Most Cited 2025 "prompt aggregation" Papers

Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents

Yifei Zhou, Qianlan Yang, Kaixiang Lin et al.

Hgformer: Hyperbolic Graph Transformer for Collaborative Filtering

Yang Xin, Xingrun Li, Heng Chang et al.

BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling

Hao Li, Yu-Hao Huang, Chang Xu et al.

Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach

Jin Zhu, Jingyi Li, Hongyi Zhou et al.

A Reasoning-Based Approach to Cryptic Crossword Clue Solving

Martin Andrews, Sam Witteveen

Fully Dynamic Euclidean Bi-Chromatic Matching in Sublinear Update Time

Gramoz Goranci, Peter Kiss, Neel Patel et al.

What Makes In-context Learning Effective for Mathematical Reasoning

Jiayu Liu, Zhenya Huang, Chaokun Wang et al.

Global-Local Dirichlet Processes for Clustering Grouped Data in the Presence of Group-Specific Idiosyncratic Variables

Arhit Chakrabarti, Yang Ni, Debdeep Pati et al.

TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

Daoyu Wang, Mingyue Cheng, Zhiding Liu et al.

Knowledge-Guided Wasserstein Distributionally Robust Optimization

Zitao Wang, Ziyuan Wang, Molei Liu et al.

Hessian Geometry of Latent Space in Generative Models

Alexander Lobashev, Dmitry Guskov, Maria Larchenko et al.

Online Sparsification of Bipartite-Like Clusters in Graphs

Joyentanuj Das, Suranjan De, He Sun

Efficient Graph Continual Learning via Lightweight Graph Neural Tangent Kernels-based Dataset Distillation

Rihong Qiu, Xinke Jiang, Yuchen Fang et al.

DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space

Mang Ning, Mingxiao Li, Jianlin Su et al.

Regression for the Mean: Auto-Evaluation and Inference with Few Labels through Post-hoc Regression

Benjamin Eyre, David Madras

FastCAV: Efficient Computation of Concept Activation Vectors for Explaining Deep Neural Networks

Laines Schmalwasser, Niklas Penzel, Joachim Denzler et al.

Learning Single Index Models with Diffusion Priors

Anqi Tang, Youming Chen, Shuchen Xue et al.

Neural Encoding and Decoding at Scale

Yizi Zhang, Yanchen Wang, Mehdi Azabou et al.

Wyckoff Transformer: Generation of Symmetric Crystals

Nikita Kazeev, Wei Nong, Ignat Romanov et al.

Generalization Analysis for Supervised Contrastive Representation Learning under Non-IID Settings

Minh Hieu Nong, Antoine Ledent

Sampling from Binary Quadratic Distributions via Stochastic Localization

Chenguang Wang, Kaiyuan Cui, Weichen Zhao et al.

Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning

Zhiwei XU, Kun Hu, Xin Xin et al.

Online Detection of LLM-Generated Texts via Sequential Hypothesis Testing by Betting

Can Chen, Jun-Kun Wang

Putnam-AXIOM: A Functional & Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs

Aryan Gulati, Brando Miranda, Eric Chen et al.

Avoiding spurious sharpness minimization broadens applicability of SAM

Sidak Pal Singh, Hossein Mobahi, Atish Agarwala et al.

Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization

Suryanarayana Sankagiri, Jalal Etesami, Matthias Grossglauser

Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers

Lokesh Veeramacheneni, Moritz Wolter, Hilde Kuehne et al.

Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification

Flavio Petruzzellis, Cristina Cornelio, Pietro Lió

How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies

Piotr Kubaty, Bartosz Wójcik, Bartłomiej Krzepkowski et al.

VTGaussian-SLAM: RGBD SLAM for Large Scale Scenes with Splatting View-Tied 3D Gaussians

Pengchong Hu, Zhizhong Han

Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication Overlapping

Muru Zhang, Mayank Mishra, Zhongzhu Zhou et al.

