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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18,541 to 18,600 of 20,219

A Survey of Deep Learning Techniques for Autonomous Driving
Sorin Grigorescu, Bogdan Trasnea, Tiberiu Cocias +1
cs.LGcs.ROarXiv:1910.07738v22019
Generation and Comprehension of Unambiguous Object Descriptions
Junhua Mao, Jonathan Huang, Alexander Toshev +3
cs.CVcs.CLcs.LGarXiv:1511.02283v32015
Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal
Junlin Wang
cs.ROcs.LGarXiv:2605.27919v12026
Experience Replay for Continual Learning
David Rolnick, Arun Ahuja, Jonathan Schwarz +2
cs.LGcs.AIstat.MLarXiv:1811.11682v22018
Deep Metric Learning via Lifted Structured Feature Embedding
Hyun Oh Song, Yu Xiang, Stefanie Jegelka +1
cs.CVcs.LGarXiv:1511.06452v12015
Fully Convolutional Siamese Networks for Change Detection
Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch
cs.CVcs.LGarXiv:1810.08462v12018
Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization
Hao Jiang, Shurui Li, Tianpeng Bu +7
cs.LGarXiv:2605.28109v12026
Rethinking Memory as Continuously Evolving Connectivity
Jizhan Fang, Buqiang Xu, Zhixian Wang +12
cs.CLcs.AIcs.LGarXiv:2605.28773v12026
The Hamilton-Jacobi Theory of Deep Learning
Jose Marie Antonio Miñoza, Erika Fille T. Legara, Christopher P. Monterola
cs.LGcs.AImath.DSarXiv:2605.28983v22026
Training Very Deep Networks
Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber
cs.LGcs.NEarXiv:1507.06228v22015
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks, Mantas Mazeika, Thomas Dietterich
cs.LGcs.CLcs.CVarXiv:1812.04606v32018
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Niranjan Srinivas, Andreas Krause, Sham M. Kakade +1
cs.LGarXiv:0912.3995v42009
Sequence Level Training with Recurrent Neural Networks
Marc'Aurelio Ranzato, Sumit Chopra, Michael Auli +1
cs.LGcs.CLarXiv:1511.06732v72015
Augmenting Attention with Exponentially Decaying Memory Improves Query-Aware KV Sparsity
Xiuying Wei, Caglar Gulcehre
cs.LGarXiv:2605.28640v12026
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
Takayuki Nishio, Ryo Yonetani
cs.NIcs.LGarXiv:1804.08333v22018
Self-supervised Graph Learning for Recommendation
Jiancan Wu, Xiang Wang, Fuli Feng +4
cs.IRcs.LGarXiv:2010.10783v42020
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Iulian V. Serban, Alessandro Sordoni, Yoshua Bengio +2
cs.CLcs.AIcs.LGarXiv:1507.04808v32015
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Tri Dao, Albert Gu
cs.LGarXiv:2405.21060v12024
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
Guangxuan Xiao, Ji Lin, Mickael Seznec +3
cs.CLcs.AIcs.LGarXiv:2211.10438v72022
LaRA: Layer-wise Representation Analysis for Detecting Data Contamination in RL Post-Training
Minju Gwak, Minseo Kwak, Dongseok Lee +3
cs.LGcs.AIarXiv:2605.29888v12026
OmniRetrieval: Unified Retrieval across Heterogeneous Knowledge Sources
Jinheon Baek, Soyeong Jeong, Sangwoo Park +5
cs.CLcs.AIcs.IRarXiv:2605.29250v12026
Model-Contrastive Federated Learning
Qinbin Li, Bingsheng He, Dawn Song
cs.LGcs.AIcs.CVarXiv:2103.16257v12021
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection
Golnaz Ghiasi, Tsung-Yi Lin, Ruoming Pang +1
cs.CVcs.LGarXiv:1904.07392v12019
LEAF: A Benchmark for Federated Settings
Sebastian Caldas, Sai Meher Karthik Duddu, Peter Wu +5
cs.LGstat.MLarXiv:1812.01097v32018
CoHyDE: Iterative Co-Training of LLM Rewriter & Dense Encoder for Tool Retrieval
Vaishali Senthil, Ashutosh Hathidara, Sebastian Schreiber
cs.AIcs.IRcs.LGarXiv:2605.29271v12026
CoCa: Contrastive Captioners are Image-Text Foundation Models
Jiahui Yu, Zirui Wang, Vijay Vasudevan +3
cs.CVcs.LGcs.MMarXiv:2205.01917v22022
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
Tim Salimans, Jonathan Ho, Xi Chen +2
stat.MLcs.AIcs.LGarXiv:1703.03864v22017
NIPS 2016 Tutorial: Generative Adversarial Networks
Ian Goodfellow
cs.LGarXiv:1701.00160v42016
T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models
Chong Mou, Xintao Wang, Liangbin Xie +5
cs.CVcs.AIcs.LGarXiv:2302.08453v22023
LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis
Kewei Xu, Xiaoben Lu, Shuofei Qiao +4
cs.LGcs.AIcs.CLarXiv:2605.30434v12026
MAAT: Multi-phase Adapter-Aware Targeted Unlearning
Suryash Yagnik, Shubham Gaur, Saksham Thakur +3
cs.LGcs.CLarXiv:2605.30514v12026
ESPO: Early-Stopping Proximal Policy Optimization
Zihang Li, Rui Zhou, Yingcheng Shi +8
cs.LGcs.AIarXiv:2605.29860v12026
Benchmarking Deep Reinforcement Learning for Continuous Control
Yan Duan, Xi Chen, Rein Houthooft +2
cs.LGcs.AIcs.ROarXiv:1604.06778v32016
Generalizing to Unseen Domains: A Survey on Domain Generalization
Jindong Wang, Cuiling Lan, Chang Liu +6
cs.LGcs.AIcs.CVarXiv:2103.03097v72021
Multimodal Music Recommendation System using LLMs
Srikar Prabhas Kandagatla, Sreehitha R. Narayana, Chandana Magapu +6
cs.IRcs.AIcs.LGarXiv:2606.00125v12026
RayDer: Scalable Self-Supervised Novel View Synthesis from Real-World Video
Ulrich Prestel, Stefan Andreas Baumann, Nick Stracke +1
cs.CVcs.AIcs.LGarXiv:2605.31535v12026
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Sebastian Nowozin, Botond Cseke, Ryota Tomioka
stat.MLcs.LGstat.MEarXiv:1606.00709v12016
PubMedQA: A Dataset for Biomedical Research Question Answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu +2
cs.CLcs.LGq-bio.QMarXiv:1909.06146v12019
WebArena: A Realistic Web Environment for Building Autonomous Agents
Shuyan Zhou, Frank F. Xu, Hao Zhu +9
cs.AIcs.CLcs.LGarXiv:2307.13854v42023
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
Remi Denton, Wojciech Zaremba, Joan Bruna +2
cs.CVcs.LGarXiv:1404.0736v22014
Pitfalls of Graph Neural Network Evaluation
Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski +1
cs.LGcs.SIstat.MLarXiv:1811.05868v22018
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Pan Lu, Hritik Bansal, Tony Xia +7
cs.CVcs.AIcs.CLarXiv:2310.02255v32023
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
Sébastien Bubeck, Nicolò Cesa-Bianchi
cs.LGstat.MLarXiv:1204.5721v22012
Diffusion Posterior Sampling for General Noisy Inverse Problems
Hyungjin Chung, Jeongsol Kim, Michael T. Mccann +2
stat.MLcs.AIcs.CVarXiv:2209.14687v42022
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
Yi Ren, Chenxu Hu, Xu Tan +4
eess.AScs.CLcs.LGarXiv:2006.04558v82020
Multi-Task Learning as Multi-Objective Optimization
Ozan Sener, Vladlen Koltun
cs.LGstat.MLarXiv:1810.04650v22018
MPNet: Masked and Permuted Pre-training for Language Understanding
Kaitao Song, Xu Tan, Tao Qin +2
cs.CLcs.LGarXiv:2004.09297v22020
Access Sets Matter: Budgeting Expert Reads for Scalable Weight-Space Model Merging
Yuanyi Wang, Yanggan Gu, Su Lu +5
cs.LGeess.SYarXiv:2605.29489v12026
Frustratingly Easy Domain Adaptation
Hal Daumé
cs.LGcs.CLarXiv:0907.1815v12009
Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models
Jiacheng Lu, Haoyi Zhu, Sipei Yi +3
cs.CVcs.LGarXiv:2605.31158v32026
DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization
Jian Mu, Tianyi Lin, Chengwei Qin +2
cs.LGcs.CLarXiv:2605.31455v12026
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
Daya Guo, Qihao Zhu, Dejian Yang +10
cs.SEcs.CLcs.LGarXiv:2401.14196v22024
Graph Neural Networks in Recommender Systems: A Survey
Shiwen Wu, Fei Sun, Wentao Zhang +2
cs.IRcs.LGarXiv:2011.02260v42020
Deep Reinforcement Learning: An Overview
Yuxi Li
cs.LGarXiv:1701.07274v62017
Green AI
Roy Schwartz, Jesse Dodge, Noah A. Smith +1
cs.CYcs.CLcs.CVarXiv:1907.10597v32019
Neural Combinatorial Optimization with Reinforcement Learning
Irwan Bello, Hieu Pham, Quoc V. Le +2
cs.AIcs.LGstat.MLarXiv:1611.09940v32016
MLlib: Machine Learning in Apache Spark
Xiangrui Meng, Joseph Bradley, Burak Yavuz +13
cs.LGcs.DCcs.MSarXiv:1505.06807v12015
Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo +8
cs.ROcs.LGarXiv:2108.10470v22021
Deep Learning for Anomaly Detection: A Survey
Raghavendra Chalapathy, Sanjay Chawla
cs.LGstat.MLarXiv:1901.03407v22019
Root Mean Square Layer Normalization
Biao Zhang, Rico Sennrich
cs.LGcs.CLstat.MLarXiv:1910.07467v12019

Machine Learning

A Survey of Deep Learning Techniques for Autonomous Driving

Generation and Comprehension of Unambiguous Object Descriptions

Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal

Experience Replay for Continual Learning

Deep Metric Learning via Lifted Structured Feature Embedding

Fully Convolutional Siamese Networks for Change Detection

Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization

Rethinking Memory as Continuously Evolving Connectivity

The Hamilton-Jacobi Theory of Deep Learning

Training Very Deep Networks

Deep Anomaly Detection with Outlier Exposure

Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Sequence Level Training with Recurrent Neural Networks

Augmenting Attention with Exponentially Decaying Memory Improves Query-Aware KV Sparsity

Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge

Self-supervised Graph Learning for Recommendation

Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

LaRA: Layer-wise Representation Analysis for Detecting Data Contamination in RL Post-Training

OmniRetrieval: Unified Retrieval across Heterogeneous Knowledge Sources

Model-Contrastive Federated Learning

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection

LEAF: A Benchmark for Federated Settings

CoHyDE: Iterative Co-Training of LLM Rewriter & Dense Encoder for Tool Retrieval

CoCa: Contrastive Captioners are Image-Text Foundation Models

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

NIPS 2016 Tutorial: Generative Adversarial Networks

T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models

LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis

MAAT: Multi-phase Adapter-Aware Targeted Unlearning

ESPO: Early-Stopping Proximal Policy Optimization

Benchmarking Deep Reinforcement Learning for Continuous Control

Generalizing to Unseen Domains: A Survey on Domain Generalization

Multimodal Music Recommendation System using LLMs

RayDer: Scalable Self-Supervised Novel View Synthesis from Real-World Video

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

PubMedQA: A Dataset for Biomedical Research Question Answering

WebArena: A Realistic Web Environment for Building Autonomous Agents

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation

Pitfalls of Graph Neural Network Evaluation

MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems

Diffusion Posterior Sampling for General Noisy Inverse Problems

FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

Multi-Task Learning as Multi-Objective Optimization

MPNet: Masked and Permuted Pre-training for Language Understanding

Access Sets Matter: Budgeting Expert Reads for Scalable Weight-Space Model Merging

Frustratingly Easy Domain Adaptation

Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models

DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization

DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Graph Neural Networks in Recommender Systems: A Survey

Deep Reinforcement Learning: An Overview

Green AI

Neural Combinatorial Optimization with Reinforcement Learning

MLlib: Machine Learning in Apache Spark

Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning

Deep Learning for Anomaly Detection: A Survey

Root Mean Square Layer Normalization