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Every arXiv paper Paperlayer has summarized so far. 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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27,241 to 27,300 of 117,640

MeSH: Memory-as-State-Highways for Recursive Transformers
Chengting Yu, Xiaobo Shu, Yadao Wang +8
cs.LGcs.AIarXiv:2510.07739v22025
Emergence of polarization in networks of large language model agents
Jinghua Piao, Zhihong Lu, Chen Gao +5
cs.SIcs.CYarXiv:2501.05171v32025
Challenging common interpretability assumptions in feature attribution explanations
Jonathan Dinu, Jeffrey Bigham, J. Zico Kolter
cs.LGcs.CYcs.HCarXiv:2012.02748v12020
From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents
Xinyi Mou, Xuanwen Ding, Qi He +8
cs.CLcs.CYarXiv:2412.03563v12024
Simulating Social Media Using Large Language Models to Evaluate Alternative News Feed Algorithms
Petter Törnberg, Diliara Valeeva, Justus Uitermark +1
cs.SIcs.AIcs.MAarXiv:2310.05984v12023
AI Agents Alone Are Not (Yet) Sufficient for Social Simulation
Yiming Li, Dacheng Tao
cs.MAcs.AIcs.CEarXiv:2603.00113v22026
Can We Fix Social Media? Testing Prosocial Interventions using Generative Social Simulation
Maik Larooij, Petter Törnberg
cs.SIcs.CYarXiv:2508.03385v12025
Social Gym and SPaRTan: Benchmarking and Improving LLM Social Reasoning via Multi-Agent Game Tournaments
Keyu He, Xuhui Zhou, Maarten Sap
cs.CLcs.AIcs.MAarXiv:2608.09128v12026
Sotopia-RL: Reward Design for Social Intelligence
Haofei Yu, Zhengyang Qi, Yining Zhao +6
cs.CLarXiv:2508.03905v32025
Confidence on the Focal: Conformal Prediction with Selection-Conditional Coverage
Ying Jin, Zhimei Ren
stat.MEmath.STstat.MLarXiv:2403.03868v32024
Data-Prompt Co-Evolution: Growing Test Sets to Refine LLM Behavior
Minjae Lee, Minsuk Kahng
cs.HCcs.LGarXiv:2510.12728v32025
Synthesizing Public Opinions with LLMs: Role Creation, Impacts, and the Future to eDemorcacy
Rabimba Karanjai, Boris Shor, Amanda Austin +4
cs.CLcs.AIarXiv:2504.00241v12025
Investigating Human + Machine Complementarity for Recidivism Predictions
Sarah Tan, Julius Adebayo, Kori Inkpen +1
cs.LGcs.AIcs.CYarXiv:1808.09123v22018
Stochastic Backpropagation through Mixture Density Distributions
Alex Graves
cs.NEarXiv:1607.05690v12016
It Takes Two to Tango: Towards Theory of AI's Mind
Arjun Chandrasekaran, Deshraj Yadav, Prithvijit Chattopadhyay +2
cs.CVcs.AIcs.CLarXiv:1704.00717v22017
Batch Multivalid Conformal Prediction
Christopher Jung, Georgy Noarov, Ramya Ramalingam +1
cs.LGmath.STstat.THarXiv:2209.15145v12022
Stochastic gradient variational Bayes for gamma approximating distributions
David A. Knowles
stat.MLarXiv:1509.01631v12015
Graph Metanetworks for Processing Diverse Neural Architectures
Derek Lim, Haggai Maron, Marc T. Law +2
cs.LGcs.AIstat.MLarXiv:2312.04501v22023
Conformal Prediction With Conditional Guarantees
Isaac Gibbs, John J. Cherian, Emmanuel J. Candès
stat.MEarXiv:2305.12616v42023
Introspection: Accelerating Neural Network Training By Learning Weight Evolution
Abhishek Sinha, Mausoom Sarkar, Aahitagni Mukherjee +1
cs.LGarXiv:1704.04959v12017
Graph Neural Networks for Learning Equivariant Representations of Neural Networks
Miltiadis Kofinas, Boris Knyazev, Yan Zhang +5
cs.LGcs.AIstat.MLarXiv:2403.12143v32024
Statistical Inference for Fairness Auditing
John J. Cherian, Emmanuel J. Candès
stat.MEcs.CYcs.LGarXiv:2305.03712v22023
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning
Hangtao Zhang, Zeming Yao, Leo Yu Zhang +4
cs.LGcs.CRcs.DCarXiv:2304.10783v32023
Interrogating LLM design under a fair learning doctrine
Johnny Tian-Zheng Wei, Maggie Wang, Ameya Godbole +2
cs.CYcs.CLarXiv:2502.16290v12025
A First Look at the Performance Enhancement Potential of Fluid Reconfigurable Intelligent Surface
Abdelhamid Salem, Kai-Kit Wong, George Alexandropoulos +2
eess.SParXiv:2502.17116v12025
Wave-Tacotron: Spectrogram-free end-to-end text-to-speech synthesis
Ron J. Weiss, RJ Skerry-Ryan, Eric Battenberg +2
cs.CLcs.SDeess.ASarXiv:2011.03568v22020
InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling
Yuchun Miao, Sen Zhang, Liang Ding +3
cs.LGcs.AIarXiv:2402.09345v52024
Interactive Code Generation via Test-Driven User-Intent Formalization
Shuvendu K. Lahiri, Sarah Fakhoury, Aaditya Naik +8
cs.SEcs.LGcs.PLarXiv:2208.05950v22022
Crystal: Introspective Reasoners Reinforced with Self-Feedback
Jiacheng Liu, Ramakanth Pasunuru, Hannaneh Hajishirzi +2
