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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421 to 480 of 20,454

MuProp: Unbiased Backpropagation for Stochastic Neural Networks
Shixiang Gu, Sergey Levine, Ilya Sutskever +1
cs.LGarXiv:1511.05176v32015
Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits
Shogo Iwazaki
cs.LGarXiv:2502.19006v22025
Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark
Marc Hanussek, Matthias Blohm, Maximilien Kintz
cs.LGstat.MLarXiv:2009.01564v22020
Learning diverse attacks on large language models for robust red-teaming and safety tuning
Seanie Lee, Minsu Kim, Lynn Cherif +8
cs.CLcs.CRcs.LGarXiv:2405.18540v32024
Directed Diffusion: Direct Control of Object Placement through Attention Guidance
Wan-Duo Kurt Ma, J. P. Lewis, Avisek Lahiri +2
cs.CVcs.GRcs.LGarXiv:2302.13153v32023
Aggregated Momentum: Stability Through Passive Damping
James Lucas, Shengyang Sun, Richard Zemel +1
cs.LGcs.AImath.OCarXiv:1804.00325v32018
Attacking the Trusted Imagination: Oracle-Level Integrity Attacks on Imagine-then-Act World Models
Linghan Chen, Kaiyan Ji, Minyu Guo
cs.LGcs.AIcs.CRarXiv:2606.22966v12026
Self-Supervised Graph Representation Learning via Global Context Prediction
Zhen Peng, Yixiang Dong, Minnan Luo +2
cs.LGstat.MLarXiv:2003.01604v12020
Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation
Jannis Bulian, Christian Buck, Wojciech Gajewski +2
cs.CLcs.LGarXiv:2202.07654v22022
A theory of continuous generative flow networks
Salem Lahlou, Tristan Deleu, Pablo Lemos +6
cs.LGstat.MLarXiv:2301.12594v22023
Reparameterizable Subset Sampling via Continuous Relaxations
Sang Michael Xie, Stefano Ermon
cs.LGstat.MLarXiv:1901.10517v52019
MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models
Gongfan Fang, Hongxu Yin, Saurav Muralidharan +5
cs.AIcs.CLcs.LGarXiv:2409.17481v22024
Optimal and Adaptive Algorithms for Online Boosting
Alina Beygelzimer, Satyen Kale, Haipeng Luo
cs.LGarXiv:1502.02651v12015
Measuring In-Context Computation Complexity via Hidden State Prediction
Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber
cs.LGarXiv:2503.13431v12025
Image Generation Via Minimizing Fr\'echet Distance in Discriminator Feature Space
Khoa D. Doan, Saurav Manchanda, Fengjiao Wang +3
cs.CVcs.LGeess.IVarXiv:2003.11774v22020
A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Assaf Shmuel, Oren Glickman, Teddy Lazebnik
cs.LGcs.AIarXiv:2408.14817v12024
TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks
Ivan Rubachev, Nikolay Kartashev, Yury Gorishniy +1
cs.LGarXiv:2406.19380v42024
fev-bench: A Realistic Benchmark for Time Series Forecasting
Oleksandr Shchur, Abdul Fatir Ansari, Caner Turkmen +5
cs.LGarXiv:2509.26468v42025
A Closer Look at Deep Learning Methods on Tabular Datasets
Han-Jia Ye, Si-Yang Liu, Hao-Run Cai +2
cs.LGarXiv:2407.00956v42024
Unreflected Use of Tabular Data Repositories Can Undermine Research Quality
Andrej Tschalzev, Lennart Purucker, Stefan Lüdtke +3
cs.LGarXiv:2503.09159v12025
TetraJet-v2: Accurate NVFP4 Training for Large Language Models with Oscillation Suppression and Outlier Control
Yuxiang Chen, Yifan Liu, Xiaoming Xu +5
cs.LGcs.AIarXiv:2510.27527v32025
Distinguishing the Knowable from the Unknowable with Language Models
Gustaf Ahdritz, Tian Qin, Nikhil Vyas +2
cs.LGcs.AIcs.CLarXiv:2402.03563v22024
TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
Zhepei Wei, Xiao Yang, Kai Sun +12
cs.CLcs.AIcs.LGarXiv:2509.25760v22025
blob loss: instance imbalance aware loss functions for semantic segmentation
Florian Kofler, Suprosanna Shit, Ivan Ezhov +14
cs.CVcs.LGeess.IVarXiv:2205.08209v32022
Representation Learning for Grounded Spatial Reasoning
Michael Janner, Karthik Narasimhan, Regina Barzilay
cs.CLcs.AIcs.LGarXiv:1707.03938v22017
Agentic Reinforcement Learning with Observation-Calibrated Self-Distillation
Yi Yang, Cong Qin, Xiaodan Liu +8
cs.LGcs.AIcs.CLarXiv:2608.04788v12026
Scalable Second Order Optimization for Deep Learning
Rohan Anil, Vineet Gupta, Tomer Koren +2
cs.LGmath.OCstat.MLarXiv:2002.09018v22020
Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo
João Loula, Benjamin LeBrun, Li Du +12
cs.CLcs.AIcs.LGarXiv:2504.13139v22025
Is Private Learning Possible with Instance Encoding?
Nicholas Carlini, Samuel Deng, Sanjam Garg +6
cs.CRcs.CVcs.LGarXiv:2011.05315v22020
