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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23,701 to 23,760 of 33,250

Learning to Diagnose with LSTM Recurrent Neural Networks
Zachary C. Lipton, David C. Kale, Charles Elkan +1
cs.LGarXiv:1511.03677v72015
CommunityKV: Efficient Long-Context Decoding via Graph Partitioning
Joe McKenna, Anastasios Alexandridis, Nathan Susanj +1
cs.LGarXiv:2610.00418v12026
Graph-Based Financial Fraud Detection with Calibrated Risk Scoring and Structural Regularization
Yunfei Nie, Jiawei Wang, Ruobing Yan +3
cs.LGarXiv:2605.12782v12026
How to learn a graph from smooth signals
Vassilis Kalofolias
stat.MLcs.LGphysics.data-anarXiv:1601.02513v12016
DMCP: Differentiable Markov Channel Pruning for Neural Networks
Shaopeng Guo, Yujie Wang, Quanquan Li +1
cs.CVcs.LGarXiv:2005.03354v22020
Adversarial Ranking for Language Generation
Kevin Lin, Dianqi Li, Xiaodong He +2
cs.CLcs.LGarXiv:1705.11001v32017
Co-regularized Alignment for Unsupervised Domain Adaptation
Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan +4
cs.LGstat.MLarXiv:1811.05443v12018
Hierarchical Federated Learning Across Heterogeneous Cellular Networks
Mehdi Salehi Heydar Abad, Emre Ozfatura, Deniz Gunduz +1
cs.LGcs.DCcs.ITarXiv:1909.02362v12019
Temporal Memory-Aware Online Test-Time Adaptation on Dynamic Graphs
Bo Li, Xin Zheng, Ming Jin +2
cs.LGarXiv:2608.27948v12026
Test-Time Compute for Tabular Foundation Models: Mechanisms, Gains, and Limits
Kanghui Ning, Marin Biloš, James T. Wilson +5
cs.LGarXiv:2610.12005v12026
Filtering Variational Objectives
Chris J. Maddison, Dieterich Lawson, George Tucker +5
cs.LGcs.AIcs.NEarXiv:1705.09279v32017
Adversarial Sampling and Training for Semi-Supervised Information Retrieval
Dae Hoon Park, Yi Chang
cs.IRcs.LGarXiv:1811.04155v22018
A Survey on Diffusion Models for Inverse Problems
Giannis Daras, Hyungjin Chung, Chieh-Hsin Lai +5
cs.LGcs.AIcs.CVarXiv:2410.00083v12024
3D Morphable Face Models -- Past, Present and Future
Bernhard Egger, William A. P. Smith, Ayush Tewari +10
cs.CVcs.GRcs.LGarXiv:1909.01815v22019
DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels
Haolei Bai, Lingcheng Kong, Xueyi Chen +3
cs.LGcs.CLarXiv:2602.11715v22026
BLADE: Distilled LLM Regularization for Calibrated Knowledge Graph Completion
Ibne Farabi Shihab, Rabeya Bosri Tamanna, Abdo El Karaky +2
cs.LGarXiv:2609.29487v12026
PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
Kaijie Zhu, Jindong Wang, Jiaheng Zhou +8
cs.CLcs.CRcs.LGarXiv:2306.04528v52023
MosMedData: Chest CT Scans With COVID-19 Related Findings Dataset
S. P. Morozov, A. E. Andreychenko, N. A. Pavlov +7
cs.CYcs.LGeess.IVarXiv:2005.06465v12020
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis +6
cs.PLcs.LGarXiv:1802.04730v32018
Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon
Xin Dong, Shangyu Chen, Sinno Jialin Pan
cs.NEcs.CVcs.LGarXiv:1705.07565v22017
RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance
Dongchi Huang, Hongyin Zhang, Bohan Hou +12
cs.ROcs.CVcs.LGarXiv:2608.09853v12026
Combating Label Noise in Deep Learning Using Abstention
Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes +2
stat.MLcs.LGarXiv:1905.10964v22019
Example-driven Parametrisations for Bayesian Shape Optimisation
Gabriel Diaz-Aylwin, Joseph Neighbor, Abiel Malkani Talwar +2
cs.LGarXiv:2610.11984v12026
Balanced Policy Evaluation and Learning
Nathan Kallus
stat.MLcs.LGmath.OCarXiv:1705.07384v22017
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems
Anthony Corso, Robert J. Moss, Mark Koren +2
cs.LGcs.AIeess.SYarXiv:2005.02979v32020
Is One Step Enough for Offline Policy Improvement?
Soohyun Choi, Seonvin Cho, Songnam Hong
cs.LGarXiv:2609.03842v22026
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases
Zechun Liu, Changsheng Zhao, Forrest Iandola +9
cs.LGcs.AIcs.CLarXiv:2402.14905v22024
Neural Module Networks
Jacob Andreas, Marcus Rohrbach, Trevor Darrell +1
cs.CVcs.CLcs.LGarXiv:1511.02799v42015
Variational Diffusion Models
Diederik P. Kingma, Tim Salimans, Ben Poole +1
cs.LGstat.MLarXiv:2107.00630v62021
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
Yuchao Lin, Keqiang Yan, Youzhi Luo +3
physics.chem-phcs.LGarXiv:2306.10045v92023
Accelerated Algorithm for Sparse Regularized Partial Optimal Transport
