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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27,841 to 27,900 of 33,092

ibUMAP: Coherent and Scalable Field Evaluation for UMAP Optimization
Bin Chen, Yumeng Xue, Patrick Paetzold +2
cs.LGcs.HCarXiv:2610.01445v12026
Adaptive Defense against Harmful Fine-Tuning for Large Language Models via Bayesian Data Scheduler
Zixuan Hu, Li Shen, Zhenyi Wang +2
cs.LGcs.AIarXiv:2510.27172v12025
Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents
Shuai Shao, Qihan Ren, Chen Qian +8
cs.AIcs.CLcs.LGarXiv:2509.26354v22025
Improving Multivariate Time Series Classification with Class-Wise Training and Model Aggregation
Mouhamadou Mansour Lo, Gildas Morvan, Mathieu Rossi +2
cs.LGarXiv:2609.07493v12026
What Doubling Tricks Can and Can't Do for Multi-Armed Bandits
Lilian Besson, Emilie Kaufmann
stat.MLcs.LGmath.STarXiv:1803.06971v12018
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler, Dan Alistarh, Tal Ben-Nun +2
cs.LGcs.AIcs.ARarXiv:2102.00554v12021
Neural Symbolic Regression that Scales
Luca Biggio, Tommaso Bendinelli, Alexander Neitz +2
cs.LGarXiv:2106.06427v12021
Insights into Performance Fitness and Error Metrics for Machine Learning
M. Z. Naser, Amir Alavi
cs.LGphysics.data-anstat.MLarXiv:2006.00887v12020
DemoFusion: Democratising High-Resolution Image Generation With No $$$
Ruoyi Du, Dongliang Chang, Timothy Hospedales +2
cs.CVcs.AIcs.LGarXiv:2311.16973v22023
Learning Ordered Representations with Nested Dropout
Oren Rippel, Michael A. Gelbart, Ryan P. Adams
stat.MLcs.LGarXiv:1402.0915v12014
The Lattice of Transition Laws
T. Y. Tsui, Jiatao Gu, Lingjie Liu
cs.LGcs.CLarXiv:2610.11216v12026
Training Plug-n-Play Knowledge Modules with Deep Context Distillation
Lucas Caccia, Alan Ansell, Edoardo Ponti +2
cs.LGcs.AIarXiv:2503.08727v42025
Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD
Murat Bilgehan Ertan, Marten van Dijk
cs.LGcs.CRarXiv:2601.10237v32026
A Survey of Reinforcement Learning from Human Feedback
Timo Kaufmann, Paul Weng, Viktor Bengs +1
cs.LGarXiv:2312.14925v32023
Your Language Model is Its Own Critic: Reinforcement Learning with Value Estimation from Actor's Internal States
Yunho Choi, Jongwon Lim, Woojin Ahn +3
cs.LGcs.AIcs.CLarXiv:2605.07579v22026
Least-time Gradient Flow
Alessandro Betti, Marco Gori, Stefano Melacci +1
cs.LGmath.OCarXiv:2610.01426v12026
LevelSyn: Physical-Aware Logic Synthesis via Level-Asynchronous Graph Neural Networks
Jingyi Zhou, Zhengyuan Shi, Ziyang Zheng +1
cs.ARcs.AIcs.LGarXiv:2609.03594v12026
Graph neural networks and the energetic cavity method for combinatorial optimization
Joe Bacchus George, George T. Cantwell
cond-mat.dis-nncs.LGarXiv:2609.07456v12026
Dissecting Representation Structure in Vision Transformers: A Rigorous Architectural Study
Kim-Cuc Nguyen, Ngai-Man Cheung
cs.CVcs.LGarXiv:2610.11205v12026
Parser-Free VLM Verification for Federated Weakly Supervised Video Anomaly Detection
Sébastien Thuau, Amira Gran, Siba Haidar +1
cs.CVcs.AIcs.LGarXiv:2609.07455v12026
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Jongho Park, Jaeseung Park, Zheyang Xiong +5
cs.LGarXiv:2402.04248v22024
Learning from Noisy Labels with Distillation
Yuncheng Li, Jianchao Yang, Yale Song +3
cs.CVcs.LGstat.MLarXiv:1703.02391v22017
TASTE: Throughput-Aware Batch Size Tuning for On-Device Edge Learning
Avik Bhatnagar, Federico Nicolas Peccia, Oliver Bringmann
cs.LGcs.AIcs.ARarXiv:2609.07444v12026
EvoSignal: LLM-Guided Evolutionary Design of Modular Traffic Signal Control Programs
Leizhen Wang, Peibo Duan, Zhenlin Qin +5
cs.LGarXiv:2610.09563v12026
Transformers as In-Context Samplers: From Closed-Form Diffusion to Estimation-Free Sampling
Arman Adibi, Alireza Jafari, Mohammad Ghavamzadeh +1
cs.LGcs.AIstat.AParXiv:2609.08981v12026
LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning
Han Guo, Philip Greengard, Eric P. Xing +1
cs.CLcs.LGarXiv:2311.12023v42023
TEMPO: Scaling Test-time Training for Large Reasoning Models
Qingyang Zhang, Xinke Kong, Haitao Wu +7
cs.LGarXiv:2604.19295v12026
Smoother Flow Matching via Contrastive Trajectory Repulsion
Ziqi Jiang, Zhenqi He, Long Chen
cs.CVcs.LGarXiv:2610.01408v12026
Training Quantum Embedding Kernels on Near-Term Quantum Computers
Thomas Hubregtsen, David Wierichs, Elies Gil-Fuster +3
quant-phcs.LGarXiv:2105.02276v12021
Supermasks in Superposition
Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu +4
cs.LGcs.AIstat.MLarXiv:2006.14769v32020
Reusing Past Samples in Proximal Policy Optimization: When and How Does It Help?
Alessandro Montenegro, Riccardo Venturelli, Marco Mussi +2
cs.LGarXiv:2610.01399v12026
Correlated initialization of deep residual networks
Felix Benning, Ivan Nourdin, Giovanni Peccati
math.PRcs.LGstat.MLarXiv:2609.03589v12026
One Axis, No Brake: Self-Knowledge Limits the Filtering of Harmful Peer Conformity in LLMs
Yibo Hu
cs.LGcs.CLcs.MAarXiv:2609.18998v12026
Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classification
Sheng Wan, Chen Gong, Ping Zhong +3
eess.IVcs.LGstat.MLarXiv:1905.06133v12019
Cheap Bandits
Manjesh Kumar Hanawal, Venkatesh Saligrama, Michal Valko +1
cs.LGstat.MLarXiv:1506.04782v22015
SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution
Zhiyuan Yao, Yuxin Chen, Zhengxi Lu +13
cs.LGcs.AIarXiv:2607.26784v12026
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He, Songze Li, Jinhyun So +17
cs.LGstat.MLarXiv:2007.13518v42020
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
Zhewei Yao, Amir Gholami, Sheng Shen +3
cs.LGmath.NAstat.MLarXiv:2006.00719v32020
Second-order Non-local Attention Networks for Person Re-identification
Bryan, Xia, Yuan Gong +2
cs.CVcs.AIcs.LGarXiv:1909.00295v12019
VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text
Tianyu Zhang, Suyuchen Wang, Lu Li +6
cs.CVcs.LGarXiv:2406.06462v42024
No Pain, More Gain: Iterative Merging for Effective Multi-Teacher On-Policy Distillation
Seonghyeon Kim, Chaeyun Jang, Noah Lee +2
cs.LGcs.AIarXiv:2609.34745v12026
Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections
Jacopo Ghirri, Carlos Rodriguez-Pardo, Lara Aleluia Reis +1
cs.LGcs.AIecon.GNarXiv:2608.18690v12026
The Denario project: Deep knowledge AI agents for scientific discovery
Francisco Villaescusa-Navarro, Boris Bolliet, Pablo Villanueva-Domingo +33
cs.AIcs.CLcs.LGarXiv:2510.26887v12025
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI
Erico Tjoa, Cuntai Guan
cs.LGcs.AIarXiv:1907.07374v52019
FCN-Transformer Feature Fusion for Polyp Segmentation
Edward Sanderson, Bogdan J. Matuszewski
eess.IVcs.CVcs.LGarXiv:2208.08352v12022
Adversarial Examples: Opportunities and Challenges
Jiliang Zhang, Chen Li
cs.LGstat.MLarXiv:1809.04790v42018
How2Everything: Mining the Web for How-To Procedures to Evaluate and Improve LLMs
Yapei Chang, Kyle Lo, Mohit Iyyer +1
cs.LGarXiv:2602.08808v12026
Are We Really Doing Few-Shot Learning? A Critical Examination of Pre-Training Assumptions
Alejandro Galan-Cuenca, Marcelo Saval-Calvo, Antonio Javier Gallego
cs.CVcs.AIcs.LGarXiv:2609.10851v12026
Recurrent Orthogonal Networks and Long-Memory Tasks
Mikael Henaff, Arthur Szlam, Yann LeCun
cs.NEcs.AIcs.LGarXiv:1602.06662v22016
KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta
Gang Liao, Hongsen Qin, Ying Wang +36
cs.LGcs.AIcs.ARarXiv:2512.23236v42025
DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications
Nathanaël Perraudin, Michaël Defferrard, Tomasz Kacprzak +1
astro-ph.COastro-ph.IMcs.AIarXiv:1810.12186v22018
Deep Learning for Multivariate Time Series Imputation: A Survey
Jun Wang, Wenjie Du, Yiyuan Yang +6
cs.LGcs.AIarXiv:2402.04059v32024
dLLM: Simple Diffusion Language Modeling
Zhanhui Zhou, Lingjie Chen, Hanghang Tong +1
cs.CLcs.AIcs.LGarXiv:2602.22661v12026
Adaptive Neural Signal Detection for Massive MIMO
Mehrdad Khani, Mohammad Alizadeh, Jakob Hoydis +1
eess.SPcs.LGstat.MLarXiv:1906.04610v12019
Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks
Samuele Poppi, Zheng-Xin Yong, Yifei He +4
cs.CLcs.AIcs.CRarXiv:2410.18210v22024
LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood
Abhinav Kumar, Tim K. Marks, Wenxuan Mou +6
cs.CVcs.LGeess.IVarXiv:2004.02980v12020
The Tsetlin Machine -- A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional Logic
Ole-Christoffer Granmo
cs.AIcs.CVcs.LGarXiv:1804.01508v152018
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow +3
cs.CRcs.LGarXiv:1602.02697v42016
When Does Self-Supervised Pretraining Help Tabular Models? A Study of Label Scarcity and Missing Data
Sahand Mazrouei
cs.LGarXiv:2608.24381v12026
Momentum in large-batch training: Polyak enlarges the critical batch size, Nesterov improves data efficiency
Jia-Nan Wang, Zixun Huang, Kairui Li +1
stat.MLcs.LGmath.OCarXiv:2609.02728v12026

