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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18,001 to 18,060 of 20,193

Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Nicolas Papernot, Martín Abadi, Úlfar Erlingsson +2
stat.MLcs.CRcs.LGarXiv:1610.05755v42016
CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images
Asif Iqbal Khan, Junaid Latief Shah, Mudasir Bhat
eess.IVcs.LGstat.MLarXiv:2004.04931v32020
Mass-Editing Memory in a Transformer
Kevin Meng, Arnab Sen Sharma, Alex Andonian +2
cs.CLcs.LGarXiv:2210.07229v22022
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
Sifan Wang, Hanwen Wang, Paris Perdikaris
cs.LGmath.NAstat.MLarXiv:2103.10974v12021
Knowledge Graph Convolutional Networks for Recommender Systems
Hongwei Wang, Miao Zhao, Xing Xie +2
cs.IRcs.LGstat.MLarXiv:1904.12575v12019
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Mikel Artetxe, Holger Schwenk
cs.CLcs.AIcs.LGarXiv:1812.10464v22018
Reinforcement Learning for Solving the Vehicle Routing Problem
Mohammadreza Nazari, Afshin Oroojlooy, Lawrence V. Snyder +1
cs.AIcs.LGstat.MLarXiv:1802.04240v22018
Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification
Yunsheng Shi, Zhengjie Huang, Shikun Feng +3
cs.LGstat.MLarXiv:2009.03509v52020
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
Junjie Hu, Sebastian Ruder, Aditya Siddhant +3
cs.CLcs.LGarXiv:2003.11080v52020
Deep Double Descent: Where Bigger Models and More Data Hurt
Preetum Nakkiran, Gal Kaplun, Yamini Bansal +3
cs.LGcs.CVcs.NEarXiv:1912.02292v12019
Stabilizing Efficient Reasoning with Step-Level Advantage Selection
Han Wang, Xiaodong Yu, Jialian Wu +4
cs.CLcs.LGarXiv:2604.24003v12026
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods
Dylan Slack, Sophie Hilgard, Emily Jia +2
cs.LGcs.AIstat.MLarXiv:1911.02508v22019
ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
Mohit Shridhar, Jesse Thomason, Daniel Gordon +5
cs.CVcs.AIcs.CLarXiv:1912.01734v22019
Activation Functions in Deep Learning: A Comprehensive Survey and Benchmark
Shiv Ram Dubey, Satish Kumar Singh, Bidyut Baran Chaudhuri
cs.LGcs.NEarXiv:2109.14545v32021
Neural 3D Mesh Renderer
Hiroharu Kato, Yoshitaka Ushiku, Tatsuya Harada
cs.CVcs.LGarXiv:1711.07566v12017
OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models
Yida Xue, Ningyu Zhang, Tingwei Wu +5
cs.MMcs.AIcs.CLarXiv:2605.00877v22026
Data Augmentation Generative Adversarial Networks
Antreas Antoniou, Amos Storkey, Harrison Edwards
stat.MLcs.CVcs.LGarXiv:1711.04340v32017
Wasserstein Auto-Encoders
Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly +1
stat.MLcs.LGarXiv:1711.01558v42017
AgentBench: Evaluating LLMs as Agents
Xiao Liu, Hao Yu, Hanchen Zhang +19
cs.AIcs.CLcs.LGarXiv:2308.03688v32023
S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization
Kun Zhou, Hui Wang, Wayne Xin Zhao +5
cs.IRcs.LGarXiv:2008.07873v12020
Composition-based Multi-Relational Graph Convolutional Networks
Shikhar Vashishth, Soumya Sanyal, Vikram Nitin +1
cs.LGstat.MLarXiv:1911.03082v22019
BARRED: Synthetic Training of Custom Policy Guardrails via Asymmetric Debate
Arnon Mazza, Elad Levi
cs.CLcs.AIcs.LGarXiv:2604.25203v12026
Symmetric Cross Entropy for Robust Learning with Noisy Labels
Yisen Wang, Xingjun Ma, Zaiyi Chen +3
cs.LGcs.CVstat.MLarXiv:1908.06112v12019
Better Models, Faster Training: Sigmoid Attention for single-cell Foundation Models
Vijay Sadashivaiah, Georgios Dasoulas, Judith Mueller +1
cs.LGq-bio.QMarXiv:2604.27124v12026
MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding
Aishwarya Kamath, Mannat Singh, Yann LeCun +3
cs.CVcs.CLcs.LGarXiv:2104.12763v22021
Scaling Laws for Reward Model Overoptimization
Leo Gao, John Schulman, Jacob Hilton
cs.LGstat.MLarXiv:2210.10760v12022
How to Explain Individual Classification Decisions
David Baehrens, Timon Schroeter, Stefan Harmeling +3
stat.MLcs.LGarXiv:0912.1128v12009
RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning
Yan Duan, John Schulman, Xi Chen +3
cs.AIcs.LGcs.NEarXiv:1611.02779v22016
Large Language Models Explore by Latent Distilling
Yuanhao Zeng, Ao Lu, Lufei Li +3
cs.CLcs.AIcs.LGarXiv:2604.24927v22026
Deep Learning: A Critical Appraisal
Gary Marcus
cs.AIcs.LGstat.MLarXiv:1801.00631v12018
Accelerating 3D Deep Learning with PyTorch3D
Nikhila Ravi, Jeremy Reizenstein, David Novotny +4
cs.CVcs.GRcs.LGarXiv:2007.08501v12020
Importance Estimation for Neural Network Pruning
Pavlo Molchanov, Arun Mallya, Stephen Tyree +2
cs.LGcs.CVstat.MLarXiv:1906.10771v12019
Prior-Aligned Data Cleaning for Tabular Foundation Models
Laure Berti-Equille
cs.LGcs.DBarXiv:2604.25154v12026
LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale
Tim Dettmers, Mike Lewis, Younes Belkada +1
cs.LGcs.AIarXiv:2208.07339v22022
Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery
Mingze Li, Yu Rong, Songyou Li +16
cs.LGcond-mat.mtrl-sciarXiv:2604.23758v32026
Structural-RNN: Deep Learning on Spatio-Temporal Graphs
Ashesh Jain, Amir R. Zamir, Silvio Savarese +1
cs.CVcs.LGcs.NEarXiv:1511.05298v32015
Relief-Based Feature Selection: Introduction and Review
Ryan J. Urbanowicz, Melissa Meeker, William LaCava +2
cs.DScs.LGstat.MLarXiv:1711.08421v22017
Turning the TIDE: Cross-Architecture Distillation for Diffusion Large Language Models
Gongbo Zhang, Wen Wang, Ye Tian +1
cs.CLcs.AIcs.LGarXiv:2604.26951v12026
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
Ahmed Salem, Yang Zhang, Mathias Humbert +3
cs.CRcs.AIcs.LGarXiv:1806.01246v22018
DKN: Deep Knowledge-Aware Network for News Recommendation
Hongwei Wang, Fuzheng Zhang, Xing Xie +1
stat.MLcs.LGarXiv:1801.08284v22018
Captum: A unified and generic model interpretability library for PyTorch
Narine Kokhlikyan, Vivek Miglani, Miguel Martin +8
cs.LGcs.AIstat.MLarXiv:2009.07896v12020
Manopt, a Matlab toolbox for optimization on manifolds
Nicolas Boumal, Bamdev Mishra, P. -A. Absil +1
cs.MScs.LGmath.OCarXiv:1308.5200v12013
Deep Learning for IoT Big Data and Streaming Analytics: A Survey
Mehdi Mohammadi, Ala Al-Fuqaha, Sameh Sorour +1
cs.NIcs.DBcs.LGarXiv:1712.04301v22017
End-to-End Attention-based Large Vocabulary Speech Recognition
Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk +2
cs.CLcs.AIcs.LGarXiv:1508.04395v22015
Neural Module Networks
Jacob Andreas, Marcus Rohrbach, Trevor Darrell +1
cs.CVcs.CLcs.LGarXiv:1511.02799v42015
Object-Centric Learning with Slot Attention
Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner +5
cs.LGcs.CVstat.MLarXiv:2006.15055v22020
Prototypical Contrastive Learning of Unsupervised Representations
Junnan Li, Pan Zhou, Caiming Xiong +1
cs.CVcs.LGarXiv:2005.04966v52020
Membership Inference Attacks From First Principles
Nicholas Carlini, Steve Chien, Milad Nasr +3
cs.CRcs.LGarXiv:2112.03570v22021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang, Xuhui Meng, George Em Karniadakis
stat.MLcs.LGarXiv:2003.06097v12020
The LAMBADA dataset: Word prediction requiring a broad discourse context
Denis Paperno, Germán Kruszewski, Angeliki Lazaridou +6
cs.CLcs.AIcs.LGarXiv:1606.06031v12016
A General Language Assistant as a Laboratory for Alignment
Amanda Askell, Yuntao Bai, Anna Chen +19
cs.CLcs.LGarXiv:2112.00861v32021
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small
Kevin Wang, Alexandre Variengien, Arthur Conmy +2
cs.LGcs.AIcs.CLarXiv:2211.00593v12022
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference
Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella +4
cs.CVcs.ARcs.LGarXiv:1612.07119v12016
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Nicholas Carlini, David Wagner
cs.LGcs.AIcs.CRarXiv:1801.01944v22018
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay
Leslie N. Smith
cs.LGcs.CVcs.NEarXiv:1803.09820v22018
Exploiting Shared Representations for Personalized Federated Learning
Liam Collins, Hamed Hassani, Aryan Mokhtari +1
cs.LGmath.OCarXiv:2102.07078v32021
Carbon Emissions and Large Neural Network Training
David Patterson, Joseph Gonzalez, Quoc Le +6
cs.LGcs.CYarXiv:2104.10350v32021
Bottleneck Transformers for Visual Recognition
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar +3
cs.CVcs.AIcs.LGarXiv:2101.11605v22021
FedMD: Heterogenous Federated Learning via Model Distillation
Daliang Li, Junpu Wang
cs.LGstat.MLarXiv:1910.03581v12019
BEGAN: Boundary Equilibrium Generative Adversarial Networks
David Berthelot, Thomas Schumm, Luke Metz
cs.LGstat.MLarXiv:1703.10717v42017