Khoa Nguyen, Dung T. Nguyen, Thong Huynh +4
cs.LGarXiv:2609.40075v12026
On the Capability Separation Between World-Model Policy Learning and Imitated World-Action Models
Yang Yu
cs.LGarXiv:2608.22197v12026
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks
Yibo Yang, Paris Perdikaris
stat.MLcs.LGphysics.comp-pharXiv:1811.04026v12018
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
Jinxin Zhou, Xiao Li, Tianyu Ding +3
cs.LGcs.AIcs.ITarXiv:2203.01238v22022
Inductive Representation Learning on Temporal Graphs
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
cs.LGstat.MLarXiv:2002.07962v12020
CoBA-RL: Capability-Oriented Budget Allocation for Reinforcement Learning in LLMs
Zhiyuan Yao, Yi-Kai Zhang, Yuxin Chen +7
cs.LGcs.AIarXiv:2602.03048v32026
T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction
Ling Zhao, Yujiao Song, Chao Zhang +5
cs.LGstat.MLarXiv:1811.05320v32018
Predicting materials properties without crystal structure: Deep representation learning from stoichiometry
Rhys E. A. Goodall, Alpha A. Lee
physics.comp-phcond-mat.mtrl-scics.LGarXiv:1910.00617v42019
CAPABLE: Capability-Aware Policy Adaptation via Behavioral Latent Encoding
Mohammad Khoshnazar, Mohammad Dehghani Tezerjani, Deyuan Qu +6
cs.ROcs.LGcs.SYarXiv:2610.11971v12026
Re2: A Consistency-ensured Dataset for Full-stage Peer Review and Multi-turn Rebuttal Discussions
Daoze Zhang, Zhijian Bao, Sihang Du +4
cs.CLcs.AIcs.LGarXiv:2505.07920v22025
SmoothGrad: removing noise by adding noise
Daniel Smilkov, Nikhil Thorat, Been Kim +2
cs.LGcs.CVstat.MLarXiv:1706.03825v12017
Variational Autoencoders Pursue PCA Directions (by Accident)
Michal Rolinek, Dominik Zietlow, Georg Martius
cs.LGcs.CVstat.MLarXiv:1812.06775v22018
Interleaved Multitask Learning with Energy Modulated Learning Progress
Hanne Say, Suzan Ece Ada, Emre Ugur +2
cs.ROcs.AIcs.LGarXiv:2504.00707v22025
On Context-Dependent Clustering of Bandits
Claudio Gentile, Shuai Li, Purushottam Kar +3
cs.LGcs.AIcs.IRarXiv:1608.03544v22016
Stochastic Grouping Conformal Prediction for Effective Subgroup Reliability
Meihui Zhong, Wenxin Tai, Ting Zhong +1
cs.LGcs.AIarXiv:2610.11957v12026
How Robust Are Automated Fact-Checking Systems? A Cross-Benchmark Evaluation
Aida Usmanova, Zangir Iklassov, Markus Leippold +1
cs.AIcs.LGarXiv:2608.25934v12026
Explainable Reinforcement Learning: A Survey
Erika Puiutta, Eric MSP Veith
cs.LGstat.MLarXiv:2005.06247v12020
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
Zhongkai Hao, Jiachen Yao, Chang Su +8
cs.LGcs.NAmath.NAarXiv:2306.08827v22023
Neural Networks can Learn Representations with Gradient Descent
Alex Damian, Jason D. Lee, Mahdi Soltanolkotabi
cs.LGcs.ITstat.MLarXiv:2206.15144v12022
Do RNN and LSTM have Long Memory?
Jingyu Zhao, Feiqing Huang, Jia Lv +4
stat.MLcs.LGarXiv:2006.03860v22020
An Empirical Study of Rich Subgroup Fairness for Machine Learning
Michael Kearns, Seth Neel, Aaron Roth +1
cs.LGstat.MLarXiv:1808.08166v12018
Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks
Michelle A. Lee, Yuke Zhu, Peter Zachares +6
cs.ROcs.LGarXiv:1907.13098v12019
It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization
Ali Behrouz, Meisam Razaviyayn, Peilin Zhong +1
cs.LGcs.AIarXiv:2504.13173v12025
Learning to Optimize under Non-Stationarity
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
cs.LGstat.MLarXiv:1810.03024v62018
Metaheuristic Design of Feedforward Neural Networks: A Review of Two Decades of Research
Varun Kumar Ojha, Ajith Abraham, Václav Snášel
cs.NEcs.LGarXiv:1705.05584v12017
Certified Data Removal from Machine Learning Models
Chuan Guo, Tom Goldstein, Awni Hannun +1
cs.LGstat.MLarXiv:1911.03030v62019
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
Huaxiu Yao, Fei Wu, Jintao Ke +6
cs.LGstat.MLarXiv:1802.08714v22018
Mendel Gödel Machine: Recursive Self-Improving Coding Agents via Comparative Evolution
Changzhi Liu, Yilun Liu, Sikuan Yan +2
cs.AIcs.LGarXiv:2608.07645v12026
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning
Arnav Chavan, Zhuang Liu, Deepak Gupta +2
cs.LGcs.AIcs.CVarXiv:2306.07967v22023
Modular Networks: Learning to Decompose Neural Computation
Louis Kirsch, Julius Kunze, David Barber
cs.LGcs.AIstat.MLarXiv:1811.05249v12018

