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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5,341 to 5,400 of 20,214

A Constitutive Markov Physics-Informed Neural Operator (MPNO) for Autoregressive Stability in Transient Dynamics
Wenpu Du, Peng Zhou, Yunlong Xia +5
cs.LGarXiv:2608.25744v12026
How to Train a Critic Stably and Efficiently
Penghui Qi, Xiangxin Zhou, Wee Sun Lee
cs.LGcs.AIcs.CLarXiv:2608.23566v12026
A Query-Time Framework for Transient 2D Pore-Scale Flow Prediction and Generative Design
Yiming Wang, Jiale Zhu, Zhichen Ye +4
cs.LGarXiv:2608.22235v12026
Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination
Subhadeep Pal, Shashwat Sourav, Tirthankar Ghosal +1
cs.AIcond-mat.mtrl-scics.CLarXiv:2607.00924v12026
Summaries:한국어
Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization
Robert Tjarko Lange, Qi Sun, Aaditya Prasad +3
cs.SEcs.AIcs.LGarXiv:2509.14279v12025
PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers
Phillip Lippe, Bastiaan S. Veeling, Paris Perdikaris +2
cs.LGcs.AIarXiv:2308.05732v22023
Graph Representation Learning in Biomedicine
Michelle M. Li, Kexin Huang, Marinka Zitnik
cs.LGcs.SIq-bio.BMarXiv:2104.04883v32021
Identity-aware Graph Neural Networks
Jiaxuan You, Jonathan Gomes-Selman, Rex Ying +1
cs.LGcs.AIcs.SIarXiv:2101.10320v22021
A Point-Cloud Deep Learning Framework for Prediction of Fluid Flow Fields on Irregular Geometries
Ali Kashefi, Davis Rempe, Leonidas J. Guibas
cs.LGphysics.flu-dynarXiv:2010.09469v22020
TrajGAIL: Generating Urban Vehicle Trajectories using Generative Adversarial Imitation Learning
Seongjin Choi, Jiwon Kim, Hwasoo Yeo
cs.LGstat.MLarXiv:2007.14189v42020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates
Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri +2
cs.LGcs.DCmath.OCarXiv:2003.10422v32020
The Synthesizability of Molecules Proposed by Generative Models
Wenhao Gao, Connor W. Coley
q-bio.QMcs.LGstat.MLarXiv:2002.07007v12020
Federated Learning of a Mixture of Global and Local Models
Filip Hanzely, Peter Richtárik
cs.LGcs.DCmath.OCarXiv:2002.05516v32020
Multi-source Distilling Domain Adaptation
Sicheng Zhao, Guangzhi Wang, Shanghang Zhang +7
cs.LGcs.CVstat.MLarXiv:1911.11554v22019
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring
David Berthelot, Nicholas Carlini, Ekin D. Cubuk +4
cs.LGcs.CVstat.MLarXiv:1911.09785v22019
Variational Autoencoders and Nonlinear ICA: A Unifying Framework
Ilyes Khemakhem, Diederik P. Kingma, Ricardo Pio Monti +1
stat.MLcs.LGarXiv:1907.04809v42019
On the Emergence of Position Bias in Transformers
Xinyi Wu, Yifei Wang, Stefanie Jegelka +1
cs.LGarXiv:2502.01951v42025
Adversarial Network Embedding
Quanyu Dai, Qiang Li, Jian Tang +1
cs.LGarXiv:1711.07838v12017
EEG-VID: Task-Guided Latent Predictive Pretraining for EEG Decoding and Assistive Target Selection
Guanzhong Sun, Junyi Ma, Yuxuan Wu +1
cs.LGcs.AIarXiv:2609.00566v22026
Look Inward to Explore Outward: Learning Temperature Policy from LLM Internal States via Hierarchical RL
Yixiao Zhou, Yang Li, Dongzhou Cheng +2
cs.LGcs.AIcs.CLarXiv:2602.13035v12026
Improving Variational Auto-Encoders using Householder Flow
Jakub M. Tomczak, Max Welling
cs.LGstat.MLarXiv:1611.09630v42016
TKAN: Temporal Kolmogorov-Arnold Networks
Remi Genet, Hugo Inzirillo
cs.LGcs.AIarXiv:2405.07344v42024
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan, Alexander Pritzel, Charles Blundell
stat.MLcs.LGarXiv:1612.01474v32016
A scalable noisy speech dataset and online subjective test framework
Chandan K. A. Reddy, Ebrahim Beyrami, Jamie Pool +3
cs.SDcs.LGeess.ASarXiv:1909.08050v12019
GeoPAR: Large-Scale Multi-Agent Combinatorial Optimization with Geometry-Guided Parallel Autoregressive Learning
Wenjian Wu, Zesheng Jia, Jiaying Tang +2
cs.LGcs.AIcs.NEarXiv:2609.00577v12026
Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks
Itay Safran, Ohad Shamir
cs.LGcs.NEstat.MLarXiv:1610.09887v32016
Understanding and Improving Information Transfer in Multi-Task Learning
Sen Wu, Hongyang R. Zhang, Christopher Ré
cs.LGcs.CLarXiv:2005.00944v12020
Large Language Model Routing with Benchmark Datasets
Tal Shnitzer, Anthony Ou, Mírian Silva +5
cs.CLcs.LGarXiv:2309.15789v12023
AI Agents That Matter
Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel +2
