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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6,901 to 6,960 of 20,193

$π_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities
Physical Intelligence, Bo Ai, Ali Amin +85
cs.LGcs.ROarXiv:2604.15483v22026
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism
Qingyun Sun, Jianxin Li, Hao Peng +4
cs.LGcs.AIarXiv:2101.08170v32021
Cut Your Losses! Learning to Prune Paths Early for Efficient Parallel Reasoning
Jiaxi Bi, Tongxu Luo, Wenyu Du +2
cs.CLcs.LGarXiv:2604.16029v22026
On-the-fly Repulsion in the Contextual Space for Rich Diversity in Diffusion Transformers
Omer Dahary, Benaya Koren, Daniel Garibi +1
cs.CVcs.AIcs.GRarXiv:2603.28762v22026
DreamGen: Unlocking Generalization in Robot Learning through Video World Models
Joel Jang, Seonghyeon Ye, Zongyu Lin +25
cs.ROcs.AIcs.LGarXiv:2505.12705v22025
Live-SWE-agent: Can Software Engineering Agents Self-Evolve on the Fly?
Chunqiu Steven Xia, Zhe Wang, Yan Yang +2
cs.SEcs.AIcs.CLarXiv:2511.13646v32025
Time Limits in Reinforcement Learning
Fabio Pardo, Arash Tavakoli, Vitaly Levdik +1
cs.LGarXiv:1712.00378v42017
X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents
Salman Rahman, Liwei Jiang, James Shiffer +7
cs.CRcs.AIcs.CLarXiv:2504.13203v22025
PETS: A Principled Framework Towards Optimal Trajectory Allocation for Efficient Test-Time Self-Consistency
Zhangyi Liu, Huaizhi Qu, Xiaowei Yin +4
cs.LGcs.AIarXiv:2602.16745v22026
Towards Autonomous Mathematics Research
Tony Feng, Trieu H. Trinh, Garrett Bingham +25
cs.LGcs.AIcs.CLarXiv:2602.10177v32026
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices
Farah Fahim, Benjamin Hawks, Christian Herwig +27
cs.LGcs.ARphysics.ins-detarXiv:2103.05579v32021
Learning to Discover at Test Time
Mert Yuksekgonul, Daniel Koceja, Xinhao Li +8
cs.LGcs.AIarXiv:2601.16175v22026
$π_0$: A Vision-Language-Action Flow Model for General Robot Control
Kevin Black, Noah Brown, Danny Driess +21
cs.LGcs.ROarXiv:2410.24164v42024
History-Guided Video Diffusion
Kiwhan Song, Boyuan Chen, Max Simchowitz +3
cs.LGcs.CVarXiv:2502.06764v22025
Deep Learning with Lung Segmentation and Bone Shadow Exclusion Techniques for Chest X-Ray Analysis of Lung Cancer
Yu. Gordienko, Peng Gang, Jiang Hui +5
cs.LGcs.CVarXiv:1712.07632v12017
Fairness in Credit Scoring: Assessment, Implementation and Profit Implications
Nikita Kozodoi, Johannes Jacob, Stefan Lessmann
stat.MLcs.LGq-fin.RMarXiv:2103.01907v42021
Machine Learning for Large-Scale Optimization in 6G Wireless Networks
Yandong Shi, Lixiang Lian, Yuanming Shi +6
eess.SPcs.LGcs.NIarXiv:2301.03377v12023
ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation
Jiazheng Xu, Xiao Liu, Yuchen Wu +5
cs.CVcs.LGarXiv:2304.05977v42023
NeurASP: Embracing Neural Networks into Answer Set Programming
Zhun Yang, Adam Ishay, Joohyung Lee
cs.AIcs.LGcs.SCarXiv:2307.07700v12023
ClimaX: A foundation model for weather and climate
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor +2
cs.LGcs.AIarXiv:2301.10343v52023
Principled Reinforcement Learning with Human Feedback from Pairwise or $K$-wise Comparisons
Banghua Zhu, Jiantao Jiao, Michael I. Jordan
cs.LGcs.AIcs.HCarXiv:2301.11270v52023
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila +1
cs.CVcs.AIcs.LGarXiv:2206.00364v22022
Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting
Zezhi Shao, Zhao Zhang, Fei Wang +2
cs.LGarXiv:2208.05233v22022
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations
Michael Zhang, Nimit S. Sohoni, Hongyang R. Zhang +2
cs.LGarXiv:2203.01517v22022
Jury Learning: Integrating Dissenting Voices into Machine Learning Models
Mitchell L. Gordon, Michelle S. Lam, Joon Sung Park +4
cs.HCcs.AIcs.LGarXiv:2202.02950v12022
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks
Claudio Filipi Gonçalves dos Santos, João Paulo Papa
cs.CVcs.LGarXiv:2201.03299v12022
Graph Structure Learning with Variational Information Bottleneck
Qingyun Sun, Jianxin Li, Hao Peng +4
cs.LGcs.AIarXiv:2112.08903v12021
Exploring Sparse Autoencoders in Text-Based Causal Confounding Adjustment
Mian Zhong, Katherine A. Keith, Anjalie Field
cs.CLcs.LGarXiv:2609.01322v12026
Graph Neural Networks with Learnable Structural and Positional Representations
Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent +2
cs.LGarXiv:2110.07875v22021
Radial-Based Undersampling for Imbalanced Data Classification
Michał Koziarski
cs.LGstat.MLarXiv:1906.00452v22019
Revisiting Deep Learning Models for Tabular Data
Yury Gorishniy, Ivan Rubachev, Valentin Khrulkov +1
cs.LGarXiv:2106.11959v52021
Transfer Learning under High-dimensional Generalized Linear Models
Ye Tian, Yang Feng
stat.MLcs.LGstat.MEarXiv:2105.14328v42021
Applications of Deep Learning in Fundus Images: A Review
Tao Li, Wang Bo, Chunyu Hu +4
eess.IVcs.CVcs.LGarXiv:2101.09864v12021
The power of quantum neural networks
Amira Abbas, David Sutter, Christa Zoufal +3
quant-phcs.LGarXiv:2011.00027v12020
Equivalence of quantum barren plateaus to cost concentration and narrow gorges
Andrew Arrasmith, Zoë Holmes, M. Cerezo +1
quant-phcs.LGarXiv:2104.05868v22021
Graph Contrastive Learning with Adaptive Augmentation
Yanqiao Zhu, Yichen Xu, Feng Yu +3
cs.LGarXiv:2010.14945v32020
Ensemble Distillation for Robust Model Fusion in Federated Learning
Tao Lin, Lingjing Kong, Sebastian U. Stich +1
cs.LGstat.MLarXiv:2006.07242v32020
Rescaling Egocentric Vision
Dima Damen, Hazel Doughty, Giovanni Maria Farinella +8
cs.CVcs.LGarXiv:2006.13256v42020
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
Fabian B. Fuchs, Daniel E. Worrall, Volker Fischer +1
cs.LGstat.MLarXiv:2006.10503v32020
Understanding the Role of Training Regimes in Continual Learning
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu +1
cs.LGcs.NEstat.MLarXiv:2006.06958v12020
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Wenzheng Feng, Jie Zhang, Yuxiao Dong +6
cs.LGcs.SIstat.MLarXiv:2005.11079v42020
Predicting Many Properties of a Quantum System from Very Few Measurements
Hsin-Yuan Huang, Richard Kueng, John Preskill
quant-phcs.ITcs.LGarXiv:2002.08953v22020
Dota 2 with Large Scale Deep Reinforcement Learning
OpenAI, :, Christopher Berner +24
cs.LGstat.MLarXiv:1912.06680v12019
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
Kaidi Cao, Colin Wei, Adrien Gaidon +2
cs.LGcs.CVstat.MLarXiv:1906.07413v22019
Generalizing from a Few Examples: A Survey on Few-Shot Learning
Yaqing Wang, Quanming Yao, James Kwok +1
cs.LGcs.AIarXiv:1904.05046v32019
Regularized Learning for Domain Adaptation under Label Shifts
Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang +1
cs.LGstat.MLarXiv:1903.09734v12019
Uniform convergence may be unable to explain generalization in deep learning
Vaishnavh Nagarajan, J. Zico Kolter
cs.LGstat.MLarXiv:1902.04742v42019
Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication
Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
cs.LGcs.DCcs.DSarXiv:1902.00340v12019
Error Feedback Fixes SignSGD and other Gradient Compression Schemes
Sai Praneeth Karimireddy, Quentin Rebjock, Sebastian U. Stich +1
cs.LGmath.OCstat.MLarXiv:1901.09847v22019
Unsupervised Learning via Meta-Learning
Kyle Hsu, Sergey Levine, Chelsea Finn
cs.LGcs.AIcs.CVarXiv:1810.02334v62018
How Powerful are Graph Neural Networks?
Keyulu Xu, Weihua Hu, Jure Leskovec +1
cs.LGcs.CVstat.MLarXiv:1810.00826v32018
Actionable Recourse in Linear Classification
Berk Ustun, Alexander Spangher, Yang Liu
stat.MLcs.LGarXiv:1809.06514v22018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator
Cong Fang, Chris Junchi Li, Zhouchen Lin +1
math.OCcs.LGstat.MLarXiv:1807.01695v22018
Progressive Neural Architecture Search
Chenxi Liu, Barret Zoph, Maxim Neumann +7
cs.CVcs.LGstat.MLarXiv:1712.00559v32017
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models
Jean Barbier, Florent Krzakala, Nicolas Macris +2
cs.ITcond-mat.dis-nncs.AIarXiv:1708.03395v32017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez +1
stat.MLcs.LGarXiv:1610.08452v22016
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations
Itay Hubara, Matthieu Courbariaux, Daniel Soudry +2
cs.NEcs.LGarXiv:1609.07061v12016
Stealing Machine Learning Models via Prediction APIs
Florian Tramèr, Fan Zhang, Ari Juels +2
cs.CRcs.LGstat.MLarXiv:1609.02943v22016
Data Programming: Creating Large Training Sets, Quickly
Alexander Ratner, Christopher De Sa, Sen Wu +2
stat.MLcs.AIcs.LGarXiv:1605.07723v32016
Thought Anchors: Which LLM Reasoning Steps Matter?
Paul C. Bogdan, Uzay Macar, Neel Nanda +1
cs.LGcs.AIcs.CLarXiv:2506.19143v42025