Machine Learning

Learning to Diagnose with LSTM Recurrent Neural Networks

CommunityKV: Efficient Long-Context Decoding via Graph Partitioning

Graph-Based Financial Fraud Detection with Calibrated Risk Scoring and Structural Regularization

How to learn a graph from smooth signals

DMCP: Differentiable Markov Channel Pruning for Neural Networks

Adversarial Ranking for Language Generation

Co-regularized Alignment for Unsupervised Domain Adaptation

Hierarchical Federated Learning Across Heterogeneous Cellular Networks

Temporal Memory-Aware Online Test-Time Adaptation on Dynamic Graphs

Test-Time Compute for Tabular Foundation Models: Mechanisms, Gains, and Limits

Filtering Variational Objectives

Adversarial Sampling and Training for Semi-Supervised Information Retrieval

A Survey on Diffusion Models for Inverse Problems

3D Morphable Face Models -- Past, Present and Future

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

BLADE: Distilled LLM Regularization for Calibrated Knowledge Graph Completion

PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

MosMedData: Chest CT Scans With COVID-19 Related Findings Dataset

Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance

Combating Label Noise in Deep Learning Using Abstention

Example-driven Parametrisations for Bayesian Shape Optimisation

Balanced Policy Evaluation and Learning

A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems

Is One Step Enough for Offline Policy Improvement?

MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Neural Module Networks

Variational Diffusion Models

Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction

Accelerated Algorithm for Sparse Regularized Partial Optimal Transport

On the Capability Separation Between World-Model Policy Learning and Imitated World-Action Models

Adversarial Uncertainty Quantification in Physics-Informed Neural Networks

On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features

Inductive Representation Learning on Temporal Graphs

CoBA-RL: Capability-Oriented Budget Allocation for Reinforcement Learning in LLMs

T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction

Predicting materials properties without crystal structure: Deep representation learning from stoichiometry

CAPABLE: Capability-Aware Policy Adaptation via Behavioral Latent Encoding

Re2: A Consistency-ensured Dataset for Full-stage Peer Review and Multi-turn Rebuttal Discussions

SmoothGrad: removing noise by adding noise

Variational Autoencoders Pursue PCA Directions (by Accident)

Interleaved Multitask Learning with Energy Modulated Learning Progress

On Context-Dependent Clustering of Bandits

Stochastic Grouping Conformal Prediction for Effective Subgroup Reliability

How Robust Are Automated Fact-Checking Systems? A Cross-Benchmark Evaluation

Explainable Reinforcement Learning: A Survey

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Neural Networks can Learn Representations with Gradient Descent

Do RNN and LSTM have Long Memory?

An Empirical Study of Rich Subgroup Fairness for Machine Learning

Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks

It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization

Learning to Optimize under Non-Stationarity

Metaheuristic Design of Feedforward Neural Networks: A Review of Two Decades of Research

Certified Data Removal from Machine Learning Models

Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

Mendel Gödel Machine: Recursive Self-Improving Coding Agents via Comparative Evolution

One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning

Modular Networks: Learning to Decompose Neural Computation