cs.LGcs.AIarXiv:2407.01502v12024
Feature-Weighted Linear Stacking
Joseph Sill, Gabor Takacs, Lester Mackey +1
cs.LGcs.AIarXiv:0911.0460v22009
Importance Weighted Active Learning
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
cs.LGarXiv:0812.4952v42008
Detecting Strategic Deception Using Linear Probes
Nicholas Goldowsky-Dill, Bilal Chughtai, Stefan Heimersheim +1
cs.LGarXiv:2502.03407v12025
Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior
Enrico Verdolotti, Luca Luceri, Silvia Giordano
cs.SIcs.CYcs.LGarXiv:2608.16323v12026
Latent On-Policy Self-Distillation
Guibin Zhang, Jiayang Lyu, Ran Sun +4
cs.LGcs.CLarXiv:2608.13040v12026
Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks
Vaidehi Patil, Peter Hase, Mohit Bansal
cs.CLcs.AIcs.LGarXiv:2309.17410v12023
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks
Mohanad Sarhan, Siamak Layeghy, Nour Moustafa +2
cs.NIcs.CRcs.LGarXiv:2108.12722v32021
Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025
Nitya Thakkar, Mert Yuksekgonul, Jake Silberg +6
cs.AIcs.CLcs.HCarXiv:2504.09737v12025
Energy-based Out-of-distribution Detection
Weitang Liu, Xiaoyun Wang, John D. Owens +1
cs.LGcs.AIarXiv:2010.03759v42020
Graph Neural Ordinary Differential Equations
Michael Poli, Stefano Massaroli, Junyoung Park +3
cs.LGcs.AIstat.MLarXiv:1911.07532v42019
Command A: An Enterprise-Ready Large Language Model
Team Cohere, :, Aakanksha +227
cs.CLcs.AIcs.LGarXiv:2504.00698v22025
Residual Corrective Diffusion Modeling for Km-scale Atmospheric Downscaling
Morteza Mardani, Noah Brenowitz, Yair Cohen +10
cs.LGphysics.ao-pharXiv:2309.15214v42023
Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs
Brandon Smart, Chuanxia Zheng, Iro Laina +1
cs.CVcs.LGarXiv:2408.13912v22024
Current Pathology Foundation Models are unrobust to Medical Center Differences
Edwin D. de Jong, Eric Marcus, Jonas Teuwen
cs.LGcs.AIarXiv:2501.18055v22025
Improving Sample Quality of Diffusion Models Using Self-Attention Guidance
Susung Hong, Gyuseong Lee, Wooseok Jang +1
cs.CVcs.AIcs.LGarXiv:2210.00939v62022
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs
Jongwoo Ko, Tianyi Chen, Sungnyun Kim +4
cs.CLcs.AIcs.LGarXiv:2503.07067v22025
PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing System
Yintao He, Haiyu Mao, Christina Giannoula +6
cs.ARcs.AIcs.DCarXiv:2502.15470v22025
WorldEval: World Model as Real-World Robot Policies Evaluator
Yaxuan Li, Yichen Zhu, Junjie Wen +2
cs.ROcs.CVcs.LGarXiv:2505.19017v12025
Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Survey
Mohamad A. Hady, Siyi Hu, Mahardhika Pratama +2
cs.MAcs.AIcs.LGarXiv:2504.21048v12025
Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models
Vincent Le Guen, Nicolas Thome
stat.MLcs.LGarXiv:1909.09020v42019
Efficient Diffusion Policies for Offline Reinforcement Learning
Bingyi Kang, Xiao Ma, Chao Du +2
cs.LGcs.AIarXiv:2305.20081v22023
Energy-Weighted Flow Matching for Offline Reinforcement Learning
Shiyuan Zhang, Weitong Zhang, Quanquan Gu
cs.LGarXiv:2503.04975v12025
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
Yang Li, Jinpei Guo, Runzhong Wang +2
cs.LGarXiv:2502.02941v12025
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares
Rong Ge, Sham M. Kakade, Rahul Kidambi +1
cs.LGmath.OCstat.MLarXiv:1904.12838v22019
A Survey of Automatic Prompt Engineering: An Optimization Perspective
Wenwu Li, Xiangfeng Wang, Wenhao Li +1
cs.AIcs.LGarXiv:2502.11560v12025
LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?
Zihan Zheng, Zerui Cheng, Zeyu Shen +16
cs.SEcs.AIcs.CLarXiv:2506.11928v12025
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
Yifan Sun, Jingyan Shen, Yibin Wang +4
cs.LGcs.AIcs.CLarXiv:2506.05316v42025
GENMO: A GENeralist Model for Human MOtion
Jiefeng Li, Jinkun Cao, Haotian Zhang +4
cs.GRcs.AIcs.CVarXiv:2505.01425v12025
Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation
Liyiming Ke, Xiujun Li, Yonatan Bisk +6
cs.CLcs.CVcs.LGarXiv:1903.02547v22019
What In-Context Learning "Learns" In-Context: Disentangling Task Recognition and Task Learning
Jane Pan, Tianyu Gao, Howard Chen +1
cs.CLcs.LGarXiv:2305.09731v12023
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling
Chuizheng Meng, Sirisha Rambhatla, Yan Liu
cs.LGcs.AIarXiv:2106.05223v12021

Machine Learning

A Constitutive Markov Physics-Informed Neural Operator (MPNO) for Autoregressive Stability in Transient Dynamics

How to Train a Critic Stably and Efficiently

A Query-Time Framework for Transient 2D Pore-Scale Flow Prediction and Generative Design

Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers

Graph Representation Learning in Biomedicine

Identity-aware Graph Neural Networks

A Point-Cloud Deep Learning Framework for Prediction of Fluid Flow Fields on Irregular Geometries

TrajGAIL: Generating Urban Vehicle Trajectories using Generative Adversarial Imitation Learning

A Unified Theory of Decentralized SGD with Changing Topology and Local Updates

The Synthesizability of Molecules Proposed by Generative Models

Federated Learning of a Mixture of Global and Local Models

Multi-source Distilling Domain Adaptation

ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring

Variational Autoencoders and Nonlinear ICA: A Unifying Framework

On the Emergence of Position Bias in Transformers

Adversarial Network Embedding

EEG-VID: Task-Guided Latent Predictive Pretraining for EEG Decoding and Assistive Target Selection

Look Inward to Explore Outward: Learning Temperature Policy from LLM Internal States via Hierarchical RL

Improving Variational Auto-Encoders using Householder Flow

TKAN: Temporal Kolmogorov-Arnold Networks

Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

A scalable noisy speech dataset and online subjective test framework

GeoPAR: Large-Scale Multi-Agent Combinatorial Optimization with Geometry-Guided Parallel Autoregressive Learning

Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks

Understanding and Improving Information Transfer in Multi-Task Learning

Large Language Model Routing with Benchmark Datasets

AI Agents That Matter

Feature-Weighted Linear Stacking

Importance Weighted Active Learning

Detecting Strategic Deception Using Linear Probes

Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior

Latent On-Policy Self-Distillation

Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks

Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks

Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025

Energy-based Out-of-distribution Detection

Graph Neural Ordinary Differential Equations

Command A: An Enterprise-Ready Large Language Model

Residual Corrective Diffusion Modeling for Km-scale Atmospheric Downscaling

Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs

Current Pathology Foundation Models are unrobust to Medical Center Differences

Improving Sample Quality of Diffusion Models Using Self-Attention Guidance

DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs

PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing System

WorldEval: World Model as Real-World Robot Policies Evaluator

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

Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models

Efficient Diffusion Policies for Offline Reinforcement Learning

Energy-Weighted Flow Matching for Offline Reinforcement Learning

Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization

The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares

A Survey of Automatic Prompt Engineering: An Optimization Perspective

LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?

Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay

GENMO: A GENeralist Model for Human MOtion

Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation

What In-Context Learning "Learns" In-Context: Disentangling Task Recognition and Task Learning

Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling