiv:2608.14375v12026
FDA: Feature Disruptive Attack
Aditya Ganeshan, B. S. Vivek, R. Venkatesh Babu
cs.CVcs.AIcs.LGarXiv:1909.04385v12019
ASCENT: Online Test-Time Training of Long-Horizon Agents via Self-Distillation of Verified Experience
Haodong Lu, Dong Gong
cs.LGarXiv:2610.05303v12026
Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation
Gregory P. Meyer, Jake Charland, Darshan Hegde +2
cs.CVcs.LGcs.ROarXiv:1904.11466v12019
Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
Matthieu Courbariaux, Itay Hubara, Daniel Soudry +2
cs.LGarXiv:1602.02830v32016
Temporal Network Embedding with Micro- and Macro-dynamics
Yuanfu Lu, Xiao Wang, Chuan Shi +2
cs.LGcs.SIstat.MLarXiv:1909.04246v12019
Program Synthesis with Large Language Models
Jacob Austin, Augustus Odena, Maxwell Nye +8
cs.PLcs.LGarXiv:2108.07732v12021
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks
Sanjeev Arora, Simon S. Du, Zhiyuan Li +3
cs.LGstat.MLarXiv:1910.01663v32019
Quantifying the Value of Privileged Information Using a PAC-Bayesian Approach
Vasily Bokov, Sebastian Schmitt, Vedran Dunjko +1
cs.LGarXiv:2609.12891v12026
Pressure-Testing Deception Probes in LLMs: Scaling, Robustness, and the Geometry of Deceptive Representations
Sachin Kumar
cs.CLcs.AIcs.LGarXiv:2605.27958v12026
Training Convolutional Networks with Noisy Labels
Sainbayar Sukhbaatar, Joan Bruna, Manohar Paluri +2
cs.CVcs.LGcs.NEarXiv:1406.2080v42014
Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC
Roger Frigola, Fredrik Lindsten, Thomas B. Schön +1
stat.MLcs.LGeess.SYarXiv:1306.2861v22013
Triangle Generative Adversarial Networks
Zhe Gan, Liqun Chen, Weiyao Wang +5
cs.LGstat.MLarXiv:1709.06548v22017
MAxBench: A Multinomial Concept Recovery Benchmark
Divya Appapogu, Freya Behrens, Yonatan Belinkov +1
cs.LGcs.AIcs.CLarXiv:2609.13072v12026
Topological Graph Neural Networks
Max Horn, Edward De Brouwer, Michael Moor +3
cs.LGmath.ATstat.MLarXiv:2102.07835v42021
The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial
Benyamin Ghojogh, Mark Crowley
stat.MLcs.LGarXiv:1905.12787v22019
Latent Flow Matching for Molecular Graph Generation
Mathis Goupillon, Roman Bresson, Konstantinos Divriotis +1
cs.LGcs.AIarXiv:2610.06468v12026
Imaging Time-Series to Improve Classification and Imputation
Zhiguang Wang, Tim Oates
cs.LGcs.NEstat.MLarXiv:1506.00327v12015
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs
Yvan Lucas, Pierre-Edouard Portier, Léa Laporte +4
cs.LGstat.MLarXiv:1909.01185v12019
MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
Qian Huang, Jian Vora, Percy Liang +1
cs.LGcs.AIarXiv:2310.03302v22023
A Physics-Guided Transformer Framework for Electromigration Analysis in Multi-Segment Interconnects
Pavlos Stoikos, Anuj Pathania, George Floros
cs.LGcs.AIarXiv:2610.06464v12026
Deep Variational Canonical Correlation Analysis
Weiran Wang, Xinchen Yan, Honglak Lee +1
cs.LGarXiv:1610.03454v32016
Canalization Before Generalization: Grokking as a Dynamical Probe
Yiming Lin
cs.LGarXiv:2608.25813v12026
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent
Yunwen Lei, Yiming Ying
cs.LGstat.MLarXiv:2006.08157v12020
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction
Kwan Ho Ryan Chan, Yaodong Yu, Chong You +3
cs.LGcs.CVcs.ITarXiv:2105.10446v32021
ARO: Aligned Representation learning for multi-Omics data
Amogh Singh, Yash Shah, Chiara D'Ercoli +4
cs.LGcs.AIarXiv:2610.06443v12026
Towards a Rigorous Evaluation of XAI Methods on Time Series
Udo Schlegel, Hiba Arnout, Mennatallah El-Assady +2
cs.LGcs.AIarXiv:1909.07082v22019
Words or Vision: Do Vision-Language Models Have Blind Faith in Text?
Ailin Deng, Tri Cao, Zhirui Chen +1
cs.CVcs.AIcs.CLarXiv:2503.02199v12025
COEC: Calibrated Orthogonal-Equivalence Compensation for Structured Pruning of Large Language Models
Peiqi Yu, Nam Ling, Wei Wang +1
cs.LGarXiv:2608.21142v12026
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications
Mostafa Rahimi Azghadi, Corey Lammie, Jason K. Eshraghian +4
cs.ARcs.LGeess.SParXiv:2007.05657v22020
Valid Stopping in Adaptive Generator-Verifier Loops
Mahmoud Hegazy, Michael I. Jordan, Aymeric Dieuleveut
stat.MLcs.AIcs.LGarXiv:2610.06432v12026
How can embedding models bind concepts?
Arnas Uselis, Darina Koishigarina, Seong Joon Oh
cs.CVcs.LGarXiv:2605.31503v12026

Machine Learning

CiteWorth: Cite-Worthiness Detection for Improved Scientific Document Understanding

Federated Transfer Reinforcement Learning for Autonomous Driving

TreePO: Bridging the Gap of Policy Optimization and Efficacy and Inference Efficiency with Heuristic Tree-based Modeling

Model-free prediction of spatiotemporal dynamical systems with recurrent neural networks: Role of network spectral radius

The Geometry of Ignorance: LLMs Know When to Temper Bayesian Priors

GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification

Autonomous Research for Open-Ended Problems: A Case Study on Telecom Ticket Retrieval

Stabilizing Generative Adversarial Networks: A Survey

CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models

Scaling data-driven robotics with reward sketching and batch reinforcement learning

Meta-HAR: Federated Representation Learning for Human Activity Recognition

Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining

Sharp Monocular View Synthesis in Less Than a Second

RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback

Probabilistic Ship Trajectory Forecasting using Transformer Models on AIS Data

Federated Learning for Ultra-Reliable Low-Latency V2V Communications

ProxQuant: Quantized Neural Networks via Proximal Operators

Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection

Judging by the Cover: Cleaning LLM Truthfulness Benchmarks to Avoid Surface-Level Feature Leakage

Adaptive Least Mean Squares Estimation of Graph Signals

Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data

Learning Latent Space Energy-Based Prior Model

Training Agents using Upside-Down Reinforcement Learning

Predicting Process Behaviour using Deep Learning

AR-Omni: A Unified Autoregressive Model for Any-to-Any Generation

Provably Efficient Q-Learning with Low Switching Cost

Automatically Extracting Challenge Sets for Non local Phenomena in Neural Machine Translation

Sample Selection Bias Correction Theory

Wrong but Useful: Trajectory Value Beyond Answer Correctness in Multi-Agent Messages

FDA: Feature Disruptive Attack

ASCENT: Online Test-Time Training of Long-Horizon Agents via Self-Distillation of Verified Experience

Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation

Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Temporal Network Embedding with Micro- and Macro-dynamics

Program Synthesis with Large Language Models

Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks

Quantifying the Value of Privileged Information Using a PAC-Bayesian Approach

Pressure-Testing Deception Probes in LLMs: Scaling, Robustness, and the Geometry of Deceptive Representations

Training Convolutional Networks with Noisy Labels

Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC

Triangle Generative Adversarial Networks

MAxBench: A Multinomial Concept Recovery Benchmark

Topological Graph Neural Networks

The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial

Latent Flow Matching for Molecular Graph Generation

Imaging Time-Series to Improve Classification and Imputation

Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs

MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

A Physics-Guided Transformer Framework for Electromigration Analysis in Multi-Segment Interconnects

Deep Variational Canonical Correlation Analysis

Canalization Before Generalization: Grokking as a Dynamical Probe

Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent

ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction

ARO: Aligned Representation learning for multi-Omics data

Towards a Rigorous Evaluation of XAI Methods on Time Series

Words or Vision: Do Vision-Language Models Have Blind Faith in Text?

COEC: Calibrated Orthogonal-Equivalence Compensation for Structured Pruning of Large Language Models

Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

Valid Stopping in Adaptive Generator-Verifier Loops

How can embedding models bind concepts?