Machine Learning

ibUMAP: Coherent and Scalable Field Evaluation for UMAP Optimization

Adaptive Defense against Harmful Fine-Tuning for Large Language Models via Bayesian Data Scheduler

Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents

Improving Multivariate Time Series Classification with Class-Wise Training and Model Aggregation

What Doubling Tricks Can and Can't Do for Multi-Armed Bandits

Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks

Neural Symbolic Regression that Scales

Insights into Performance Fitness and Error Metrics for Machine Learning

DemoFusion: Democratising High-Resolution Image Generation With No $$$

Learning Ordered Representations with Nested Dropout

The Lattice of Transition Laws

Training Plug-n-Play Knowledge Modules with Deep Context Distillation

Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD

A Survey of Reinforcement Learning from Human Feedback

Your Language Model is Its Own Critic: Reinforcement Learning with Value Estimation from Actor's Internal States

Least-time Gradient Flow

LevelSyn: Physical-Aware Logic Synthesis via Level-Asynchronous Graph Neural Networks

Graph neural networks and the energetic cavity method for combinatorial optimization

Dissecting Representation Structure in Vision Transformers: A Rigorous Architectural Study

Parser-Free VLM Verification for Federated Weakly Supervised Video Anomaly Detection

Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks

Learning from Noisy Labels with Distillation

TASTE: Throughput-Aware Batch Size Tuning for On-Device Edge Learning

EvoSignal: LLM-Guided Evolutionary Design of Modular Traffic Signal Control Programs

Transformers as In-Context Samplers: From Closed-Form Diffusion to Estimation-Free Sampling

LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning

TEMPO: Scaling Test-time Training for Large Reasoning Models

Smoother Flow Matching via Contrastive Trajectory Repulsion

Training Quantum Embedding Kernels on Near-Term Quantum Computers

Supermasks in Superposition

Reusing Past Samples in Proximal Policy Optimization: When and How Does It Help?

Correlated initialization of deep residual networks

One Axis, No Brake: Self-Knowledge Limits the Filtering of Harmful Peer Conformity in LLMs

Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classification

Cheap Bandits

SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution

FedML: A Research Library and Benchmark for Federated Machine Learning

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

Second-order Non-local Attention Networks for Person Re-identification

VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text

No Pain, More Gain: Iterative Merging for Effective Multi-Teacher On-Policy Distillation

Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections

The Denario project: Deep knowledge AI agents for scientific discovery

A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI

FCN-Transformer Feature Fusion for Polyp Segmentation

Adversarial Examples: Opportunities and Challenges

How2Everything: Mining the Web for How-To Procedures to Evaluate and Improve LLMs

Are We Really Doing Few-Shot Learning? A Critical Examination of Pre-Training Assumptions

Recurrent Orthogonal Networks and Long-Memory Tasks

KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta

DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications

Deep Learning for Multivariate Time Series Imputation: A Survey

dLLM: Simple Diffusion Language Modeling

Adaptive Neural Signal Detection for Massive MIMO

Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks

LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood

The Tsetlin Machine -- A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional Logic

Practical Black-Box Attacks against Machine Learning

When Does Self-Supervised Pretraining Help Tabular Models? A Study of Label Scarcity and Missing Data

Momentum in large-batch training: Polyak enlarges the critical batch size, Nesterov improves data efficiency