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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26,881 to 26,940 of 33,132

Learning Continuous Control Policies by Stochastic Value Gradients
Nicolas Heess, Greg Wayne, David Silver +3
cs.LGcs.NEarXiv:1510.09142v12015
Aviary: training language agents on challenging scientific tasks
Siddharth Narayanan, James D. Braza, Ryan-Rhys Griffiths +8
cs.AIcs.CLcs.LGarXiv:2412.21154v12024
Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing
Anurag Ajay, Jiajun Wu, Nima Fazeli +4
cs.ROcs.LGarXiv:1808.03246v12018
Representation-Aligned Auxiliary Supervision for Language Model Adaptation
Kyuyoung Kim, Peiyao Sheng, Ashwin Hebbar +9
cs.CLcs.LGarXiv:2610.04098v12026
StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion
Takuhiro Kaneko, Hirokazu Kameoka, Kou Tanaka +1
cs.SDcs.LGeess.ASarXiv:1907.12279v22019
Robust Recovery of Subspace Structures by Low-Rank Representation
Guangcan Liu, Zhouchen Lin, Shuicheng Yan +3
cs.ITcs.CVcs.LGarXiv:1010.2955v62010
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)
Behnood Rasti, Danfeng Hong, Renlong Hang +4
cs.CVcs.LGeess.IVarXiv:2003.02822v42020
GUIDE: Generative Utility Inference and Decision Engine
Anagha Tiwari, Alexander G. Gray, Nick Feamster +3
cs.LGarXiv:2609.12137v12026
ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generation
Yunhong Min, Daehyeon Choi, Kyeongmin Yeo +2
cs.CVcs.LGarXiv:2503.22194v32025
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
Yinlam Chow, Guy Tennenholtz, Izzeddin Gur +7
cs.CLcs.AIcs.LGarXiv:2412.15287v22024
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir, Tong Zhang
cs.LGmath.OCstat.MLarXiv:1212.1824v22012
Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery
Peter Chen, Wotao Yin
cs.AIcs.CLcs.LGarXiv:2610.03872v12026
Sink-Aware Pruning for Diffusion Language Models
Aidar Myrzakhan, Tianyi Li, Bowei Guo +2
cs.CLcs.AIcs.LGarXiv:2602.17664v12026
Audio Super Resolution using Neural Networks
Volodymyr Kuleshov, S. Zayd Enam, Stefano Ermon
cs.SDcs.LGarXiv:1708.00853v12017
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
Xingchao Liu, Chengyue Gong, Qiang Liu
cs.LGarXiv:2209.03003v12022
Interactive Language: Talking to Robots in Real Time
Corey Lynch, Ayzaan Wahid, Jonathan Tompson +5
cs.ROcs.AIcs.LGarXiv:2210.06407v12022
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J. Maddison +2
cs.LGstat.MLarXiv:1703.07370v42017
Probability flow ODEs in score-based and reflected diffusion models
Rama CONT
stat.MLcs.LGmath.PRarXiv:2610.03846v12026
Lasso Screening Rules via Dual Polytope Projection
Jie Wang, Peter Wonka, Jieping Ye
cs.LGstat.MLarXiv:1211.3966v32012
Near Optimal Behavior via Approximate State Abstraction
David Abel, D. Ellis Hershkowitz, Michael L. Littman
cs.LGcs.AIarXiv:1701.04113v12017
Targeted Active Learning for Preference-Based Treatment Effects on Multivariate Outcomes
Lola Giordani, Mathieu Even, Chloé Geoffroy +3
stat.MLcs.LGstat.MEarXiv:2610.03824v12026
The Convergence of Sparsified Gradient Methods
Dan Alistarh, Torsten Hoefler, Mikael Johansson +3
cs.LGcs.DCstat.MLarXiv:1809.10505v12018
Foundations and Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions
Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency
cs.LGcs.AIcs.CLarXiv:2209.03430v22022
Curriculum Learning with GNN-based Reinforcement Learning for Job Shop Scheduling
Jayakrishnan K. Vasudevan, Jonathan Hoss, Noah Klarmann
cs.LGcs.AIarXiv:2609.28085v12026
Practical Obstacles to Deploying Active Learning
David Lowell, Zachary C. Lipton, Byron C. Wallace
cs.LGstat.MLarXiv:1807.04801v32018
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
Wen Sun, Arun Venkatraman, Geoffrey J. Gordon +2
cs.LGarXiv:1703.01030v12017
DOW-KE: Anchor-Free Multi-Layer Knowledge Editing via Direct End-to-End Weight Optimization
Ran Chen, Junbo Zhang, Qianli Zhou +2
cs.LGarXiv:2608.16932v12026
Semi-parametric Image Synthesis
Xiaojuan Qi, Qifeng Chen, Jiaya Jia +1
cs.CVcs.AIcs.GRarXiv:1804.10992v12018
Rethinking floating point for deep learning
Jeff Johnson
math.NAcs.LGarXiv:1811.01721v12018
Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing
Chen Liang, Mohammad Norouzi, Jonathan Berant +2
cs.LGcs.AIcs.CLarXiv:1807.02322v52018
Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks
Yuhang Li, Xin Dong, Wei Wang
cs.LGstat.MLarXiv:1909.13144v22019
From Mixing to Tearing: Graph Decomposition in Decentralized Optimization via Message Passing
Kuangyu Ding, Gesualdo Scutari
math.OCcs.LGarXiv:2610.03709v12026
Hierarchical Prototype Emergence in Modern Hopfield Models
Aditya Cowsik, Adithya Sriram
cond-mat.dis-nncs.AIcs.LGarXiv:2609.12079v12026
Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive
Arka Pal, Deep Karkhanis, Samuel Dooley +3
cs.CLcs.AIcs.LGarXiv:2402.13228v22024
Convolutional Conditional Neural Processes
Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong +3
stat.MLcs.LGarXiv:1910.13556v52019
Learning One-hidden-layer ReLU Networks via Gradient Descent
Xiao Zhang, Yaodong Yu, Lingxiao Wang +1
stat.MLcs.LGarXiv:1806.07808v12018
Marformer: A Transformer for Predicting Missing Data Distributions
Prabhav Singh, Xiheng Tom Wang, Haojun Shi +1
cs.LGstat.MEarXiv:2610.12379v12026
Unveiling the Depth-Performance Dilemma in Split-Federated Fine-tuning of LLMs
Hariharan Ramesh, Someshwaran Murugaiyan, Jyotikrishna Dass
cs.LGcs.CLcs.DCarXiv:2608.22188v12026
Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models
Rinon Gal, Moab Arar, Yuval Atzmon +3
cs.CVcs.GRcs.LGarXiv:2302.12228v32023
AudioLM: a Language Modeling Approach to Audio Generation
Zalán Borsos, Raphaël Marinier, Damien Vincent +8
cs.SDcs.LGeess.ASarXiv:2209.03143v22022
Learning Individually Inferred Communication for Multi-Agent Cooperation
Ziluo Ding, Tiejun Huang, Zongqing Lu
cs.LGcs.MAstat.MLarXiv:2006.06455v22020
Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models
Garrett Bernstein, Ryan McKenna, Tao Sun +3
cs.LGcs.CRstat.MLarXiv:1706.04646v12017
Reinforcement Learning from LLM Feedback to Counteract Goal Misgeneralization
Houda Nait El Barj, Theophile Sautory
cs.LGarXiv:2401.07181v12024
PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design
Runtian Wang, Renhao Xue, Baige Chen +1
cs.LGphysics.opticsarXiv:2605.26502v22026
A Geometric Theory of Robust Fairness Audits
Binita Maity
cs.LGarXiv:2608.24818v12026
Penalizing side effects using stepwise relative reachability
Victoria Krakovna, Laurent Orseau, Ramana Kumar +2
cs.LGcs.AIstat.MLarXiv:1806.01186v22018
The Elements of Differentiable Programming
Mathieu Blondel, Vincent Roulet
cs.LGcs.AIcs.PLarXiv:2403.14606v42024
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Şimşek, François Ged, Arthur Jacot +4
cs.LGarXiv:2105.12221v22021
Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation
Ryutaro Tanno, David G. T. Barrett, Andrew Sellergren +23
eess.IVcs.CLcs.CVarXiv:2311.18260v32023
Simple Guidance Mechanisms for Discrete Diffusion Models
Yair Schiff, Subham Sekhar Sahoo, Hao Phung +7
cs.LGarXiv:2412.10193v32024
Private PAC learning implies finite Littlestone dimension
Noga Alon, Roi Livni, Maryanthe Malliaris +1
cs.LGcs.AIcs.CRarXiv:1806.00949v32018
m-Set Adversarial Bandits with Winner Feedback
Nicolò Cesa-Bianchi, Matteo Papini
cs.LGstat.MLarXiv:2610.10128v12026
Normal-Form Correlation in Markov Games
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina +3
cs.GTcs.CCcs.DSarXiv:2610.03621v12026
Language Models with Conformal Factuality Guarantees
Christopher Mohri, Tatsunori Hashimoto
cs.LGcs.AIcs.CLarXiv:2402.10978v12024
Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph
Cong Fu, Chao Xiang, Changxu Wang +1
cs.LGarXiv:1707.00143v102017
Reinforcement Learning for Syndrome Extraction
John Zhuoyang Ye, Aarav Pabla, Jens Palsberg
cs.LGquant-pharXiv:2609.12020v12026
What Can a Gaussian Process Design Test
Ivan De Boi, Marnix Van Soom
cs.LGarXiv:2610.10122v12026
dna2vec: Consistent vector representations of variable-length k-mers
Patrick Ng
q-bio.QMcs.CLcs.LGarXiv:1701.06279v12017
QTrans: A Quantum Transformer for Sentiment Classification
Ren-Xin Zhao, Xinjie Huang, Yahong Liu +4
cs.LGarXiv:2609.12011v12026
Improving LLM Group Fairness on Tabular Data via In-Context Learning
Valeriia Cherepanova, Chia-Jung Lee, Nil-Jana Akpinar +4
cs.LGcs.AIarXiv:2412.04642v12024

Machine Learning

Learning Continuous Control Policies by Stochastic Value Gradients

Aviary: training language agents on challenging scientific tasks

Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing

Representation-Aligned Auxiliary Supervision for Language Model Adaptation

StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion

Robust Recovery of Subspace Structures by Low-Rank Representation

Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)

GUIDE: Generative Utility Inference and Decision Engine

ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generation

Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models

Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes

Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery

Sink-Aware Pruning for Diffusion Language Models

Audio Super Resolution using Neural Networks

Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Interactive Language: Talking to Robots in Real Time

REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models

Probability flow ODEs in score-based and reflected diffusion models

Lasso Screening Rules via Dual Polytope Projection

Near Optimal Behavior via Approximate State Abstraction

Targeted Active Learning for Preference-Based Treatment Effects on Multivariate Outcomes

The Convergence of Sparsified Gradient Methods

Foundations and Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions

Curriculum Learning with GNN-based Reinforcement Learning for Job Shop Scheduling

Practical Obstacles to Deploying Active Learning

Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction

DOW-KE: Anchor-Free Multi-Layer Knowledge Editing via Direct End-to-End Weight Optimization

Semi-parametric Image Synthesis

Rethinking floating point for deep learning

Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing

Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

From Mixing to Tearing: Graph Decomposition in Decentralized Optimization via Message Passing

Hierarchical Prototype Emergence in Modern Hopfield Models

Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive

Convolutional Conditional Neural Processes

Learning One-hidden-layer ReLU Networks via Gradient Descent

Marformer: A Transformer for Predicting Missing Data Distributions

Unveiling the Depth-Performance Dilemma in Split-Federated Fine-tuning of LLMs

Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models

AudioLM: a Language Modeling Approach to Audio Generation

Learning Individually Inferred Communication for Multi-Agent Cooperation

Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models

Reinforcement Learning from LLM Feedback to Counteract Goal Misgeneralization

PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design

A Geometric Theory of Robust Fairness Audits

Penalizing side effects using stepwise relative reachability

The Elements of Differentiable Programming

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation

Simple Guidance Mechanisms for Discrete Diffusion Models

Private PAC learning implies finite Littlestone dimension

m-Set Adversarial Bandits with Winner Feedback

Normal-Form Correlation in Markov Games

Language Models with Conformal Factuality Guarantees

Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph

Reinforcement Learning for Syndrome Extraction

What Can a Gaussian Process Design Test

dna2vec: Consistent vector representations of variable-length k-mers

QTrans: A Quantum Transformer for Sentiment Classification

Improving LLM Group Fairness on Tabular Data via In-Context Learning