Machine Learning

Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images

Mass-Editing Memory in a Transformer

Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets

Knowledge Graph Convolutional Networks for Recommender Systems

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

Reinforcement Learning for Solving the Vehicle Routing Problem

Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification

XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization

Deep Double Descent: Where Bigger Models and More Data Hurt

Stabilizing Efficient Reasoning with Step-Level Advantage Selection

Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods

ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

Activation Functions in Deep Learning: A Comprehensive Survey and Benchmark

Neural 3D Mesh Renderer

OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models

Data Augmentation Generative Adversarial Networks

Wasserstein Auto-Encoders

AgentBench: Evaluating LLMs as Agents

S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization

Composition-based Multi-Relational Graph Convolutional Networks

BARRED: Synthetic Training of Custom Policy Guardrails via Asymmetric Debate

Symmetric Cross Entropy for Robust Learning with Noisy Labels

Better Models, Faster Training: Sigmoid Attention for single-cell Foundation Models

MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding

Scaling Laws for Reward Model Overoptimization

How to Explain Individual Classification Decisions

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

Large Language Models Explore by Latent Distilling

Deep Learning: A Critical Appraisal

Accelerating 3D Deep Learning with PyTorch3D

Importance Estimation for Neural Network Pruning

Prior-Aligned Data Cleaning for Tabular Foundation Models

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery

Structural-RNN: Deep Learning on Spatio-Temporal Graphs

Relief-Based Feature Selection: Introduction and Review

Turning the TIDE: Cross-Architecture Distillation for Diffusion Large Language Models

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

DKN: Deep Knowledge-Aware Network for News Recommendation

Captum: A unified and generic model interpretability library for PyTorch

Manopt, a Matlab toolbox for optimization on manifolds

Deep Learning for IoT Big Data and Streaming Analytics: A Survey

End-to-End Attention-based Large Vocabulary Speech Recognition

Neural Module Networks

Object-Centric Learning with Slot Attention

Prototypical Contrastive Learning of Unsupervised Representations

Membership Inference Attacks From First Principles

B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data

The LAMBADA dataset: Word prediction requiring a broad discourse context

A General Language Assistant as a Laboratory for Alignment

Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

FINN: A Framework for Fast, Scalable Binarized Neural Network Inference

Audio Adversarial Examples: Targeted Attacks on Speech-to-Text

A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay

Exploiting Shared Representations for Personalized Federated Learning

Carbon Emissions and Large Neural Network Training

Bottleneck Transformers for Visual Recognition

FedMD: Heterogenous Federated Learning via Model Distillation

BEGAN: Boundary Equilibrium Generative Adversarial Networks