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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25,801 to 25,860 of 33,309

Trust-Region Optimization for Smooth Potential-Interaction Energies in Wasserstein Space
You Wan, Ting Gao, Jinqiao Duan
stat.MLcs.LGmath.OCarXiv:2610.08883v12026
Fast and accurate sentiment classification using an enhanced Naive Bayes model
Vivek Narayanan, Ishan Arora, Arjun Bhatia
cs.CLcs.IRcs.LGarXiv:1305.6143v22013
Understanding Learned Reward Functions
Eric J. Michaud, Adam Gleave, Stuart Russell
cs.LGarXiv:2012.05862v12020
SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training
Gowthami Somepalli, Micah Goldblum, Avi Schwarzschild +2
cs.LGcs.AIstat.MLarXiv:2106.01342v12021
Stream Recursion Model (SRM)
Asael Sorensen, Charles Brock, David Chamberlain +3
cs.LGarXiv:2609.28809v12026
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data
Shaoli Huang, Xinchao Wang, Dacheng Tao
cs.CVcs.LGarXiv:2012.04846v12020
Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs
Yibo Wang, Hai-Long Sun, Qing-Guo Chen +4
cs.CLcs.LGarXiv:2601.08198v12026
Graph-Based Learning for Multi-Horizon Martian Atmospheric Forecasting
Gary Myler, James Holmes, Manish Patel +1
cs.SEcs.LGarXiv:2609.35042v12026
Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks
Jianghui Wang, Vinay Joshi, Saptarshi Majumder +7
cs.CLcs.AIcs.LGarXiv:2507.23194v12025
Scaling Laws For Scalable Oversight
Joshua Engels, David D. Baek, Subhash Kantamneni +1
cs.AIcs.CYcs.LGarXiv:2504.18530v32025
How to Teach Large Multimodal Models New Skills
Zhen Zhu, Yiming Gong, Yao Xiao +2
cs.AIcs.CVcs.LGarXiv:2510.08564v22025
A Bayesian Mirror Architecture for Emergent Consciousness: Circular Hierarchies, Self-Manifolds, and Hybrid Event-Self Binding
Eduardo Righi Capanema de Almeida
cs.LGarXiv:2610.08792v12026
VEX-Bench: Benchmarking Verification Complexity of LLM-Generated Misinformation
Hanxun Huang, Yutao Wu, Qizhou Wang +9
cs.LGcs.AIcs.CLarXiv:2609.35028v12026
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization
Koen Helwegen, James Widdicombe, Lukas Geiger +3
cs.LGstat.MLarXiv:1906.02107v22019
Representation Learning for Attributed Multiplex Heterogeneous Network
Yukuo Cen, Xu Zou, Jianwei Zhang +3
cs.SIcs.LGarXiv:1905.01669v22019
Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?
Raja Giryes, Guillermo Sapiro, Alex M. Bronstein
cs.NEcs.LGstat.MLarXiv:1504.08291v52015
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation
Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov +8
cs.LGmath.OCarXiv:2012.03826v62020
Adversary Resistant Deep Neural Networks with an Application to Malware Detection
Qinglong Wang, Wenbo Guo, Kaixuan Zhang +4
cs.LGarXiv:1610.01239v42016
QiYao-M: Multimodal Time Series Foundation Model with Role-Aware Modeling of Endogenous and Exogenous Modalities
Hanyin Cheng, Linfeng Wang, Zhengbo Qu +7
cs.LGarXiv:2609.34842v12026
Towards Out-Of-Distribution Generalization: A Survey
Jiashuo Liu, Zheyan Shen, Yue He +4
cs.LGarXiv:2108.13624v22021
Scaling Vision Transformers
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby +1
cs.CVcs.AIcs.LGarXiv:2106.04560v22021
CroissantMiner: Automated Extraction and Validation of Croissant Metadata for ML Datasets
Berke Arda, Ahmetcan Yavuz, Paul Gerry +7
cs.CLcs.AIcs.DLarXiv:2610.07132v12026
QF3: Fast Flow RL with Filtered Q-Gradients
Chung Min Kim, Brent Yi, David McAllister +7
cs.ROcs.LGarXiv:2610.08789v12026
An Analysis of Linear Time Series Forecasting Models
William Toner, Luke Darlow
cs.LGarXiv:2403.14587v22024
Debiasing Evaluations That are Biased by Evaluations
Jingyan Wang, Ivan Stelmakh, Yuting Wei +1
stat.MLcs.ITcs.LGarXiv:2012.00714v12020
PROOF-Gen: From Optimized Data to Better Distillation
Anh Ta, Junjie Zhu, Shahin Shayandeh
cs.AIcs.LGarXiv:2608.23911v12026
Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data
Santiago Silva, Boris Gutman, Eduardo Romero +3
stat.MLcs.LGq-bio.NCarXiv:1810.08553v42018
Machine Unlearning via Algorithmic Stability
Enayat Ullah, Tung Mai, Anup Rao +2
cs.LGstat.MLarXiv:2102.13179v12021
Human-LLM Collaborative Feature Engineering for Tabular Data
Zhuoyan Li, Aditya Bansal, Jinzhao Li +8
cs.LGcs.CLcs.HCarXiv:2601.21060v12026
Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe
Wenjin Hou, Shangpin Peng, Weinong Wang +13
cs.LGarXiv:2605.03677v22026
Instance-Adaptive Prompts as Context for Time-Series Foundation Models
Zehao Xiao, Shifeng Xie, Lei Zan +5
cs.LGarXiv:2609.34786v12026
Privacy for Free: How does Dataset Condensation Help Privacy?
Tian Dong, Bo Zhao, Lingjuan Lyu
cs.CRcs.LGarXiv:2206.00240v12022
Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation
Niels Mündler, Jingxuan He, Slobodan Jenko +1
cs.CLcs.AIcs.LGarXiv:2305.15852v32023
Statistical Benefits of Fine-Tuning from Pretrained Initialization in Diagonal Linear Networks
Alexandre Declèves, Etienne Boursier, Nicolas Flammarion
stat.MLcs.LGarXiv:2609.34756v12026
Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction-Reality Gaps
Jiaxin Zhang, Xiangyu Peng, Qinglin Chen +3
cs.LGcs.AIarXiv:2610.02740v12026
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
Jaideep Pathak, Shashank Subramanian, Peter Harrington +10
physics.ao-phcs.LGarXiv:2202.11214v12022
Learning Features of Music from Scratch
John Thickstun, Zaid Harchaoui, Sham Kakade
stat.MLcs.LGcs.SDarXiv:1611.09827v22016
Approximate Inference Turns Deep Networks into Gaussian Processes
Mohammad Emtiyaz Khan, Alexander Immer, Ehsan Abedi +1
stat.MLcs.AIcs.LGarXiv:1906.01930v32019
FedKD: Communication Efficient Federated Learning via Knowledge Distillation
Chuhan Wu, Fangzhao Wu, Lingjuan Lyu +2
cs.LGcs.CLarXiv:2108.13323v22021
Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research
Johan S. Obando-Ceron, Pablo Samuel Castro
cs.LGcs.AIarXiv:2011.14826v22020
At the Dawn of Generative AI Era: A Tutorial-cum-Survey on New Frontiers in 6G Wireless Intelligence
Abdulkadir Celik, Ahmed M. Eltawil
cs.NIcs.AIcs.LGarXiv:2402.18587v12024
An introduction to graphical tensor notation for mechanistic interpretability
Jordan K. Taylor
cs.LGcs.AIarXiv:2402.01790v12024
Unsupervised Speech Decomposition via Triple Information Bottleneck
Kaizhi Qian, Yang Zhang, Shiyu Chang +2
eess.AScs.LGcs.SDarXiv:2004.11284v62020
Coverage-centric Coreset Selection for High Pruning Rates
Haizhong Zheng, Rui Liu, Fan Lai +1
cs.LGcs.AIarXiv:2210.15809v22022
Anomaly Detection using One-Class Neural Networks
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
cs.LGcs.NEstat.MLarXiv:1802.06360v22018
Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
Tom Everitt, Marcus Hutter, Ramana Kumar +1
cs.AIcs.LGarXiv:1908.04734v52019
Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
Shigang Li, Torsten Hoefler
cs.DCcs.LGarXiv:2107.06925v52021
Learning Propagation Geometry from Message-Passing Feedback
Yingxu Wang, Kunyu Zhang, Xinwang Liu +4
cs.LGarXiv:2609.34711v12026
Linear Bandits under Exact Sliding-Window Constraints
Seyed Mohammad Hadi Hosseini, Yasin Abbasi-Yadkori, Sattar Vakili
cs.LGarXiv:2610.08745v12026
SAUSS: Stochastic Approximation with Unbiased Simulated Scores for Limited Dependent Variable Models
Sokbae Lee, Yuan Liao, Myung Hwan Seo +1
stat.MEcs.LGecon.EMarXiv:2608.25304v12026
Noisy but Valid: Robust Statistical Evaluation of LLMs with Imperfect Judges
Chen Feng, Minghe Shen, Ananth Balashankar +2
cs.LGcs.AIcs.CVarXiv:2601.20913v12026
APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music
Jaavid Aktar Husain, Dorien Herremans
cs.SDcs.AIcs.LGarXiv:2605.03395v22026
Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review
Ivan Stelmakh, Nihar B. Shah, Aarti Singh +1
cs.DLcs.LGstat.AParXiv:2011.14646v12020
Revisiting Visual Representation Enhancement of VLMs via Kernel Canonical Correlation Analysis
Peilin Yang, Xiaoyu Liu, Jian Sun +1
cs.CVcs.AIcs.LGarXiv:2610.02718v12026
Prescriptive Scaling Reveals the Evolution of Language Model Capabilities
Hanlin Zhang, Jikai Jin, Vasilis Syrgkanis +1
cs.LGcs.AIcs.CLarXiv:2602.15327v22026
Hologram Representation via Quadratic Phase Gaussian Splatting
Haolong Wang, Yicheng Zhan, Kaan Akşit +1
cs.GRcs.CVcs.LGarXiv:2609.11434v12026
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification
Youngseog Chung, Willie Neiswanger, Ian Char +1
cs.LGstat.MLarXiv:2011.09588v42020
Benign Overfitting under Heterogeneous Input Fusion
Houzhen Liu, Xiaobo Xia
cs.LGstat.MLarXiv:2610.09340v12026
Hybrid Linear Attention Done Right: Efficient Distillation and Effective Architectures for Extremely Long Contexts
Yingfa Chen, Zhen Leng Thai, Zihan Zhou +6
cs.CLcs.AIcs.LGarXiv:2601.22156v12026
Denoising Hierarchical Representations: Joint Continuous Diffusion for Language Modeling
Mathias Ollu, Nikos Komodakis
cs.CLcs.LGarXiv:2610.08738v12026

Machine Learning

Trust-Region Optimization for Smooth Potential-Interaction Energies in Wasserstein Space

Fast and accurate sentiment classification using an enhanced Naive Bayes model

Understanding Learned Reward Functions

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

Stream Recursion Model (SRM)

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data

Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs

Graph-Based Learning for Multi-Horizon Martian Atmospheric Forecasting

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

Scaling Laws For Scalable Oversight

How to Teach Large Multimodal Models New Skills

A Bayesian Mirror Architecture for Emergent Consciousness: Circular Hierarchies, Self-Manifolds, and Hybrid Event-Self Binding

VEX-Bench: Benchmarking Verification Complexity of LLM-Generated Misinformation

Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization

Representation Learning for Attributed Multiplex Heterogeneous Network

Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?

HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation

Adversary Resistant Deep Neural Networks with an Application to Malware Detection

QiYao-M: Multimodal Time Series Foundation Model with Role-Aware Modeling of Endogenous and Exogenous Modalities

Towards Out-Of-Distribution Generalization: A Survey

Scaling Vision Transformers

CroissantMiner: Automated Extraction and Validation of Croissant Metadata for ML Datasets

QF3: Fast Flow RL with Filtered Q-Gradients

An Analysis of Linear Time Series Forecasting Models

Debiasing Evaluations That are Biased by Evaluations

PROOF-Gen: From Optimized Data to Better Distillation

Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data

Machine Unlearning via Algorithmic Stability

Human-LLM Collaborative Feature Engineering for Tabular Data

Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe

Instance-Adaptive Prompts as Context for Time-Series Foundation Models

Privacy for Free: How does Dataset Condensation Help Privacy?

Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation

Statistical Benefits of Fine-Tuning from Pretrained Initialization in Diagonal Linear Networks

Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction-Reality Gaps

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Learning Features of Music from Scratch

Approximate Inference Turns Deep Networks into Gaussian Processes

FedKD: Communication Efficient Federated Learning via Knowledge Distillation

Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research

At the Dawn of Generative AI Era: A Tutorial-cum-Survey on New Frontiers in 6G Wireless Intelligence

An introduction to graphical tensor notation for mechanistic interpretability

Unsupervised Speech Decomposition via Triple Information Bottleneck

Coverage-centric Coreset Selection for High Pruning Rates

Anomaly Detection using One-Class Neural Networks

Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective

Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines

Learning Propagation Geometry from Message-Passing Feedback

Linear Bandits under Exact Sliding-Window Constraints

SAUSS: Stochastic Approximation with Unbiased Simulated Scores for Limited Dependent Variable Models

Noisy but Valid: Robust Statistical Evaluation of LLMs with Imperfect Judges

APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music

Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review

Revisiting Visual Representation Enhancement of VLMs via Kernel Canonical Correlation Analysis

Prescriptive Scaling Reveals the Evolution of Language Model Capabilities

Hologram Representation via Quadratic Phase Gaussian Splatting

Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification

Benign Overfitting under Heterogeneous Input Fusion

Hybrid Linear Attention Done Right: Efficient Distillation and Effective Architectures for Extremely Long Contexts

Denoising Hierarchical Representations: Joint Continuous Diffusion for Language Modeling