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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19,921 to 19,948 of 19,948

Adaptive Protection for Evolutionary Feature Construction in Symbolic Regression with Application to Credit Classification
Hengzhe Zhang, Qi Chen, Bing Xue +3
cs.LGcs.NEarXiv:2608.14209v12026
Amplified Does Not Mean Predictive: Reasoning Behaviors in Thinking Models
Jean de Dieu Nyandwi, Leena Mathur, Yonatan Bisk +2
cs.CLcs.AIcs.CVarXiv:2608.13760v12026
TailBooster: A Dual-Layer Generative Framework for Extreme Value Augmentation with Operational Validity Enforcement
Karim Aly, Alexei Sharpanskykh, Jacco Hoekstra
cs.LGcs.AIarXiv:2608.11951v12026
AI Evaluation Should Work With Humans
Jan Kulveit, Gavin Leech, Tomáš Gavenčiak +1
cs.AIcs.LGarXiv:2608.13577v12026
Knowledge-guided Pattern Discovery via Coupled Tensor Factorizations
Gaute Johannessen, Geert Roelof van der Ploeg, Evrim Acar
cs.LGarXiv:2608.13234v12026
Improved Large Language Diffusion Models
Shen Nie, Qiyang Min, Shaoxuan Xu +7
cs.CLcs.AIcs.LGarXiv:2606.25331v12026
Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models
Kaiwen Zheng, Guande He, Min Zhao +7
cs.CVcs.LGarXiv:2606.25473v12026
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, Quoc V. Le
cs.CLcs.LGarXiv:1409.3215v32014
Sparse Orthogonal Regression Technique: A Spectral Framework for Equation Discovery, Approximation, and Integration
Sabin Roman, Ljupco Todorovski, Saso Dzeroski
cs.LGarXiv:2608.13504v12026
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver +4
cs.LGarXiv:1312.5602v12013
Vidu S1: A Real-Time Interactive Video Generation Model
Jintao Zhang, Kai Jiang, Jintao Chen +24
cs.CVcs.LGarXiv:2607.03118v22026
KVAE: Family of Tokenizers for Multimodal Generative Models
Andrey Shutkin, Denis Parkhomenko, Ivan Kirillov +11
cs.CVcs.LGcs.SDarXiv:2608.05798v12026
RoFormer: Enhanced Transformer with Rotary Position Embedding
Jianlin Su, Yu Lu, Shengfeng Pan +3
cs.CLcs.AIcs.LGarXiv:2104.09864v52021
Demystifying On-Policy Distillation: Roles, Pathologies, and Regulations
Rui Wang, Hongru Wang, Yi Chen +4
cs.CLcs.LGarXiv:2607.13399v12026
On the global feature importance for interpretable and trustworthy heat demand forecasting
Milan Zdravković
cs.LGeess.SYarXiv:2608.13039v12026
Forecast Collapse in Time-Series Foundation Models
Shu Wan, Miles Ma, Hank Zhu +4
cs.LGcs.AIcs.CEarXiv:2608.14106v12026
DanceOPD: On-Policy Generative Field Distillation
Wei Zhou, Xiongwei Zhu, Zelin Xu +8
cs.CVcs.CLcs.LGarXiv:2606.27377v22026
MobileMem: Learning from a Year of Mobile Experiences
Xinle Deng, Yida Xue, Xiangyuan Ru +14
cs.AIcs.CLcs.LGarXiv:2608.13606v12026
On-Policy Self-Distillation without Any Supervision
Yijiang Li, Bingyang Wang, Yijun Liang +3
cs.LGarXiv:2608.06296v22026
Distilling the Knowledge in a Neural Network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean
stat.MLcs.LGcs.NEarXiv:1503.02531v12015
SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe
Yifei Shen, Bo Li, Xinjie Zhang
cs.SEcs.AIcs.LGarXiv:2607.03451v12026
Generative Adversarial Networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza +5
stat.MLcs.LGarXiv:1406.2661v12014
MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training
Wenhan Ma, Jianyu Wei, Liang Zhao +10
cs.CLcs.LGarXiv:2606.30406v12026
Proximal Policy Optimization Algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal +2
cs.LGarXiv:1707.06347v22017
Intern-S2-Preview: Scientific Agentic Foundation Model
Lei Bai, Jiaqi Cao, Chiyu Chen +122
cs.LGcs.CLcs.CVarXiv:2608.13505v12026
AgenticDataBench: A Comprehensive Benchmark for Data Agents
Zhaoyan Sun, Shan Zhong, Daizhou Wen +10
cs.DBcs.AIcs.CLarXiv:2607.01647v12026
The State-Prediction Separation Hypothesis
Giovanni Monea, Nathan Godey, Kianté Brantley +1
cs.CLcs.AIcs.LGarXiv:2607.01218v12026
WARP: Weight-Space Analysis for Recovering Training Data Portfolios
Tzu-Heng Huang, Aditya Goyal, John Cooper +1
cs.LGarXiv:2607.01686v12026

Machine Learning

Adaptive Protection for Evolutionary Feature Construction in Symbolic Regression with Application to Credit Classification

Amplified Does Not Mean Predictive: Reasoning Behaviors in Thinking Models

TailBooster: A Dual-Layer Generative Framework for Extreme Value Augmentation with Operational Validity Enforcement

AI Evaluation Should Work With Humans

Knowledge-guided Pattern Discovery via Coupled Tensor Factorizations

Improved Large Language Diffusion Models

Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models

Sequence to Sequence Learning with Neural Networks

Sparse Orthogonal Regression Technique: A Spectral Framework for Equation Discovery, Approximation, and Integration

Playing Atari with Deep Reinforcement Learning

Vidu S1: A Real-Time Interactive Video Generation Model

KVAE: Family of Tokenizers for Multimodal Generative Models

RoFormer: Enhanced Transformer with Rotary Position Embedding

Demystifying On-Policy Distillation: Roles, Pathologies, and Regulations

On the global feature importance for interpretable and trustworthy heat demand forecasting

Forecast Collapse in Time-Series Foundation Models

DanceOPD: On-Policy Generative Field Distillation

MobileMem: Learning from a Year of Mobile Experiences

On-Policy Self-Distillation without Any Supervision

Distilling the Knowledge in a Neural Network

SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe

Generative Adversarial Networks

MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training

Proximal Policy Optimization Algorithms

Intern-S2-Preview: Scientific Agentic Foundation Model

AgenticDataBench: A Comprehensive Benchmark for Data Agents

The State-Prediction Separation Hypothesis

WARP: Weight-Space Analysis for Recovering Training Data Portfolios