Convergence of Consistency Model with Multistep Sampling under General Data Assumptions

Yiding Chen, Yiyi Zhang, Owen Oertell et al.

Mahalanobis++: Improving OOD Detection via Feature Normalization

Maximilian Müller, Matthias Hein

Audio Flamingo 2: An Audio-Language Model with Long-Audio Understanding and Expert Reasoning Abilities

Sreyan Ghosh, Zhifeng Kong, Sonal Kumar et al.

Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance

Linxi Zhao, Yihe Deng, Weitong Zhang et al.

Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL

Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi GNVV et al.

What Makes a Good Feedforward Computational Graph?

Alex Vitvitskyi, João Madeira Araujo, Marc Lackenby et al.

Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models

Lucy Xiaoyang Shi, brian ichter, Michael Equi et al.

Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning

Erchi Wang, Yuqing Zhu, Yu-Xiang Wang

FAB-PPI: Frequentist, Assisted by Bayes, Prediction-Powered Inference

Stefano Cortinovis, Francois Caron

Optimizing Noise Distributions for Differential Privacy

Atefeh Gilani, Felipe Gomez, Shahab Asoodeh et al.

Training Diffusion-based Generative Models with Limited Data

Zhaoyu Zhang, Yang Hua, Guanxiong Sun et al.

Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression

Jingfeng Wu, Peter Bartlett, Matus Telgarsky et al.

Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Stochastic Bias and Remedies

Qiang Li, Michal Yemini, Hoi To Wai

Consensus Is All You Get: The Role of Attention in Transformers

Alvaro Rodriguez Abella, João Pedro Silvestre, Paulo Tabuada

Gradient Descent Converges Arbitrarily Fast for Logistic Regression via Large and Adaptive Stepsizes

Ruiqi Zhang, Jingfeng Wu, Peter Bartlett

OrcaLoca: An LLM Agent Framework for Software Issue Localization

Zhongming Yu, Hejia Zhang, Yujie Zhao et al.

Mixed-curvature decision trees and random forests

Philippe Chlenski, Quentin Chu, Raiyan Khan et al.

An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures

Thibaut Boissin, Franck Mamalet, Thomas Fel et al.

Scalable Model Merging with Progressive Layer-wise Distillation

Jing Xu, Jiazheng Li, Jingzhao Zhang

Learning Distribution-wise Control in Representation Space for Language Models

Deng, Ruidi Chang, Hanjie Chen

Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning

Puning Yang, Qizhou Wang, Zhuo Huang et al.

EditLord: Learning Code Transformation Rules for Code Editing

Weichen Li, Albert Jan, Baishakhi Ray et al.

AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Zheng Lian, Haoyu Chen, Lan Chen et al.

Fluctuations of the largest eigenvalues of transformed spiked Wigner matrices

Aro Lee, Ji Oon Lee

Covered Forest: Fine-grained generalization analysis of graph neural networks

Antonis Vasileiou, Ben Finkelshtein, Floris Geerts et al.

Robust Noise Attenuation via Adaptive Pooling of Transformer Outputs

Greyson Brothers

Breaking Barriers: Combinatorial Algorithms for Non-Monotone Submodular Maximization with Sublinear Adaptivity and $1/e$ Approximation

Yixin Chen, Wenjing Chen, Alan Kuhnle

NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits

Tushar Aggarwal, Swayam Singh, Abhijeet Awasthi et al.

MMInference: Accelerating Pre-filling for Long-Context Visual Language Models via Modality-Aware Permutation Sparse Attention

Yucheng Li, Huiqiang Jiang, Chengruidong Zhang et al.

Conformal Prediction as Bayesian Quadrature

Jake Snell, Thomas Griffiths

A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition

Nian Liu, Xiaoxin He, Thomas Laurent et al.

Improving the Statistical Efficiency of Cross-Conformal Prediction

DTZO: Distributed Trilevel Zeroth Order Learning with Provable Non-Asymptotic Convergence

Yang Jiao, Kai Yang, Chengtao Jian

Hierarchical Equivariant Policy via Frame Transfer

Haibo Zhao, Dian Wang, Yizhe Zhu et al.

The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes

Pedro Santos, Alberto Sardinha, Francisco S. Melo

Dynamical phases of short-term memory mechanisms in RNNs

Bariscan Kurtkaya, Fatih Dinc, Mert Yuksekgonul et al.

The Berkeley Function Calling Leaderboard (BFCL): From Tool Use to Agentic Evaluation of Large Language Models

Shishir G. Patil, Huanzhi Mao, Fanjia Yan et al.

Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance

Shogo Iwazaki, Shion Takeno

Eliciting Language Model Behaviors with Investigator Agents

Xiang Li, Neil Chowdhury, Daniel Johnson et al.

Policy Gradient with Tree Expansion

Gal Dalal, Assaf Hallak, Gugan Chandrashekhar Mallika Thoppe et al.

SGD Jittering: A Training Strategy for Robust and Accurate Model-Based Architectures

Peimeng Guan, Mark Davenport

Double Machine Learning for Causal Inference under Shared-State Interference

Chris Hays, Manish Raghavan

SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders

Bartosz Cywiński, Kamil Deja

Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations

Shahaf Bassan, Yizhak Elboher, Tobias Ladner et al.

Adaptive Elicitation of Latent Information Using Natural Language

Jimmy Wang, Tom Zollo, Richard Zemel et al.

Goal-Space Planning with Subgoal Models

Chunlok Lo, Kevin Roice, Parham Mohammad Panahi et al.

RULEBREAKERS: Challenging LLMs at the Crossroads between Formal Logic and Human-like Reasoning

Jason Chan, Robert Gaizauskas, Zhixue Zhao

SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity

Samir Khaki, Xiuyu Li, Junxian Guo et al.

Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization

Michael S Yao, James Gee, Osbert Bastani

Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow

Zhonglin Cao, Mario Geiger, Allan Costa et al.

Survival Analysis via Density Estimation

Hiroki Yanagisawa, Shunta Akiyama

Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning

Hongyao Chen, Tianyang Xu, Xiaojun Wu et al.

Tilted Sharpness-Aware Minimization

Tian Li, Tianyi Zhou, Jeff Bilmes

LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence

Zhuoling Li, Xiaogang Xu, Zhenhua Xu et al.

DynaMind: Reasoning over Abstract Video Dynamics for Embodied Decision-Making

Ziru Wang, Mengmeng Wang, Jade Dai et al.

Graph4MM: Weaving Multimodal Learning with Structural Information

Xuying Ning, Dongqi Fu, Tianxin Wei et al.

Investigating the Overlooked Hessian Structure: From CNNs to LLMs

Qian-Yuan Tang, Yufei Gu, Yunfeng Cai et al.

Dimension-Independent Rates for Structured Neural Density Estimation

Vandermeulen, Wai Ming Tai, Bryon Aragam

Counterfactual Graphical Models: Constraints and Inference

Juan Correa, Elias Bareinboim

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound

David Boetius, Stefan Leue, Tobias Sutter

Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systems

Taejin Park, Ivan Medennikov, Kunal Dhawan et al.

Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge

Hanna Wallach, Meera Desai, A. Feder Cooper et al.

Position: AI Agents Need Authenticated Delegation

Tobin South, Samuele Marro, Thomas Hardjono et al.

Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks

Judy Hanwen Shen

Position: Certified Robustness Does Not (Yet) Imply Model Security

Andrew C. Cullen, Paul MONTAGUE, Sarah Erfani et al.

Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It

Jillian Fisher, Ruth Elisabeth Appel, Chan Young Park et al.

Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification

Jan Blechschmidt, Tom-Christian Riemer, Max Winkler et al.

Machine Learning meets Algebraic Combinatorics: A Suite of Datasets Capturing Research-level Conjecturing Ability in Pure Mathematics

Herman Chau, Helen Jenne, Davis Brown et al.

Position: Future Research and Challenges Remain Towards AI for Software Engineering

Alex Gu, Naman Jain, Wen-Ding Li et al.

Deliberation in Latent Space via Differentiable Cache Augmentation

Luyang Liu, Jonas Pfeiffer, Jiaxing Wu et al.

Position: AI Safety Must Embrace an Antifragile Perspective

Ming Jin, Hyunin Lee

Machines and Mathematical Mutations: Using GNNs to Characterize Quiver Mutation Classes

Jesse He, Helen Jenne, Herman Chau et al.

Position: We Can’t Understand AI Using our Existing Vocabulary

John Hewitt, Robert Geirhos, Been Kim

Position: LLM Social Simulations Are a Promising Research Method

Jacy Anthis, Ryan Liu, Sean Richardson et al.

Trajectory World Models for Heterogeneous Environments

Shaofeng Yin, Jialong Wu, Siqiao Huang et al.

Position: Beyond Assistance – Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care

Abeer Badawi, Md Tahmid Rahman Laskar, Jimmy Huang et al.

Position: Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work.

Aviv Ovadya, Kyle Redman, Luke Thorburn et al.

Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra

Alan Amin, Andres Potapczynski, Andrew Wilson

Reliable Algorithm Selection for Machine Learning-Guided Design

Clara Fannjiang, Ji Won Park

On Fine-Grained Distinct Element Estimation

Ilias Diakonikolas, Daniel Kane, Jasper Lee et al.

Learning-Augmented Hierarchical Clustering

Vladimir Braverman, Jon C. Ergun, Chen Wang et al.

Low-distortion and GPU-compatible Tree Embeddings in Hyperbolic Space

Max van Spengler, Pascal Mettes

DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts

Tobias Braun, Mark Rothermel, Marcus Rohrbach et al.

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators

Ze Cheng, Zhuoyu Li, Wang Xiaoqiang et al.

S4S: Solving for a Fast Diffusion Model Solver

Eric Frankel, Sitan Chen, Jerry Li et al.

Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization

Peiyan Zhang, Haibo Jin, Leyang Hu et al.

Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts

Jiahai Feng, Stuart Russell, Jacob Steinhardt

Uniform Mean Estimation for Heavy-Tailed Distributions via Median-of-Means

Mikael Møller Høgsgaard, Andrea Paudice

FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting

Yue Jiang, Yile Chen, Xiucheng Li et al.

ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior

Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang et al.

From RAG to Memory: Non-Parametric Continual Learning for Large Language Models

Bernal Jimenez Gutierrez, Yiheng Shu, Weijian Qi et al.

DRAG: Data Reconstruction Attack using Guided Diffusion

Wa-Kin Lei, Jun-Cheng Chen, Shang-Tse Chen

FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation

Srijith Nair, Michael Lin, Peizhong Ju et al.

Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning

Zhiyao Zhang, Myeung Suk Oh, Hairi et al.

The Jailbreak Tax: How Useful are Your Jailbreak Outputs?

Kristina Nikolić, Luze Sun, Jie Zhang et al.

LETS Forecast: Learning Embedology for Time Series Forecasting

Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.

Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning

Chen-Xiao Gao, Chenyang Wu, Mingjun Cao et al.

Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds

Aya Kayal, Sattar Vakili, Laura Toni et al.

Gridded Transformer Neural Processes for Spatio-Temporal Data

Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.

Latent Mamba Operator for Partial Differential Equations

Karn Tiwari, Niladri Dutta, N M Anoop Krishnan et al.

High-Dimensional Prediction for Sequential Decision Making

Georgy Noarov, Ramya Ramalingam, Aaron Roth et al.

Steering Protein Language Models

Long-Kai Huang, Rongyi Zhu, Bing He et al.

Cross-City Latent Space Alignment for Consistency Region Embedding

Meng Chen, Hongwei Jia, Zechen Li et al.

Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry

Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.

Diffusion Adversarial Post-Training for One-Step Video Generation

Shanchuan Lin, Xin Xia, Yuxi Ren et al.

Adaptive Sensitivity Analysis for Robust Augmentation against Natural Corruptions in Image Segmentation

Laura Zheng, Wenjie Wei, Tony Wu et al.

Closed-form Solutions: A New Perspective on Solving Differential Equations

Shu Wei, Yanjie Li, Lina Yu et al.

David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training

Weijian Luo, colin zhang, Debing Zhang et al.

A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward

Zachary Roch, George Atia, Yue Wang

Statistical Test for Feature Selection Pipelines by Selective Inference

Tomohiro Shiraishi, Tatsuya Matsukawa, Shuichi Nishino et al.

Position: AI Safety should prioritize the Future of Work

Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty

Distributionally Robust Active Learning for Gaussian Process Regression

Shion Takeno, Yoshito Okura, Yu Inatsu et al.

Geometry-Informed Neural Networks

Arturs Berzins, Andreas Radler, Eric Volkmann et al.

SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models

Yung-Sung Chuang, Benjamin Cohen-Wang, Shannon Shen et al.

Multiaccuracy and Multicalibration via Proxy Groups

Beepul Bharti, Mary Clemens-Sewall, Paul H. Yi et al.

A Model of Place Field Reorganization During Reward Maximization

M Ganesh Kumar, Blake Bordelon, Jacob A Zavatone-Veth et al.

Representative Language Generation

Charlotte Peale, Vinod Raman, Omer Reingold

Detecting Strategic Deception with Linear Probes

Nicholas Goldowsky-Dill, Bilal Chughtai, Stefan Heimersheim et al.

LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data

Peer Nagy, Sascha Frey, Kang Li et al.

Curse of High Dimensionality Issue in Transformer for Long Context Modeling

Shuhai Zhang, Zeng You, Yaofo Chen et al.

Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations

Juwei Yue, Haikuo Li, Jiawei Sheng et al.

Goal-Oriented Skill Abstraction for Offline Multi-Task Reinforcement Learning

Jinmin He, Kai Li, Yifan Zang et al.

Score-of-Mixture Training: One-Step Generative Model Training Made Simple via Score Estimation of Mixture Distributions

Tejas Jayashankar, Jongha (Jon) Ryu, Gregory Wornell

Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective

Firas Laakom, Haobo Chen, Jürgen Schmidhuber et al.

SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space

Xupeng Zhu, Fan Wang, Robin Walters et al.

Hypo3D: Exploring Hypothetical Reasoning in 3D

Ye Mao, Weixun Luo, Junpeng Jing et al.

Maximum Entropy Reinforcement Learning with Diffusion Policy

Xiaoyi Dong, Jian Cheng, Xi Zhang

Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability

Michael Crawshaw, Blake Woodworth, Mingrui Liu

Return Capping: Sample Efficient CVaR Policy Gradient Optimisation

Harry Mead, Clarissa Costen, Bruno Lacerda et al.

Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection

Yucen Li, Daohan Lu, Polina Kirichenko et al.

Sample Complexity of Distributionally Robust Off-Dynamics Reinforcement Learning with Online Interaction

Yiting He, Zhishuai Liu, Weixin Wang et al.

Unifews: You Need Fewer Operations for Efficient Graph Neural Networks

Ningyi Liao, Zihao Yu, Ruixiao Zeng et al.

Exploring Representations and Interventions in Time Series Foundation Models

Michal Wilinski, Mononito Goswami, Willa Potosnak et al.

Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers

Alireza Amiribavandpour, Xinting Huang, Mark Rofin et al.

Action Dubber: Timing Audible Actions via Inflectional Flow

Wenlong Wan, Weiying Zheng, Tianyi Xiang et al.

FLAM: Frame-Wise Language-Audio Modeling

Yusong Wu, Christos Tsirigotis, Ke Chen et al.

Robust Sparsification via Sensitivity

Chansophea Wathanak In, Yi Li, David Woodruff et al.

Rényi Neural Processes

Xuesong Wang, He Zhao, Edwin V. Bonilla

Adaptive Sample Sharing for Multi Agent Linear Bandits

Hamza Cherkaoui, Merwan Barlier, Igor Colin

Zero-Shot Offline Imitation Learning via Optimal Transport

Thomas Rupf, Marco Bagatella, Nico Gürtler et al.

Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

Linhao Luo, Zicheng Zhao, Reza Haffari et al.

FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making

Yucen Wang, Rui Yu, Shenghua Wan et al.

Anytime-Constrained Equilibria in Polynomial Time

Jeremy McMahan

Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations

Jeet Mohapatra, Nima Dehmamy, Csaba Both et al.

Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing

Han Jiang, Xiaoyuan Yi, Zhihua Wei et al.

Telling Peer Direct Effects from Indirect Effects in Observational Network Data

Xiaojing Du, Jiuyong Li, Debo Cheng et al.

Partially Observable Reinforcement Learning with Memory Traces

Onno Eberhard, Michael Muehlebach, Claire Vernade

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization

Simone Bombari, Marco Mondelli

EPIC: Efficient Position-Independent Caching for Serving Large Language Models

JUNHAO HU, Wenrui Huang, Weidong Wang et al.

Multivariate Conformal Selection

Tian Bai, Yue Zhao, Xiang Yu et al.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs

Jianqing Zhang, Yang Liu, Jie Fu et al.

Direct Motion Models for Assessing Generated Videos

Kelsey Allen, Carl Doersch, Guangyao Zhou et al.

How Effective Can Dropout Be in Multiple Instance Learning ?

Wenhui Zhu, Peijie Qiu, Xiwen Chen et al.

Understanding Synthetic Context Extension via Retrieval Heads

Xinyu Zhao, Fangcong Yin, Greg Durrett

KernelBench: Can LLMs Write Efficient GPU Kernels?

Anne Ouyang, Simon Guo, Simran Arora et al.

Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization

Cameron Jakub, Mihai Nica

MARS: Unleashing the Power of Variance Reduction for Training Large Models

Huizhuo Yuan, Yifeng Liu, Shuang Wu et al.

ADIOS: Antibody Development via Opponent Shaping

Sebastian Towers, Aleksandra Kalisz, Philippe Robert et al.

Reinforcement Learning for Quantum Control under Physical Constraints

Jan Ole Ernst, Aniket Chatterjee, Tim Franzmeyer et al.

Automated Benchmark Generation for Repository-Level Coding Tasks

Konstantinos Vergopoulos, Mark Müller, Martin Vechev

Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models

Yinhong Liu, Zhijiang Guo, Tianya Liang et al.

Attention-Level Speculation

Jack Cai, Ammar Vora, Randolph Zhang et al.

Unified Screening for Multiple Diseases

Yiğit Narter, Alihan Hüyük, Mihaela van der Schaar et al.

Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly From Data

Krzysztof Kacprzyk, Julianna Piskorz, Mihaela van der Schaar

Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts

Chengyi Cai, Zesheng Ye, Lei Feng et al.

Elucidating the Design Space of Multimodal Protein Language Models

Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang et al.

Models of Heavy-Tailed Mechanistic Universality

Liam Hodgkinson, Zhichao Wang, Michael Mahoney

Stochastic Encodings for Active Feature Acquisition

Alexander Norcliffe, Changhee Lee, Fergus Imrie et al.

Sum-of-Parts: Self-Attributing Neural Networks with End-to-End Learning of Feature Groups

Weiqiu You, Helen Qu, Marco Gatti et al.