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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16,141 to 16,200 of 20,199

Faith and Fate: Limits of Transformers on Compositionality
Nouha Dziri, Ximing Lu, Melanie Sclar +13
cs.CLcs.AIcs.LGarXiv:2305.18654v32023
Learning-guided Kansa collocation for forward and inverse PDEs beyond linearity
Zheyuan Hu, Weitao Chen, Cengiz Öztireli +2
cs.CEcs.AIcs.LGarXiv:2602.07970v32026
Deep Anomaly Detection Using Geometric Transformations
Izhak Golan, Ran El-Yaniv
cs.LGstat.MLarXiv:1805.10917v22018
How2Everything: Mining the Web for How-To Procedures to Evaluate and Improve LLMs
Yapei Chang, Kyle Lo, Mohit Iyyer +1
cs.LGarXiv:2602.08808v12026
Data and its (dis)contents: A survey of dataset development and use in machine learning research
Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender +2
cs.LGarXiv:2012.05345v12020
Contextual Transformer Networks for Visual Recognition
Yehao Li, Ting Yao, Yingwei Pan +1
cs.CVcs.AIcs.LGarXiv:2107.12292v12021
How Much Reasoning Do Retrieval-Augmented Models Add beyond LLMs? A Benchmarking Framework for Multi-Hop Inference over Hybrid Knowledge
Junhong Lin, Bing Zhang, Song Wang +4
cs.LGarXiv:2602.10210v12026
FedPS: Federated data Preprocessing via aggregated Statistics
Xuefeng Xu, Graham Cormode
cs.LGcs.AIarXiv:2602.10870v12026
An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks
Brian Kenji Iwana, Seiichi Uchida
cs.LGstat.MLarXiv:2007.15951v42020
Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana +2
q-bio.BMcs.LGstat.MLarXiv:2009.01411v32020
Improving the Robustness of Deep Neural Networks via Stability Training
Stephan Zheng, Yang Song, Thomas Leung +1
cs.CVcs.LGarXiv:1604.04326v12016
Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks
Hoo-Chang Shin, Neil A Tenenholtz, Jameson K Rogers +5
cs.CVcs.LGstat.MLarXiv:1807.10225v22018
Neural Variational Inference for Text Processing
Yishu Miao, Lei Yu, Phil Blunsom
cs.CLcs.LGstat.MLarXiv:1511.06038v42015
Real Image Denoising with Feature Attention
Saeed Anwar, Nick Barnes
cs.CVcs.LGarXiv:1904.07396v22019
SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning
Quenton Yeo, Zhaoge Bi, Linghan Huang +3
cs.LGarXiv:2608.24561v12026
Mitigating Sybils in Federated Learning Poisoning
Clement Fung, Chris J. M. Yoon, Ivan Beschastnikh
cs.LGcs.CRcs.DCarXiv:1808.04866v52018
STATe-of-Thoughts: Structured Action Templates for Tree-of-Thoughts
Zachary Bamberger, Till R. Saenger, Gilad Morad +3
cs.CLcs.LGarXiv:2602.14265v32026
Whom to Query for What: Adaptive Group Elicitation via Multi-Turn LLM Interactions
Ruomeng Ding, Tianwei Gao, Thomas P. Zollo +3
cs.LGcs.AIcs.CLarXiv:2602.14279v22026
PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction
Jiawei Jiang, Chengkai Han, Wayne Xin Zhao +1
cs.LGarXiv:2301.07945v32023
Learning with a Wasserstein Loss
Charlie Frogner, Chiyuan Zhang, Hossein Mobahi +2
cs.LGcs.CVstat.MLarXiv:1506.05439v32015
COMPOT: Calibration-Optimized Matrix Procrustes Orthogonalization for Transformers Compression
Denis Makhov, Dmitriy Shopkhoev, Magauiya Zhussip +3
cs.LGarXiv:2602.15200v12026
BEATs: Audio Pre-Training with Acoustic Tokenizers
Sanyuan Chen, Yu Wu, Chengyi Wang +4
eess.AScs.AIcs.CLarXiv:2212.09058v12022
Taming foundation model with invariance-oriented pre-training for broad-spectrum EEG analysis across signal-level, brain-state, and brain-health tasks
Yulong Dou, Han Wu, Guo Chen +3
cs.LGcs.AIarXiv:2608.24597v12026
Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning
Werner Zellinger, Thomas Grubinger, Edwin Lughofer +2
stat.MLcs.LGarXiv:1702.08811v32017
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
Behnam Neyshabur, Srinadh Bhojanapalli, Nathan Srebro
cs.LGarXiv:1707.09564v22017
MoTE: Mixture of Task Experts for Multi-Task Video Understanding
Muhammad Asad Ali, Umar Khan, Nadia Robertini +1
cs.CVcs.LGarXiv:2608.24763v12026
Physics-informed learning of governing equations from scarce data
Zhao Chen, Yang Liu, Hao Sun
cs.LGphysics.comp-phphysics.data-anarXiv:2005.03448v32020
Graph networks as learnable physics engines for inference and control
Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg +4
cs.LGcs.AIstat.MLarXiv:1806.01242v12018
Large Causal Models for Temporal Causal Discovery
Nikolaos Kougioulis, Nikolaos Gkorgkolis, MingXue Wang +4
cs.LGarXiv:2602.18662v32026
No One Size Fits All: QueryBandits for Hallucination Mitigation
Nicole Cho, William Watson, Alec Koppel +2
cs.CLcs.AIcs.LGarXiv:2602.20332v12026
On Causal and Anticausal Learning
Bernhard Schoelkopf, Dominik Janzing, Jonas Peters +3
cs.LGstat.MLarXiv:1206.6471v12012
Action Recognition using Visual Attention
Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov
cs.LGcs.CVarXiv:1511.04119v32015
Learning to Detect Language Model Training Data via Active Reconstruction
Junjie Oscar Yin, John X. Morris, Vitaly Shmatikov +2
cs.LGcs.AIcs.CLarXiv:2602.19020v12026
Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning
Chongwen Huang, Ronghong Mo, Chau Yuen
cs.ITcs.LGarXiv:2002.10072v12020
Steering Recurrent Reasoners at Inference Time with Readout Feedback
Shunsuke Kamiya, Masanori Koyama, Seongcheol Jeong +5
cs.LGarXiv:2608.24136v12026
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
Zongyi Li, Daniel Zhengyu Huang, Burigede Liu +1
cs.LGmath.NAarXiv:2207.05209v22022
MEG-to-MEG Transfer Learning and Cross-Task Speech/Silence Detection with Limited Data
Xabier de Zuazo, Vincenzo Verbeni, Eva Navas +3
cs.LGarXiv:2602.18253v12026
Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations
Sosuke Kobayashi
cs.CLcs.LGarXiv:1805.06201v12018
A Simple Convolutional Generative Network for Next Item Recommendation
Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis +2
cs.IRcs.LGstat.MLarXiv:1808.05163v42018
Communication-Inspired Tokenization for Structured Image Representations
Aram Davtyan, Yusuf Sahin, Yasaman Haghighi +4
cs.CVcs.AIcs.LGarXiv:2602.20731v12026
Segmented Continuous Optimization
Teymur Aghayev
eess.SPcs.LGarXiv:2602.20857v22026
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions
Oscar Li, Hao Liu, Chaofan Chen +1
cs.AIcs.LGstat.MLarXiv:1710.04806v22017
Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking
Ravi Ghadia, Maksim Abraham, Sergei Vorobyov +1
cs.LGcs.DCarXiv:2602.21196v22026
Small Language Models for Privacy-Preserving Clinical Information Extraction in Low-Resource Languages
Mohammadreza Ghaffarzadeh-Esfahani, Nahid Yousefian, Ebrahim Heidari-Farsani +4
cs.CLcs.AIcs.LGarXiv:2602.21374v12026
POMO: Policy Optimization with Multiple Optima for Reinforcement Learning
Yeong-Dae Kwon, Jinho Choo, Byoungjip Kim +3
cs.LGarXiv:2010.16011v32020
DER: Dynamically Expandable Representation for Class Incremental Learning
Shipeng Yan, Jiangwei Xie, Xuming He
cs.CVcs.LGarXiv:2103.16788v12021
Data Leakage Inflates Generalizability of Power Outage Prediction Models
Yamil Essus, Ranga Raju Vatsavai, Benjamin Rachunok
cs.LGarXiv:2608.24665v12026
Transformers converge to invariant algorithmic cores
Joshua S. Schiffman
cs.LGcs.AIarXiv:2602.22600v22026
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT
Sheng Shen, Zhen Dong, Jiayu Ye +5
cs.CLcs.LGarXiv:1909.05840v22019
Challenges of Real-World Reinforcement Learning
Gabriel Dulac-Arnold, Daniel Mankowitz, Todd Hester
cs.LGcs.AIcs.ROarXiv:1904.12901v12019
Joint Distribution Optimal Transportation for Domain Adaptation
Nicolas Courty, Rémi Flamary, Amaury Habrard +1
stat.MLcs.LGarXiv:1705.08848v22017
Causal Analysis for Time Series Foundation Models
Mathis Jander, Wouter van Heeswijk, Martijn Mes
cs.LGarXiv:2608.24303v12026
Variational Adversarial Active Learning
Samarth Sinha, Sayna Ebrahimi, Trevor Darrell
cs.LGcs.CVstat.MLarXiv:1904.00370v32019
The Variational Fair Autoencoder
Christos Louizos, Kevin Swersky, Yujia Li +2
stat.MLcs.LGarXiv:1511.00830v62015
Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation
Chenxing Wei, Hong Wang, Ying He +4
cs.AIcs.LGarXiv:2603.01375v12026
Detecting and Correcting for Label Shift with Black Box Predictors
Zachary C. Lipton, Yu-Xiang Wang, Alex Smola
cs.LGcs.AIcs.NEarXiv:1802.03916v32018
Predictability of El Niño from Delayed Observations
Francisco J. Beron-Vera
physics.ao-phcs.LGmath.DSarXiv:2608.24428v12026
Legal RAG Bench: an end-to-end benchmark for legal RAG
Abdur-Rahman Butler, Umar Butler
cs.CLcs.IRcs.LGarXiv:2603.01710v12026
On the Robustness of Interpretability Methods
David Alvarez-Melis, Tommi S. Jaakkola
cs.LGstat.MLarXiv:1806.08049v12018
Efficient Test-Time Model Adaptation without Forgetting
Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang +4
cs.LGarXiv:2204.02610v22022

Machine Learning

Faith and Fate: Limits of Transformers on Compositionality

Learning-guided Kansa collocation for forward and inverse PDEs beyond linearity

Deep Anomaly Detection Using Geometric Transformations

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

Data and its (dis)contents: A survey of dataset development and use in machine learning research

Contextual Transformer Networks for Visual Recognition

How Much Reasoning Do Retrieval-Augmented Models Add beyond LLMs? A Benchmarking Framework for Multi-Hop Inference over Hybrid Knowledge

FedPS: Federated data Preprocessing via aggregated Statistics

An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks

Learning from Protein Structure with Geometric Vector Perceptrons

Improving the Robustness of Deep Neural Networks via Stability Training

Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks

Neural Variational Inference for Text Processing

Real Image Denoising with Feature Attention

SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning

Mitigating Sybils in Federated Learning Poisoning

STATe-of-Thoughts: Structured Action Templates for Tree-of-Thoughts

Whom to Query for What: Adaptive Group Elicitation via Multi-Turn LLM Interactions

PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction

Learning with a Wasserstein Loss

COMPOT: Calibration-Optimized Matrix Procrustes Orthogonalization for Transformers Compression

BEATs: Audio Pre-Training with Acoustic Tokenizers

Taming foundation model with invariance-oriented pre-training for broad-spectrum EEG analysis across signal-level, brain-state, and brain-health tasks

Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning

A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks

MoTE: Mixture of Task Experts for Multi-Task Video Understanding

Physics-informed learning of governing equations from scarce data

Graph networks as learnable physics engines for inference and control

Large Causal Models for Temporal Causal Discovery

No One Size Fits All: QueryBandits for Hallucination Mitigation

On Causal and Anticausal Learning

Action Recognition using Visual Attention

Learning to Detect Language Model Training Data via Active Reconstruction

Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning

Steering Recurrent Reasoners at Inference Time with Readout Feedback

Fourier Neural Operator with Learned Deformations for PDEs on General Geometries

MEG-to-MEG Transfer Learning and Cross-Task Speech/Silence Detection with Limited Data

Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations

A Simple Convolutional Generative Network for Next Item Recommendation

Communication-Inspired Tokenization for Structured Image Representations

Segmented Continuous Optimization

Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions

Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking

Small Language Models for Privacy-Preserving Clinical Information Extraction in Low-Resource Languages

POMO: Policy Optimization with Multiple Optima for Reinforcement Learning

DER: Dynamically Expandable Representation for Class Incremental Learning

Data Leakage Inflates Generalizability of Power Outage Prediction Models

Transformers converge to invariant algorithmic cores

Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT

Challenges of Real-World Reinforcement Learning

Joint Distribution Optimal Transportation for Domain Adaptation

Causal Analysis for Time Series Foundation Models

Variational Adversarial Active Learning

The Variational Fair Autoencoder

Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation

Detecting and Correcting for Label Shift with Black Box Predictors

Predictability of El Niño from Delayed Observations

Legal RAG Bench: an end-to-end benchmark for legal RAG

On the Robustness of Interpretability Methods

Efficient Test-Time Model Adaptation without Forgetting