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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17,161 to 17,220 of 20,199

ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks
Xiaohan Ding, Yuchen Guo, Guiguang Ding +1
cs.CVcs.LGcs.NEarXiv:1908.03930v32019
Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling
Diego Marcheggiani, Ivan Titov
cs.CLcs.LGarXiv:1703.04826v42017
Test-Time Training with KV Binding Is Secretly Linear Attention
Junchen Liu, Sven Elflein, Or Litany +2
cs.LGcs.AIcs.CVarXiv:2602.21204v42026
Aletheia tackles FirstProof autonomously
Tony Feng, Junehyuk Jung, Sang-hyun Kim +14
cs.AIcs.CLcs.LGarXiv:2602.21201v32026
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar, Peyton Greenside, Anna Shcherbina +1
cs.LGcs.CVcs.NEarXiv:1605.01713v32016
Speaker Recognition from Raw Waveform with SincNet
Mirco Ravanelli, Yoshua Bengio
eess.AScs.LGcs.SDarXiv:1808.00158v32018
Topic Modeling in Embedding Spaces
Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei
cs.IRcs.CLcs.LGarXiv:1907.04907v12019
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac +12
cs.LGcs.CLcs.CVarXiv:2107.14795v32021
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
Xue Bin Peng, Aviral Kumar, Grace Zhang +1
cs.LGstat.MLarXiv:1910.00177v32019
Spend Less, Reason Better: Budget-Aware Value Tree Search for LLM Agents
Yushu Li, Wenlong Deng, Jiajin Li +1
cs.LGcs.AIarXiv:2603.12634v12026
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang, Da Zheng, Zihao Ye +12
cs.LGstat.MLarXiv:1909.01315v22019
A Survey on Distributed Machine Learning
Joost Verbraeken, Matthijs Wolting, Jonathan Katzy +3
cs.LGcs.DCstat.MLarXiv:1912.09789v12019
Enhanced Artificial Neural Networks Using QHAdamW in Air Quality Forecasting
Mary Joy Daniel Vinas
cs.AIcs.ETcs.LGarXiv:2608.21463v12026
Joint Unsupervised Learning of Deep Representations and Image Clusters
Jianwei Yang, Devi Parikh, Dhruv Batra
cs.CVcs.LGarXiv:1604.03628v32016
Pay Attention to MLPs
Hanxiao Liu, Zihang Dai, David R. So +1
cs.LGcs.CLcs.CVarXiv:2105.08050v22021
Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring
Yossi Adi, Carsten Baum, Moustapha Cisse +2
cs.LGarXiv:1802.04633v32018
LRAgent: Efficient KV Cache Sharing for Multi-LoRA LLM Agents
Hyesung Jeon, Hyeongju Ha, Jae-Joon Kim
cs.LGarXiv:2602.01053v22026
Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso, Luca Cavalleri, Dominique Beaini +2
cs.LGcs.CVstat.MLarXiv:2004.05718v52020
PDE-Net: Learning PDEs from Data
Zichao Long, Yiping Lu, Xianzhong Ma +1
math.NAcs.LGcs.NEarXiv:1710.09668v22017
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
Pratik Chaudhari, Anna Choromanska, Stefano Soatto +6
cs.LGstat.MLarXiv:1611.01838v52016
Sparse Communication for Distributed Gradient Descent
Alham Fikri Aji, Kenneth Heafield
cs.CLcs.DCcs.LGarXiv:1704.05021v22017
How to train your MAML
Antreas Antoniou, Harrison Edwards, Amos Storkey
cs.LGstat.MLarXiv:1810.09502v32018
Learn Hard Problems During RL with Reference Guided Fine-tuning
Yangzhen Wu, Shanda Li, Zixin Wen +5
cs.LGcs.CLarXiv:2603.01223v22026
Representation Alignment for Just Image Transformers is not Easier than You Think
Jaeyo Shin, Jiwook Kim, Hyunjung Shim
cs.CVcs.LGarXiv:2603.14366v12026
Out-of-Distribution Detection with Deep Nearest Neighbors
Yiyou Sun, Yifei Ming, Xiaojin Zhu +1
cs.LGcs.CVarXiv:2204.06507v32022
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato +1
cs.NIcs.LGarXiv:1405.4463v22014
CauScale: Neural Causal Discovery at Scale
Bo Peng, Sirui Chen, Jiaguo Tian +2
cs.LGcs.AIstat.MLarXiv:2602.08629v22026
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
Elad Hoffer, Itay Hubara, Daniel Soudry
stat.MLcs.LGarXiv:1705.08741v22017
Point-E: A System for Generating 3D Point Clouds from Complex Prompts
Alex Nichol, Heewoo Jun, Prafulla Dhariwal +2
cs.CVcs.LGarXiv:2212.08751v12022
Task-CoEvolve: Efficient Harness Optimization via Adaptive Validation Task Selection
Atsuyuki Miyai, Kiyoharu Aizawa, Toshihiko Yamasaki
cs.CLcs.AIcs.LGarXiv:2608.20169v22026
Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review
Sergey Levine
cs.LGcs.AIcs.ROarXiv:1805.00909v32018
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems
Laura von Rueden, Sebastian Mayer, Katharina Beckh +11
stat.MLcs.AIcs.LGarXiv:1903.12394v32019
On the Expressive Power of Deep Neural Networks
Maithra Raghu, Ben Poole, Jon Kleinberg +2
stat.MLcs.AIcs.LGarXiv:1606.05336v62016
Towards Deep Neural Network Architectures Robust to Adversarial Examples
Shixiang Gu, Luca Rigazio
cs.LGcs.CVcs.NEarXiv:1412.5068v42014
Olaf-World: Orienting Latent Actions for Video World Modeling
Yuxin Jiang, Yuchao Gu, Ivor W. Tsang +1
cs.CVcs.AIcs.LGarXiv:2602.10104v22026
The State of Sparsity in Deep Neural Networks
Trevor Gale, Erich Elsen, Sara Hooker
cs.LGstat.MLarXiv:1902.09574v12019
AI Learning and Conceptual Transfer in the Game of Hidden Rules
Christo Mathew, Wentian Wang, Jacob Feldman +4
cs.AIcs.LGarXiv:2608.21372v12026
Do Deep Generative Models Know What They Don't Know?
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh +2
stat.MLcs.LGarXiv:1810.09136v32018
Diffusion Improves Graph Learning
Johannes Gasteiger, Stefan Weißenberger, Stephan Günnemann
cs.SIcs.AIcs.LGarXiv:1911.05485v62019
Touchalytics: On the Applicability of Touchscreen Input as a Behavioral Biometric for Continuous Authentication
Mario Frank, Ralf Biedert, Eugene Ma +2
cs.CRcs.LGarXiv:1207.6231v22012
Score-based Generative Modeling in Latent Space
Arash Vahdat, Karsten Kreis, Jan Kautz
stat.MLcs.LGarXiv:2106.05931v32021
Input Convex Neural Networks
Brandon Amos, Lei Xu, J. Zico Kolter
cs.LGmath.OCarXiv:1609.07152v32016
Reviewing Model Collapse and Countermeasures
Xihao Xie, Beichen Hu
cs.AIcs.LGarXiv:2608.21366v12026
Accurate Uncertainties for Deep Learning Using Calibrated Regression
Volodymyr Kuleshov, Nathan Fenner, Stefano Ermon
cs.LGstat.MLarXiv:1807.00263v12018
Federated Learning for Smart Healthcare: A Survey
Dinh C. Nguyen, Quoc-Viet Pham, Pubudu N. Pathirana +5
cs.LGeess.SParXiv:2111.08834v12021
Adversarial Attack on Graph Structured Data
Hanjun Dai, Hui Li, Tian Tian +4
cs.LGcs.CRcs.SIarXiv:1806.02371v12018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi, Paolo Frasconi, Saverio Salzo +2
stat.MLcs.LGarXiv:1806.04910v22018
Measuring Catastrophic Forgetting in Neural Networks
Ronald Kemker, Marc McClure, Angelina Abitino +2
cs.AIcs.CVcs.LGarXiv:1708.02072v42017
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
En Li, Liekang Zeng, Zhi Zhou +1
cs.NIcs.CVcs.DCarXiv:1910.05316v12019
Machine Learning Testing: Survey, Landscapes and Horizons
Jie M. Zhang, Mark Harman, Lei Ma +1
cs.LGcs.AIcs.SEarXiv:1906.10742v22019
Overcoming Exploration in Reinforcement Learning with Demonstrations
Ashvin Nair, Bob McGrew, Marcin Andrychowicz +2
cs.LGcs.AIcs.NEarXiv:1709.10089v22017
TIES-Merging: Resolving Interference When Merging Models
Prateek Yadav, Derek Tam, Leshem Choshen +2
cs.LGcs.AIcs.CLarXiv:2306.01708v22023
Arcee Trinity Large Technical Report
Varun Singh, Lucas Krauss, Sami Jaghouar +23
cs.LGcs.CLarXiv:2602.17004v12026
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition
Grégoire Montavon, Sebastian Bach, Alexander Binder +2
cs.LGstat.MLarXiv:1512.02479v12015
LIBERO-Para: A Diagnostic Benchmark and Metrics for Paraphrase Robustness in VLA Models
Chanyoung Kim, Minwoo Kim, Minseok Kang +2
cs.LGarXiv:2603.28301v12026
Asymmetric Loss For Multi-Label Classification
Emanuel Ben-Baruch, Tal Ridnik, Nadav Zamir +4
cs.CVcs.LGarXiv:2009.14119v42020
DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning
Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi +8
cs.LGcs.CVarXiv:2204.04799v22022
Gated Feedback Recurrent Neural Networks
Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho +1
cs.NEcs.LGstat.MLarXiv:1502.02367v42015
Towards Automated Kernel Generation in the Era of LLMs
Yang Yu, Peiyu Zang, Chi Hsu Tsai +11
cs.LGcs.CLarXiv:2601.15727v32026
Autoregressive Image Generation using Residual Quantization
Doyup Lee, Chiheon Kim, Saehoon Kim +2
cs.CVcs.LGarXiv:2203.01941v22022

Machine Learning

ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks

Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling

Test-Time Training with KV Binding Is Secretly Linear Attention

Aletheia tackles FirstProof autonomously

Not Just a Black Box: Learning Important Features Through Propagating Activation Differences

Speaker Recognition from Raw Waveform with SincNet

Topic Modeling in Embedding Spaces

Perceiver IO: A General Architecture for Structured Inputs & Outputs

Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Spend Less, Reason Better: Budget-Aware Value Tree Search for LLM Agents

Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

A Survey on Distributed Machine Learning

Enhanced Artificial Neural Networks Using QHAdamW in Air Quality Forecasting

Joint Unsupervised Learning of Deep Representations and Image Clusters

Pay Attention to MLPs

Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring

LRAgent: Efficient KV Cache Sharing for Multi-LoRA LLM Agents

Principal Neighbourhood Aggregation for Graph Nets

PDE-Net: Learning PDEs from Data

Entropy-SGD: Biasing Gradient Descent Into Wide Valleys

Sparse Communication for Distributed Gradient Descent

How to train your MAML

Learn Hard Problems During RL with Reference Guided Fine-tuning

Representation Alignment for Just Image Transformers is not Easier than You Think

Out-of-Distribution Detection with Deep Nearest Neighbors

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

CauScale: Neural Causal Discovery at Scale

Train longer, generalize better: closing the generalization gap in large batch training of neural networks

Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Task-CoEvolve: Efficient Harness Optimization via Adaptive Validation Task Selection

Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems

On the Expressive Power of Deep Neural Networks

Towards Deep Neural Network Architectures Robust to Adversarial Examples

Olaf-World: Orienting Latent Actions for Video World Modeling

The State of Sparsity in Deep Neural Networks

AI Learning and Conceptual Transfer in the Game of Hidden Rules

Do Deep Generative Models Know What They Don't Know?

Diffusion Improves Graph Learning

Touchalytics: On the Applicability of Touchscreen Input as a Behavioral Biometric for Continuous Authentication

Score-based Generative Modeling in Latent Space

Input Convex Neural Networks

Reviewing Model Collapse and Countermeasures

Accurate Uncertainties for Deep Learning Using Calibrated Regression

Federated Learning for Smart Healthcare: A Survey

Adversarial Attack on Graph Structured Data

Bilevel Programming for Hyperparameter Optimization and Meta-Learning

Measuring Catastrophic Forgetting in Neural Networks

Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing

Machine Learning Testing: Survey, Landscapes and Horizons

Overcoming Exploration in Reinforcement Learning with Demonstrations

TIES-Merging: Resolving Interference When Merging Models

Arcee Trinity Large Technical Report

Explaining NonLinear Classification Decisions with Deep Taylor Decomposition

LIBERO-Para: A Diagnostic Benchmark and Metrics for Paraphrase Robustness in VLA Models

Asymmetric Loss For Multi-Label Classification

DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning

Gated Feedback Recurrent Neural Networks

Towards Automated Kernel Generation in the Era of LLMs

Autoregressive Image Generation using Residual Quantization