The Alignment Problem in Constrained Code Generation
Matteo Biagiola, Jahrim Gabriele Cesario, Luca Di Grazia +2
cs.SEcs.LGcs.PLarXiv:2606.21619v12026
CRUST-Bench: A Comprehensive Benchmark for C-to-safe-Rust Transpilation
Anirudh Khatry, Robert Zhang, Jia Pan +4
cs.SEcs.CLcs.LGarXiv:2504.15254v32025
Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation
Luca Beurer-Kellner, Marc Fischer, Martin Vechev
cs.LGcs.CLarXiv:2403.06988v12024
Explaining Question Answering Models through Text Generation
Veronica Latcinnik, Jonathan Berant
cs.CLcs.AIcs.LGarXiv:2004.05569v12020
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations
Bodhisattwa Prasad Majumder, Oana-Maria Camburu, Thomas Lukasiewicz +1
cs.CLcs.AIcs.LGarXiv:2106.13876v42021
Goal Driven Discovery of Distributional Differences via Language Descriptions
Ruiqi Zhong, Peter Zhang, Steve Li +3
cs.CLcs.AIcs.LGarXiv:2302.14233v22023
Sum-max Submodular Bandits
Stephen Pasteris, Alberto Rumi, Fabio Vitale +1
cs.LGarXiv:2311.05975v12023
A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings
Davide Buffelli, Fabio Vandin
cs.LGcs.AIarXiv:2012.06755v12020
Lossless Acceleration for Seq2seq Generation with Aggressive Decoding
Tao Ge, Heming Xia, Xin Sun +2
cs.CLcs.LGarXiv:2205.10350v12022
On the insufficiency of existing momentum schemes for Stochastic Optimization
Rahul Kidambi, Praneeth Netrapalli, Prateek Jain +1
cs.LGmath.OCstat.MLarXiv:1803.05591v22018
Evaluating Machine Unlearning via Epistemic Uncertainty
Alexander Becker, Thomas Liebig
cs.LGarXiv:2208.10836v22022
TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts
Yu-Hao Huang, Chang Xu, Yueying Wu +2
cs.LGcs.AIarXiv:2501.05403v12025
Reliable Graph Neural Networks via Robust Aggregation
Simon Geisler, Daniel Zügner, Stephan Günnemann
cs.LGstat.MLarXiv:2010.15651v12020
Efficient Online Data Mixing For Language Model Pre-Training
Alon Albalak, Liangming Pan, Colin Raffel +1
cs.CLcs.LGarXiv:2312.02406v22023
Language models scale reliably with over-training and on downstream tasks
Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar +22
cs.CLcs.LGarXiv:2403.08540v22024
GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering
Abdullah Hamdi, Luke Melas-Kyriazi, Jinjie Mai +5
cs.CVcs.GRcs.LGarXiv:2402.10128v22024
Pathways on the Image Manifold: Image Editing via Video Generation
Noam Rotstein, Gal Yona, Daniel Silver +3
cs.CVcs.AIcs.LGarXiv:2411.16819v42024
Model-Preserving Adaptive Rounding
Albert Tseng, Zhaofeng Sun, Christopher De Sa
cs.LGcs.AIarXiv:2505.22988v32025
AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning
Jianguo Zhang, Tian Lan, Rithesh Murthy +15
cs.AIcs.CLcs.LGarXiv:2402.15506v42024
Collaborative Unsupervised Visual Representation Learning from Decentralized Data
Weiming Zhuang, Xin Gan, Yonggang Wen +2
cs.DCcs.AIcs.CVarXiv:2108.06492v12021
FAHT: An Adaptive Fairness-aware Decision Tree Classifier
Wenbin Zhang, Eirini Ntoutsi
cs.LGcs.AIstat.MLarXiv:1907.07237v12019
DiscoGen: Procedural Generation of Algorithm Discovery Tasks in Machine Learning
Alexander D. Goldie, Zilin Wang, Adrian Hayler +17
cs.LGcs.AIarXiv:2603.17863v22026
All SMILES Variational Autoencoder
Zaccary Alperstein, Artem Cherkasov, Jason Tyler Rolfe
cs.LGstat.MLarXiv:1905.13343v22019
Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
Zijian Guo, Weichao Zhou, Wenchao Li
cs.LGcs.AIarXiv:2402.17217v22024
DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging
Matteo Pagliardini, Amirkeivan Mohtashami, Francois Fleuret +1
cs.CLcs.LGarXiv:2402.02622v22024
Training a Generally Curious Agent
Fahim Tajwar, Yiding Jiang, Abitha Thankaraj +4
cs.LGcs.AIcs.CLarXiv:2502.17543v42025
Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications
Ethan Lin, Zhiyuan Peng, Yi Fang
cs.CLcs.AIcs.IRarXiv:2409.16605v12024
CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM
Minkyu Jeon, Rishwanth Raghu, Miro Astore +6
cs.CVcs.AIcs.CEarXiv:2408.05526v22024
Mixture of neural fields for heterogeneous reconstruction in cryo-EM
Axel Levy, Rishwanth Raghu, David Shustin +5
cs.LGarXiv:2412.09420v12024
RAP: Retrieval-Augmented Personalization for Multimodal Large Language Models
Haoran Hao, Jiaming Han, Changsheng Li +2
cs.CVcs.AIcs.CLarXiv:2410.13360v32024
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
Weichao Mao, Kaiqing Zhang, Qiaomin Xie +1
cs.AIcs.LGarXiv:2006.04672v22020

Machine Learning

MuProp: Unbiased Backpropagation for Stochastic Neural Networks

Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits

Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark

Learning diverse attacks on large language models for robust red-teaming and safety tuning

Directed Diffusion: Direct Control of Object Placement through Attention Guidance

Aggregated Momentum: Stability Through Passive Damping

Attacking the Trusted Imagination: Oracle-Level Integrity Attacks on Imagine-then-Act World Models

Self-Supervised Graph Representation Learning via Global Context Prediction

Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation

A theory of continuous generative flow networks

Reparameterizable Subset Sampling via Continuous Relaxations

MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models

Optimal and Adaptive Algorithms for Online Boosting

Measuring In-Context Computation Complexity via Hidden State Prediction

Image Generation Via Minimizing Fr\'echet Distance in Discriminator Feature Space

A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets

TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

fev-bench: A Realistic Benchmark for Time Series Forecasting

A Closer Look at Deep Learning Methods on Tabular Datasets

Unreflected Use of Tabular Data Repositories Can Undermine Research Quality

TetraJet-v2: Accurate NVFP4 Training for Large Language Models with Oscillation Suppression and Outlier Control

Distinguishing the Knowable from the Unknowable with Language Models

TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning

blob loss: instance imbalance aware loss functions for semantic segmentation

Representation Learning for Grounded Spatial Reasoning

Agentic Reinforcement Learning with Observation-Calibrated Self-Distillation

Scalable Second Order Optimization for Deep Learning

Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo

Is Private Learning Possible with Instance Encoding?

The Alignment Problem in Constrained Code Generation

CRUST-Bench: A Comprehensive Benchmark for C-to-safe-Rust Transpilation

Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation

Explaining Question Answering Models through Text Generation

Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations

Goal Driven Discovery of Distributional Differences via Language Descriptions

Sum-max Submodular Bandits

A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings

Lossless Acceleration for Seq2seq Generation with Aggressive Decoding

On the insufficiency of existing momentum schemes for Stochastic Optimization

Evaluating Machine Unlearning via Epistemic Uncertainty

TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts

Reliable Graph Neural Networks via Robust Aggregation

Efficient Online Data Mixing For Language Model Pre-Training

Language models scale reliably with over-training and on downstream tasks

GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering

Pathways on the Image Manifold: Image Editing via Video Generation

Model-Preserving Adaptive Rounding

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning

Collaborative Unsupervised Visual Representation Learning from Decentralized Data

FAHT: An Adaptive Fairness-aware Decision Tree Classifier

DiscoGen: Procedural Generation of Algorithm Discovery Tasks in Machine Learning

All SMILES Variational Autoencoder

Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning

DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging

Training a Generally Curious Agent

Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications

CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM

Mixture of neural fields for heterogeneous reconstruction in cryo-EM

RAP: Retrieval-Augmented Personalization for Multimodal Large Language Models

POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis