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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17,581 to 17,640 of 20,192

Look, Listen and Learn
Relja Arandjelović, Andrew Zisserman
cs.CVcs.LGarXiv:1705.08168v22017
Unsupervised Cross-lingual Representation Learning for Speech Recognition
Alexis Conneau, Alexei Baevski, Ronan Collobert +2
cs.CLcs.LGcs.SDarXiv:2006.13979v22020
MM-Zero: Self-Evolving Multi-Model Vision Language Models From Zero Data
Zongxia Li, Hongyang Du, Chengsong Huang +8
cs.CVcs.LGarXiv:2603.09206v12026
Recent Advances in Open Set Recognition: A Survey
Chuanxing Geng, Sheng-jun Huang, Songcan Chen
cs.LGstat.MLarXiv:1811.08581v42018
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh +6
cs.CLcs.AIcs.LGarXiv:2305.02301v22023
Order Matters: Sequence to sequence for sets
Oriol Vinyals, Samy Bengio, Manjunath Kudlur
stat.MLcs.CLcs.LGarXiv:1511.06391v42015
Instruction-Following Evaluation for Large Language Models
Jeffrey Zhou, Tianjian Lu, Swaroop Mishra +5
cs.CLcs.AIcs.LGarXiv:2311.07911v12023
On Deep Multi-View Representation Learning: Objectives and Optimization
Weiran Wang, Raman Arora, Karen Livescu +1
cs.LGarXiv:1602.01024v12016
Gradient-based Hyperparameter Optimization through Reversible Learning
Dougal Maclaurin, David Duvenaud, Ryan P. Adams
stat.MLcs.LGarXiv:1502.03492v32015
PACED: Distillation and On-Policy Self-Distillation at the Frontier of Student Competence
Yuanda Xu, Hejian Sang, Zhengze Zhou +2
cs.AIcs.LGarXiv:2603.11178v32026
Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?
Pingyue Zhang, Zihan Huang, Yue Wang +11
cs.AIcs.CLcs.LGarXiv:2602.07055v12026
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
Chenxi Liu, Liang-Chieh Chen, Florian Schroff +4
cs.CVcs.LGarXiv:1901.02985v22019
Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction
Laila Rasmy, Yang Xiang, Ziqian Xie +2
cs.CLcs.LGcs.NEarXiv:2005.12833v12020
On Variational Bounds of Mutual Information
Ben Poole, Sherjil Ozair, Aaron van den Oord +2
cs.LGstat.MLarXiv:1905.06922v12019
Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
Haowen Xu, Wenxiao Chen, Nengwen Zhao +10
cs.LGstat.MLarXiv:1802.03903v12018
Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications
Thanh Thi Nguyen, Ngoc Duy Nguyen, Saeid Nahavandi
cs.LGcs.AIcs.MAarXiv:1812.11794v22018
An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution
Rosanne Liu, Joel Lehman, Piero Molino +4
cs.CVcs.LGstat.MLarXiv:1807.03247v22018
Progress & Compress: A scalable framework for continual learning
Jonathan Schwarz, Jelena Luketina, Wojciech M. Czarnecki +4
stat.MLcs.LGarXiv:1805.06370v22018
A Survey of Machine Learning for Big Code and Naturalness
Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu +1
cs.SEcs.LGcs.PLarXiv:1709.06182v22017
Deep Learning vs. Traditional Computer Vision
Niall O' Mahony, Sean Campbell, Anderson Carvalho +5
cs.CVcs.LGarXiv:1910.13796v12019
Domain Generalization with MixStyle
Kaiyang Zhou, Yongxin Yang, Yu Qiao +1
cs.CVcs.LGarXiv:2104.02008v12021
Self-Hinting Language Models Enhance Reinforcement Learning
Baohao Liao, Hanze Dong, Xinxing Xu +2
cs.LGcs.AIcs.CLarXiv:2602.03143v12026
Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders
Amandeep Kumar, Vishal M. Patel
cs.LGcs.CVarXiv:2602.10099v22026
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks
Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg +2
cs.LGcs.CVcs.NEarXiv:1406.6909v22014
The Hidden Vulnerability of Distributed Learning in Byzantium
El Mahdi El Mhamdi, Rachid Guerraoui, Sébastien Rouault
stat.MLcs.CRcs.DCarXiv:1802.07927v22018
Unified Latents (UL): How to train your latents
Jonathan Heek, Emiel Hoogeboom, Thomas Mensink +1
cs.LGcs.CVarXiv:2602.17270v12026
Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning
Chi-Pin Huang, Yunze Man, Zhiding Yu +4
cs.CVcs.AIcs.LGarXiv:2601.09708v22026
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Zeyu Han, Chao Gao, Jinyang Liu +2
cs.LGarXiv:2403.14608v72024
COVID-19 Image Data Collection
Joseph Paul Cohen, Paul Morrison, Lan Dao
eess.IVcs.CVcs.LGarXiv:2003.11597v12020
Neural Spline Flows