cs.AIcs.CLcs.LGarXiv:2310.04921v22023
Cycles of Thought: Measuring LLM Confidence through Stable Explanations
Evan Becker, Stefano Soatto
cs.CLcs.LGarXiv:2406.03441v12024
Can Large Language Models Write Good Property-Based Tests?
Vasudev Vikram, Caroline Lemieux, Joshua Sunshine +1
cs.SEarXiv:2307.04346v22023
Higher criticism for detecting sparse heterogeneous mixtures
David Donoho, Jiashun Jin
math.STstat.THarXiv:math/0410072v12004
Active Learning of Abstract Plan Feasibility
Michael Noseworthy, Caris Moses, Isaiah Brand +4
cs.ROcs.AIarXiv:2107.00683v12021
The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking
Yuchun Miao, Sen Zhang, Liang Ding +3
cs.LGarXiv:2501.19358v32025
Large Language Models have Intrinsic Self-Correction Ability
Dancheng Liu, Amir Nassereldine, Ziming Yang +8
cs.CLcs.AIarXiv:2406.15673v22024
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion
Yash Bhalgat, Iro Laina, João F. Henriques +2
cs.CVcs.AIcs.LGarXiv:2306.04633v22023
CoverUp: Effective High Coverage Test Generation for Python
Juan Altmayer Pizzorno, Emery D. Berger
cs.SEcs.AIcs.LGarXiv:2403.16218v42024
KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints
Marko Mihajlovic, Aayush Bansal, Michael Zollhoefer +2
cs.CVarXiv:2205.04992v22022
Learning to Search for Dependencies
Kai-Wei Chang, He He, Hal Daumé III +1
cs.CLcs.LGarXiv:1503.05615v22015
InspireMusic: Integrating Super Resolution and Large Language Model for High-Fidelity Long-Form Music Generation
Chong Zhang, Yukun Ma, Qian Chen +12
cs.SDcs.AIcs.CLarXiv:2503.00084v12025
Semi-discrete Optimal Transport for Time-Varying Multi-Agent Coverage Control
Italo Napolitano, Mario di Bernardo
eess.SYcs.SYmath.OCarXiv:2601.21753v22026
QUITO-X: A New Perspective on Context Compression from the Information Bottleneck Theory
Yihang Wang, Xu Huang, Bowen Tian +6
cs.CLcs.AIarXiv:2408.10497v32024
Sowing the Wind, Reaping the Whirlwind: The Impact of Editing Language Models
Rima Hazra, Sayan Layek, Somnath Banerjee +1
cs.CLarXiv:2401.10647v52024
Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communities
Tianjie Ju, Yiting Wang, Xinbei Ma +7
cs.CLarXiv:2407.07791v22024
AffordanceLLM: Grounding Affordance from Vision Language Models
Shengyi Qian, Weifeng Chen, Min Bai +3
cs.CVcs.ROarXiv:2401.06341v22024
Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies
Linyong Nan, Yilun Zhao, Weijin Zou +5
cs.CLarXiv:2305.12586v12023
AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation
Ziyan Zhao, Ke Fan, He-Yang Xu +5
cs.ROcs.AIarXiv:2506.19269v22025
The expressive power of kth-order invariant graph networks
Floris Geerts
cs.LGmath.COstat.MLarXiv:2007.12035v12020
DP-MLM: Differentially Private Text Rewriting Using Masked Language Models
Stephen Meisenbacher, Maulik Chevli, Juraj Vladika +1
cs.CLarXiv:2407.00637v12024
"We Need a Woman in Music": Exploring Wikipedia's Values on Article Priority
Mo Houtti, Isaac Johnson, Joel Cepeda +3
cs.CYcs.HCarXiv:2208.08426v12022
Diffusion Large Language Models for Black-Box Optimization
Ye Yuan, Can, Chen +4
cs.CEcs.AIarXiv:2601.14446v12026
Quality change: norm or exception? Measurement, Analysis and Detection of Quality Change in Wikipedia
Paramita Das, Bhanu Prakash Reddy Guda, Sasi Bhusan Seelaboyina +2
cs.SIcs.IRarXiv:2111.01496v12021
The Risks, Benefits, and Consequences of Prepublication Moderation: Evidence from 17 Wikipedia Language Editions
Chau Tran, Kaylea Champion, Benjamin Mako Hill +1
cs.HCarXiv:2202.05548v22022
LLMs in Wikipedia: Investigating How LLMs Impact Participation in Knowledge Communities
Moyan Zhou, Soobin Cho, Loren Terveen
cs.HCarXiv:2509.07819v12025
Invisible Labor in Open Source Software Ecosystems
John Meluso, Amanda Casari, Katie McLaughlin +1
cs.SEarXiv:2401.06889v22024
Communication networks and group effectiveness: the case of English Wikipedia
Agnieszka Rychwalska, Szymon Talaga, Karolina Ziembowicz +1
cs.SIarXiv:2107.03506v12021
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks
Pascal Mattia Esser, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
cs.LGstat.MLarXiv:2112.03968v12021
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees
Haotian Ju, Dongyue Li, Hongyang R. Zhang
cs.LGcs.CVmath.STarXiv:2206.02659v62022
Generalization bounds for deep convolutional neural networks
Philip M. Long, Hanie Sedghi
cs.LGcs.AIcs.NEarXiv:1905.12600v62019
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks
Renjie Liao, Raquel Urtasun, Richard Zemel
cs.LGarXiv:2012.07690v12020

Every paper with a summary

MeSH: Memory-as-State-Highways for Recursive Transformers

Emergence of polarization in networks of large language model agents

Challenging common interpretability assumptions in feature attribution explanations

From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents

Simulating Social Media Using Large Language Models to Evaluate Alternative News Feed Algorithms

AI Agents Alone Are Not (Yet) Sufficient for Social Simulation

Can We Fix Social Media? Testing Prosocial Interventions using Generative Social Simulation

Social Gym and SPaRTan: Benchmarking and Improving LLM Social Reasoning via Multi-Agent Game Tournaments

Sotopia-RL: Reward Design for Social Intelligence

Confidence on the Focal: Conformal Prediction with Selection-Conditional Coverage

Data-Prompt Co-Evolution: Growing Test Sets to Refine LLM Behavior

Synthesizing Public Opinions with LLMs: Role Creation, Impacts, and the Future to eDemorcacy

Investigating Human + Machine Complementarity for Recidivism Predictions

Stochastic Backpropagation through Mixture Density Distributions

It Takes Two to Tango: Towards Theory of AI's Mind

Batch Multivalid Conformal Prediction

Stochastic gradient variational Bayes for gamma approximating distributions

Graph Metanetworks for Processing Diverse Neural Architectures

Conformal Prediction With Conditional Guarantees

Introspection: Accelerating Neural Network Training By Learning Weight Evolution

Graph Neural Networks for Learning Equivariant Representations of Neural Networks

Statistical Inference for Fairness Auditing

Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning

Interrogating LLM design under a fair learning doctrine

A First Look at the Performance Enhancement Potential of Fluid Reconfigurable Intelligent Surface

Wave-Tacotron: Spectrogram-free end-to-end text-to-speech synthesis

InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling

Interactive Code Generation via Test-Driven User-Intent Formalization

Crystal: Introspective Reasoners Reinforced with Self-Feedback

Cycles of Thought: Measuring LLM Confidence through Stable Explanations

Can Large Language Models Write Good Property-Based Tests?

Higher criticism for detecting sparse heterogeneous mixtures

Active Learning of Abstract Plan Feasibility

The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking

Large Language Models have Intrinsic Self-Correction Ability

Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion

CoverUp: Effective High Coverage Test Generation for Python

KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints

Learning to Search for Dependencies

InspireMusic: Integrating Super Resolution and Large Language Model for High-Fidelity Long-Form Music Generation

Semi-discrete Optimal Transport for Time-Varying Multi-Agent Coverage Control

QUITO-X: A New Perspective on Context Compression from the Information Bottleneck Theory

Sowing the Wind, Reaping the Whirlwind: The Impact of Editing Language Models

Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communities

AffordanceLLM: Grounding Affordance from Vision Language Models

Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies

AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation

The expressive power of kth-order invariant graph networks

DP-MLM: Differentially Private Text Rewriting Using Masked Language Models

"We Need a Woman in Music": Exploring Wikipedia's Values on Article Priority

Diffusion Large Language Models for Black-Box Optimization

Quality change: norm or exception? Measurement, Analysis and Detection of Quality Change in Wikipedia

The Risks, Benefits, and Consequences of Prepublication Moderation: Evidence from 17 Wikipedia Language Editions

LLMs in Wikipedia: Investigating How LLMs Impact Participation in Knowledge Communities

Invisible Labor in Open Source Software Ecosystems

Communication networks and group effectiveness: the case of English Wikipedia

Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks

Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees

Generalization bounds for deep convolutional neural networks

A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks