Most Cited 2024 "pre-training data" Papers

Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection

Nils Palumbo, Yang Guo, Xi Wu et al.

Improving Context Understanding in Multimodal Large Language Models via Multimodal Composition Learning

Wei Li, Hehe Fan, Yongkang Wong et al.

Position: On the Possibilities of AI-Generated Text Detection

Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu et al.

Policy Evaluation for Variance in Average Reward Reinforcement Learning

Shubhada Agrawal, Prashanth L.A., Siva Maguluri

When is Transfer Learning Possible?

My Phan, Kianté Brantley, Stephanie Milani et al.

Generalization Analysis for Multi-Label Learning

Yi-Fan Zhang, Min-Ling Zhang

Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency

Yangfan Liu, JIAQI LYU, Xin Geng et al.

Position: Future Directions in the Theory of Graph Machine Learning

Christopher Morris, Fabrizio Frasca, Nadav Dym et al.

Evaluation of Trajectory Distribution Predictions with Energy Score

Novin Shahroudi, Mihkel Lepson, Meelis Kull

Active Ranking and Matchmaking, with Perfect Matchings

Hafedh El Ferchichi, Matthieu LERASLE, Vianney Perchet

Towards Neural Architecture Search through Hierarchical Generative Modeling

Lichuan Xiang, Łukasz Dudziak, Mohamed Abdelfattah et al.

Implicit Representations for Constrained Image Segmentation

Jan Philipp Schneider, Mishal Fatima, Jovita Lukasik et al.

Amortized Variational Deep Kernel Learning

Alan Matias, César Lincoln Mattos, Joao Paulo Gomes et al.

SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP

Subhojyoti Mukherjee, Josiah Hanna, Robert Nowak

Position: A Safe Harbor for AI Evaluation and Red Teaming

Shayne Longpre, Sayash Kapoor, Kevin Klyman et al.

Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination

Zhiyao Luo, Yangchen Pan, Peter Watkinson et al.

Graph Out-of-Distribution Detection Goes Neighborhood Shaping

Tianyi Bao, Qitian Wu, Zetian Jiang et al.

Position: On the Societal Impact of Open Foundation Models

Sayash Kapoor, Rishi Bommasani, Kevin Klyman et al.

Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition

Tong Wei, Zhen Mao, Zi-Hao Zhou et al.

Lightweight Image Super-Resolution via Flexible Meta Pruning

Yulun Zhang, Kai Zhang, Luc Van Gool et al.

Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning

Wenke Huang, Zekun Shi, Mang Ye et al.

Position: Open-Endedness is Essential for Artificial Superhuman Intelligence

Edward Hughes, Michael Dennis, Jack Parker-Holder et al.

Fundamental Limits of Distributed Covariance Matrix Estimation Under Communication Constraints

Mohammad Reza Rahmani, Mohammad Hossein Yassaee, Mohammad Ali Maddah Ali et al.

Faster Streaming and Scalable Algorithms for Finding Directed Dense Subgraphs in Large Graphs

Slobodan Mitrovic, Theodore Pan

Sign Rank Limitations for Inner Product Graph Decoders

Su Hyeong Lee, QINGQI ZHANG, Risi Kondor

Effect-Invariant Mechanisms for Policy Generalization

Sorawit Saengkyongam, Niklas Pfister, Predag Klasnja et al.

Position: Data-driven Discovery with Large Generative Models

Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal et al.

What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks

Ching-Yun (Irene) Ko, Pin-Yu Chen, Payel Das et al.

STELLA: Continual Audio-Video Pre-training with SpatioTemporal Localized Alignment

Jaewoo Lee, Jaehong Yoon, Wonjae Kim et al.

Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration

Gyusang Cho, Chan-Hyun Youn

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MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation

Bowen Tao, Xin-Chun Li, De-Chuan Zhan

Predicting Dose-Response Curves with Deep Neural Networks

Pedro A. Campana, Paul Prasse, Tobias Scheffer

ReLU Network with Width $d+\mathcal{O}(1)$ Can Achieve Optimal Approximation Rate

Chenghao Liu, Minghua Chen

Improved Dimensionality Dependence for Zeroth-Order Optimisation over Cross-Polytopes

Weijia Shao

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen et al.

Flexible Residual Binarization for Image Super-Resolution

Yulun Zhang, Haotong Qin, Zixiang Zhao et al.

Characterizing ResNet's Universal Approximation Capability

Chenghao Liu, Enming Liang, Minghua Chen

Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy

Lucas Spangher, Allen Wang, Andrew Maris et al.

Physics and Lie symmetry informed Gaussian processes

David Dalton, Dirk Husmeier, Hao Gao

Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback

Vincent Conitzer, Rachel Freedman, Jobstq Heitzig et al.

Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph

Yufei Kuang, Jie Wang, Yuyan Zhou et al.

Minimum Norm Interpolation Meets The Local Theory of Banach Spaces

Gil Kur, Pedro Abdalla, Pierre Bizeul et al.

Exploiting Human-AI Dependence for Learning to Defer

Zixi Wei, Yuzhou Cao, Lei Feng

AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training

Li Ding, Wen Fei, Yuyang Huang et al.

Contrastive Predict-and-Search for Mixed Integer Linear Programs

Taoan Huang, Aaron Ferber, Arman Zharmagambetov et al.

Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches

David Glukhov, Ilia Shumailov, Yarin Gal et al.

Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing

Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam et al.

Bifurcated Attention for Single-Context Large-Batch Sampling

Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda et al.

Breadth-First Exploration on Adaptive Grid for Reinforcement Learning

Youngsik Yoon, Gangbok Lee, Sungsoo Ahn et al.

Kepler codebook

Junrong Lian, Ziyue Dong, Pengxu Wei et al.

Augmenting Decision with Hypothesis in Reinforcement Learning

Nguyen Minh Quang, Hady Lauw

The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks

Songhua He, Periklis Papakonstantinou

Cell2Sentence: Teaching Large Language Models the Language of Biology

Daniel Levine, Syed Rizvi, Sacha Lévy et al.

Position: Social Environment Design Should be Further Developed for AI-based Policy-Making

Edwin Zhang, Sadie Zhao, Tonghan Wang et al.

Dynamic Metric Embedding into lp Space

Kiarash Banihashem, MohammadTaghi Hajiaghayi, Dariusz Kowalski et al.

Meta Evidential Transformer for Few-Shot Open-Set Recognition

Hitesh Sapkota, Krishna Neupane, Qi Yu

Editing Partially Observable Networks via Graph Diffusion Models

Puja Trivedi, Ryan A Rossi, David Arbour et al.

On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity

Junyi FAN, Yuxuan Han, Zijian Liu et al.

The Emergence of Reproducibility and Consistency in Diffusion Models

Huijie Zhang, Jinfan Zhou, Yifu Lu et al.

Accelerated Speculative Sampling Based on Tree Monte Carlo

Zhengmian Hu, Heng Huang

How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective

Keyan Miao, Konstantinos Gatsis

Position: Video as the New Language for Real-World Decision Making

Sherry Yang, Jacob C Walker, Jack Parker-Holder et al.

Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data

Kishan Panaganti, Adam Wierman, Eric Mazumdar

Position: Intent-aligned AI Systems Must Optimize for Agency Preservation

Catalin Mitelut, Benjamin Smith, Peter Vamplew

Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research

Riley Simmons-Edler, Ryan Badman, Shayne Longpre et al.

Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration

Xiong-Hui Chen, Junyin Ye, Hang Zhao et al.

Policy-conditioned Environment Models are More Generalizable

Ruifeng Chen, Xiong-Hui Chen, Yihao Sun et al.

SILVER: Single-loop variance reduction and application to federated learning

Kazusato Oko, Shunta Akiyama, Denny Wu et al.

Coresets for Multiple $\ell_p$ Regression

David Woodruff, Taisuke Yasuda

InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning

Zhe Huang, Xiaowei Yu, Dajiang Zhu et al.

Position: Will we run out of data? Limits of LLM scaling based on human-generated data

Pablo Villalobos, Anson Ho, Jaime Sevilla et al.

Towards Efficient Training and Evaluation of Robust Models against $l_0$ Bounded Adversarial Perturbations

Xuyang Zhong, Yixiao HUANG, Chen Liu

Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification

Martin Mihelich, François Castagnos, Charles Dognin

An Explicit Frame Construction for Normalizing 3D Point Clouds

Justin Baker, Shih-Hsin Wang, Tommaso de Fernex et al.

Hierarchical Novelty Detection via Fine-Grained Evidence Allocation

Spandan Pyakurel, Qi Yu

Sampling-based Multi-dimensional Recalibration

Youngseog Chung, Ian Char, Jeff Schneider

Switching the Loss Reduces the Cost in Batch Reinforcement Learning

Alex Ayoub, Kaiwen Wang, Vincent Liu et al.

Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series

Asterios Tsiourvas, Wei Sun, Georgia Perakis et al.

A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle

Nadav Hallak, Kfir Levy

Position: LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks

Subbarao Kambhampati, Karthik Valmeekam, Lin Guan et al.

New Sample Complexity Bounds for Sample Average Approximation in Heavy-Tailed Stochastic Programming

Hongcheng Liu, Jindong Tong

Efficient Value Iteration for s-rectangular Robust Markov Decision Processes

Navdeep Kumar, Kaixin Wang, Kfir Levy et al.

Large Scale Dataset Distillation with Domain Shift

Noel Loo, Alaa Maalouf, Ramin Hasani et al.

Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models

Francesca-Zhoufan Li, Ava Amini, Yisong Yue et al.

Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations

Pan Xu

Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving

Sohei Arisaka, Qianxiao Li

Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation

Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu

GiLOT: Interpreting Generative Language Models via Optimal Transport

Xuhong Li, Jiamin Chen, Yekun Chai et al.

Autoencoding Conditional Neural Processes for Representation Learning

Victor Prokhorov, Ivan Titov, Siddharth N

LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning

Hongye Jin, Xiaotian Han, Jingfeng Yang et al.

Position: Automatic Environment Shaping is the Next Frontier in RL

Younghyo Park, Gabriel Margolis, Pulkit Agrawal

BLO-SAM: Bi-level Optimization Based Finetuning of the Segment Anything Model for Overfitting-Preventing Semantic Segmentation

Li Zhang, Youwei Liang, Ruiyi Zhang et al.

Data-free Neural Representation Compression with Riemannian Neural Dynamics

Zhengqi Pei, Anran Zhang, Shuhui Wang et al.

Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining

Florian Tramer, Gautam Kamath, Nicholas Carlini

Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification

Jay Gala, Pengtao Xie

Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?

Yilong Wang, Haishan Ye, Guang Dai et al.

Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling

Yuanbang Liang, Jing Wu, Yu-Kun Lai et al.

Causal Inference out of Control: Estimating Performativity without Treatment Randomization

Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner

Overcoming the Optimizer's Curse: Obtaining Realistic Prescriptions from Neural Networks

Asterios Tsiourvas, Georgia Perakis

Ameliorate Spurious Correlations in Dataset Condensation

Jiaxing Cui, Ruochen Wang, Yuanhao Xiong et al.

Sparsest Models Elude Pruning: An Exposé of Pruning’s Current Capabilities

Stephen Zhang, Vardan Papyan

Regularized Q-learning through Robust Averaging

Peter Schmitt-Förster, Tobias Sutter

Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms

Hiren Madhu, Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri

How do Transformers Perform In-Context Autoregressive Learning ?

Michael Sander, Raja Giryes, Taiji Suzuki et al.

Vision Transformers as Probabilistic Expansion from Learngene

Qiufeng Wang, Xu Yang, Haokun Chen et al.

QBMK: Quantum-based Matching Kernels for Un-attributed Graphs

Lu Bai, Lixin Cui, Ming Li et al.

Modeling Language Tokens as Functionals of Semantic Fields

Zhengqi Pei, Anran Zhang, Shuhui Wang et al.

Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing

Gabriel Arpino, Xiaoqi Liu, Ramji Venkataramanan

Score-Based Causal Discovery of Latent Variable Causal Models

Ignavier Ng, Xinshuai Dong, Haoyue Dai et al.

Reward Shaping for Reinforcement Learning with An Assistant Reward Agent

Haozhe Ma, Kuankuan Sima, Thanh Vinh Vo et al.

Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference

Luca Masserano, Alexander Shen, Michele Doro et al.

Position: Technical Research and Talent is Needed for Effective AI Governance

Anka Reuel, Lisa Soder, Benjamin Bucknall et al.

Dirichlet Flow Matching with Applications to DNA Sequence Design

Hannes Stärk, Bowen Jing, Chenyu Wang et al.

Fast Sampling-Based Sketches for Tensors

William Swartworth, David Woodruff

Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning

Yun-Hsuan Lien, Ping-Chun Hsieh, Tzu-Mao Li et al.

Diffusion Models Encode the Intrinsic Dimension of Data Manifolds

Jan Stanczuk, Georgios Batzolis, Teo Deveney et al.

R2E: Turning any Github Repository into a Programming Agent Environment

Naman Jain, Manish Shetty Molahalli, Tianjun Zhang et al.

Two Fists, One Heart: Multi-Objective Optimization Based Strategy Fusion for Long-tailed Learning

Zhe Zhao, Pengkun Wang, HaiBin Wen et al.

Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection

Abhinab Acharya, Dayou Yu, Qi Yu et al.

Data-free Distillation of Diffusion Models with Bootstrapping

Jiatao Gu, Chen Wang, Shuangfei Zhai et al.

Generalization Analysis of Deep Non-linear Matrix Completion

Antoine Ledent, Rodrigo Alves

Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers

Yuxing Liu, Lesi Chen, Luo Luo

Logistic Variational Bayes Revisited

Michael Komodromos, Marina Evangelou, Sarah Filippi