Conor Durkan, Artur Bekasov, Iain Murray +1
stat.MLcs.LGarXiv:1906.04032v22019
Evaluating Protein Transfer Learning with TAPE
Roshan Rao, Nicholas Bhattacharya, Neil Thomas +5
cs.LGq-bio.BMstat.MLarXiv:1906.08230v12019
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization
Chelsea Finn, Sergey Levine, Pieter Abbeel
cs.LGcs.AIcs.ROarXiv:1603.00448v32016
Deep Complex Networks
Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang +7
cs.NEcs.LGarXiv:1705.09792v42017
VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models
Wenlong Huang, Chen Wang, Ruohan Zhang +3
cs.ROcs.AIcs.CLarXiv:2307.05973v22023
Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability
Shobhita Sundaram, John Quan, Ariel Kwiatkowski +3
cs.LGcs.CLarXiv:2601.18778v32026
MemTrapBench: Benchmarking Cognitive Traps in LLM Memory Use
Mengru Wang, Haozhe Luo, Zhenqian Xu +6
cs.AIcs.CLcs.CYarXiv:2608.20202v12026
AVO: Agentic Variation Operators for Autonomous Evolutionary Search
Terry Chen, Zhifan Ye, Bing Xu +20
cs.LGarXiv:2603.24517v12026
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
Bernd Bischl, Martin Binder, Michel Lang +9
stat.MLcs.LGarXiv:2107.05847v32021
Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale
Yicheng Zou, Dongsheng Zhu, Lin Zhu +174
cs.LGcs.CLcs.CVarXiv:2603.25040v22026
MetaClaw: Just Talk -- An Agent That Meta-Learns and Evolves in the Wild
Peng Xia, Jianwen Chen, Xinyu Yang +10
cs.LGarXiv:2603.17187v12026
CSI: A Hybrid Deep Model for Fake News Detection
Natali Ruchansky, Sungyong Seo, Yan Liu
cs.LGcs.SIarXiv:1703.06959v42017
Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks
Srijan Kumar, Xikun Zhang, Jure Leskovec
cs.SIcs.CYcs.LGarXiv:1908.01207v12019
MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices
Zhiqing Sun, Hongkun Yu, Xiaodan Song +3
cs.CLcs.LGarXiv:2004.02984v22020
Power of data in quantum machine learning
Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni +4
quant-phcs.LGarXiv:2011.01938v22020
Automatic diagnosis of the 12-lead ECG using a deep neural network
Antônio H. Ribeiro, Manoel Horta Ribeiro, Gabriela M. M. Paixão +9
cs.LGeess.SPstat.MLarXiv:1904.01949v22019
Gradient based sample selection for online continual learning
Rahaf Aljundi, Min Lin, Baptiste Goujaud +1
cs.LGcs.AIcs.CVarXiv:1903.08671v52019
Multivariate LSTM-FCNs for Time Series Classification
Fazle Karim, Somshubra Majumdar, Houshang Darabi +1
cs.LGstat.MLarXiv:1801.04503v22018
Bilinear Attention Networks
Jin-Hwa Kim, Jaehyun Jun, Byoung-Tak Zhang
cs.CVcs.AIcs.CLarXiv:1805.07932v22018
MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks
Dan Li, Dacheng Chen, Lei Shi +3
cs.LGstat.MLarXiv:1901.04997v12019
Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations
Wei Liu, Jiawei Xu, Yingru Li +4
cs.LGcs.AIcs.CLarXiv:2602.05885v22026
Interpretation of Neural Networks is Fragile
Amirata Ghorbani, Abubakar Abid, James Zou
stat.MLcs.LGarXiv:1710.10547v22017
ContextBench: A Benchmark for Context Retrieval in Coding Agents
Han Li, Letian Zhu, Bohan Zhang +7
cs.LGarXiv:2602.05892v32026
Neural Thickets: Diverse Task Experts Are Dense Around Pretrained Weights
Yulu Gan, Phillip Isola
cs.LGcs.AIarXiv:2603.12228v12026
Unrolled Generative Adversarial Networks
Luke Metz, Ben Poole, David Pfau +1
cs.LGstat.MLarXiv:1611.02163v42016
Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation
Zhuolin Yang, Zihan Liu, Yang Chen +14
cs.CLcs.AIcs.LGarXiv:2603.19220v22026
COVIDX-Net: A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images
Ezz El-Din Hemdan, Marwa A. Shouman, Mohamed Esmail Karar
eess.IVcs.CVcs.LGarXiv:2003.11055v12020
Composer 2 Technical Report
Cursor Research, :, Aaron Chan +53
cs.SEcs.LGarXiv:2603.24477v22026
Generalized End-to-End Loss for Speaker Verification
Li Wan, Quan Wang, Alan Papir +1
eess.AScs.CLcs.LGarXiv:1710.10467v52017
Reinforcement-aware Knowledge Distillation for LLM Reasoning
Zhaoyang Zhang, Shuli Jiang, Yantao Shen +6
cs.LGcs.AIarXiv:2602.22495v32026
Rethinking the Trust Region in LLM Reinforcement Learning
Penghui Qi, Xiangxin Zhou, Zichen Liu +4
cs.LGcs.AIcs.CLarXiv:2602.04879v32026

Machine Learning

Look, Listen and Learn

Unsupervised Cross-lingual Representation Learning for Speech Recognition

MM-Zero: Self-Evolving Multi-Model Vision Language Models From Zero Data

Recent Advances in Open Set Recognition: A Survey

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes

Order Matters: Sequence to sequence for sets

Instruction-Following Evaluation for Large Language Models

On Deep Multi-View Representation Learning: Objectives and Optimization

Gradient-based Hyperparameter Optimization through Reversible Learning

PACED: Distillation and On-Policy Self-Distillation at the Frontier of Student Competence

Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction

On Variational Bounds of Mutual Information

Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications

An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

Progress & Compress: A scalable framework for continual learning

A Survey of Machine Learning for Big Code and Naturalness

Deep Learning vs. Traditional Computer Vision

Domain Generalization with MixStyle

Self-Hinting Language Models Enhance Reinforcement Learning

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks

The Hidden Vulnerability of Distributed Learning in Byzantium

Unified Latents (UL): How to train your latents

Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

COVID-19 Image Data Collection

Neural Spline Flows

Evaluating Protein Transfer Learning with TAPE

Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization

Deep Complex Networks

VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models

Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability

MemTrapBench: Benchmarking Cognitive Traps in LLM Memory Use

AVO: Agentic Variation Operators for Autonomous Evolutionary Search

Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges

Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale

MetaClaw: Just Talk -- An Agent That Meta-Learns and Evolves in the Wild

CSI: A Hybrid Deep Model for Fake News Detection

Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks

MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices

Power of data in quantum machine learning

Automatic diagnosis of the 12-lead ECG using a deep neural network

Gradient based sample selection for online continual learning

Multivariate LSTM-FCNs for Time Series Classification

Bilinear Attention Networks

MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Interpretation of Neural Networks is Fragile

ContextBench: A Benchmark for Context Retrieval in Coding Agents

Neural Thickets: Diverse Task Experts Are Dense Around Pretrained Weights

Unrolled Generative Adversarial Networks

Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation

COVIDX-Net: A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images

Composer 2 Technical Report

Generalized End-to-End Loss for Speaker Verification

Reinforcement-aware Knowledge Distillation for LLM Reasoning

Rethinking the Trust Region in LLM Reinforcement Learning