Machine Learning

$π_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism

Cut Your Losses! Learning to Prune Paths Early for Efficient Parallel Reasoning

On-the-fly Repulsion in the Contextual Space for Rich Diversity in Diffusion Transformers

DreamGen: Unlocking Generalization in Robot Learning through Video World Models

Live-SWE-agent: Can Software Engineering Agents Self-Evolve on the Fly?

Time Limits in Reinforcement Learning

X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents

PETS: A Principled Framework Towards Optimal Trajectory Allocation for Efficient Test-Time Self-Consistency

Towards Autonomous Mathematics Research

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

Learning to Discover at Test Time

$π_0$: A Vision-Language-Action Flow Model for General Robot Control

History-Guided Video Diffusion

Deep Learning with Lung Segmentation and Bone Shadow Exclusion Techniques for Chest X-Ray Analysis of Lung Cancer

Fairness in Credit Scoring: Assessment, Implementation and Profit Implications

Machine Learning for Large-Scale Optimization in 6G Wireless Networks

ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation

NeurASP: Embracing Neural Networks into Answer Set Programming

ClimaX: A foundation model for weather and climate

Principled Reinforcement Learning with Human Feedback from Pairwise or $K$-wise Comparisons

Elucidating the Design Space of Diffusion-Based Generative Models

Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting

Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations

Jury Learning: Integrating Dissenting Voices into Machine Learning Models

Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks

Graph Structure Learning with Variational Information Bottleneck

Exploring Sparse Autoencoders in Text-Based Causal Confounding Adjustment

Graph Neural Networks with Learnable Structural and Positional Representations

Radial-Based Undersampling for Imbalanced Data Classification

Revisiting Deep Learning Models for Tabular Data

Transfer Learning under High-dimensional Generalized Linear Models

Applications of Deep Learning in Fundus Images: A Review

The power of quantum neural networks

Equivalence of quantum barren plateaus to cost concentration and narrow gorges

Graph Contrastive Learning with Adaptive Augmentation

Ensemble Distillation for Robust Model Fusion in Federated Learning

Rescaling Egocentric Vision

SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks

Understanding the Role of Training Regimes in Continual Learning

Graph Random Neural Network for Semi-Supervised Learning on Graphs

Predicting Many Properties of a Quantum System from Very Few Measurements

Dota 2 with Large Scale Deep Reinforcement Learning

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

Generalizing from a Few Examples: A Survey on Few-Shot Learning

Regularized Learning for Domain Adaptation under Label Shifts

Uniform convergence may be unable to explain generalization in deep learning

Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication

Error Feedback Fixes SignSGD and other Gradient Compression Schemes

Unsupervised Learning via Meta-Learning

How Powerful are Graph Neural Networks?

Actionable Recourse in Linear Classification

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator

Progressive Neural Architecture Search

Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Stealing Machine Learning Models via Prediction APIs

Data Programming: Creating Large Training Sets, Quickly

Thought Anchors: Which LLM Reasoning Steps Matter?