Most Cited 2025 "risk allocation" Papers

A Generic Family of Graphical Models: Diversity, Efficiency, and Heterogeneity

Yufei Huang, Changhu Wang, Junjie Tang et al.

TabFlex: Scaling Tabular Learning to Millions with Linear Attention

Yuchen Zeng, Tuan Dinh, Wonjun Kang et al.

Efficiently Vectorized MCMC on Modern Accelerators

Hugh Dance, Pierre Glaser, Peter Orbanz et al.

Understanding Complexity in VideoQA via Visual Program Generation

Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave et al.

Adversarial Inputs for Linear Algebra Backends

Jonas Möller, Lukas Pirch, Felix Weissberg et al.

SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting

Yitian Zhang, Liheng Ma, Antonios Valkanas et al.

Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective

Steve Azzolin, SAGAR MALHOTRA, Andrea Passerini et al.

ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy

Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik et al.

SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models

Jiawei Zhang, Xuan Yang, Taiqi Wang et al.

Nemotron-CORTEXA: Enhancing LLM Agents for Software Engineering Tasks via Improved Localization and Solution Diversity

Atefeh Sohrabizadeh, Jialin Song, Mingjie Liu et al.

Whitened CLIP as a Likelihood Surrogate of Images and Captions

Roy Betser, Meir Yossef Levi, Guy Gilboa

Time Series Representations with Hard-Coded Invariances

Thibaut Germain, Chrysoula Kosma, Laurent Oudre

EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption

Leo de Castro, Daniel Escudero, Adya Agrawal et al.

Universal Neural Optimal Transport

Jonathan Geuter, Gregor Kornhardt, Ingimar Tomasson et al.

Measuring In-Context Computation Complexity via Hidden State Prediction

Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber

Teaching Transformers Causal Reasoning through Axiomatic Training

Aniket Vashishtha, Abhinav Kumar, Atharva Pandey et al.

CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging

Wenju Sun, Qingyong Li, Yangliao Geng et al.

Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization

Youran Dong, Junfeng Yang, Wei Yao et al.

CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition

Zebin Wang, Menghan Lin, Bolin Shen et al.

Simplicity Bias and Optimization Threshold in Two-Layer ReLU Networks

Etienne Boursier, Nicolas Flammarion

Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead

Won-Jun Jang, Hyeon-Seo Park, Si-Hyeon Lee

Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning

Mengmeng Chen, Xiaohu Wu, QIQI LIU et al.

Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic Regressions

Supratim Shit, Gurmehak chadha, Surendra kumar et al.

Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation

Shyam Nuggehalli, Jifan Zhang, Lalit Jain et al.

Strong and Weak Identifiability of Optimization-based Causal Discovery in Non-linear Additive Noise Models

Mingjia Li, Hong Qian, Tian-Zuo Wang et al.

Nearly Optimal Sample Complexity for Learning with Label Proportions

Robert Busa-Fekete, Travis Dick, Claudio Gentile et al.

Scalable Private Partition Selection via Adaptive Weighting

Justin Chen, Vincent Cohen-Addad, Alessandro Epasto et al.

GSM-$\infty$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?

Yang Zhou, Hongyi Liu, Zhuoming Chen et al.

PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction

Aaron Wenteler, Martina Occhetta, Nikhil Branson et al.

Perceptual-GS: Scene-adaptive Perceptual Densification for Gaussian Splatting

Hongbi ZHOU, Zhangkai NI

Scaling Trends in Language Model Robustness

Nikolaus Howe, Ian McKenzie, Oskar Hollinsworth et al.

Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances

Jie Wang, March Boedihardjo, Yao Xie

I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models

Zhenxing Mi, Kuan-Chieh Wang, Guocheng Qian et al.

Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance

Lisha Chen, Quan Xiao, Ellen Fukuda et al.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation

Piyush Lalitkumar Tiwary, Kinjawl Bhattacharyya, Prathosh AP

Feedforward Few-shot Species Range Estimation

Christian Lange, Max Hamilton, Elijah Cole 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.

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.

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.

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

Mang Ning, Mingxiao Li, Jianlin Su et al.

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

Laines Schmalwasser, Niklas Penzel, Joachim Denzler 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.

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.

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.

Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL

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

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

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

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

Qiang Li, Michal Yemini, Hoi To Wai

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.

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

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

Zheng Lian, Haoyu Chen, Lan Chen et al.

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

Antonis Vasileiou, Ben Finkelshtein, Floris Geerts et al.

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.

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

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

Pedro Santos, Alberto Sardinha, Francisco S. Melo

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

Shogo Iwazaki, Shion Takeno

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

Adaptive Elicitation of Latent Information Using Natural Language

Jimmy Wang, Tom Zollo, Richard Zemel 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

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

Ziru Wang, Mengmeng Wang, Jade Dai et al.

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound

David Boetius, Stefan Leue, Tobias Sutter

Position: AI Agents Need Authenticated Delegation

Tobin South, Samuele Marro, Thomas Hardjono et al.

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.

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.

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.

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.

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators

Ze Cheng, Zhuoyu Li, Wang Xiaoqiang et al.

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

Yue Jiang, Yile Chen, Xiucheng Li 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.

Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds

Aya Kayal, Sattar Vakili, Laura Toni et al.

High-Dimensional Prediction for Sequential Decision Making

Georgy Noarov, Ramya Ramalingam, Aaron Roth 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

Distributionally Robust Active Learning for Gaussian Process Regression

Shion Takeno, Yoshito Okura, Yu Inatsu 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.

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

Jinmin He, Kai Li, Yifan Zang et al.

Hypo3D: Exploring Hypothetical Reasoning in 3D

Ye Mao, Weixun Luo, Junpeng Jing 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.

Zero-Shot Offline Imitation Learning via Optimal Transport

Thomas Rupf, Marco Bagatella, Nico Gürtler et al.

Anytime-Constrained Equilibria in Polynomial Time

Jeremy McMahan

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.

KernelBench: Can LLMs Write Efficient GPU Kernels?

Anne Ouyang, Simon Guo, Simran Arora et al.

ADIOS: Antibody Development via Opponent Shaping

Sebastian Towers, Aleksandra Kalisz, Philippe Robert et al.

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.

Models of Heavy-Tailed Mechanistic Universality

Liam Hodgkinson, Zhichao Wang, Michael Mahoney

Balancing Preservation and Modification: A Region and Semantic Aware Metric for Instruction-Based Image Editing

Zhuoying Li, Zhu Xu, Yuxin Peng et al.

On the Similarities of Embeddings in Contrastive Learning

Chungpa Lee, Sehee Lim, Kibok Lee et al.

Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity

Zhenglin Wan, Xingrui Yu, David Bossens et al.

High-Fidelity Simultaneous Speech-To-Speech Translation

Tom Labiausse, Laurent Mazaré, Edouard Grave et al.

PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning

Angel Villar-Corrales, Sven Behnke

World Model Implanting for Test-time Adaptation of Embodied Agents

Minjong Yoo, Jinwoo Jang, Sihyung Yoon et al.

M³HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality

Ziyan Wang, Zhicheng Zhang, Fei Fang et al.

Position: General Intelligence Requires Reward-based Pretraining

Seungwook Han, Jyothish Pari, Samuel Gershman et al.

Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived

Yuhe Guo, Huayi Tang, Jiahong Ma et al.

Position: Constants are Critical in Regret Bounds for Reinforcement Learning

Simone Drago, Marco Mussi, Alberto Maria Metelli

Continuous Bayesian Model Selection for Multivariate Causal Discovery

Anish Dhir, Ruby Sedgwick, Avinash Kori et al.

Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation

Mohit Pandey, Gopeshh Subbaraj, Artem Cherkasov et al.

Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models

Mingi Jung, Saehyung Lee, Eunji Kim et al.

Text-to-LoRA: Instant Transformer Adaption

Rujikorn Charakorn, Edoardo Cetin, Yujin Tang et al.

On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning

Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li

Can Large Language Models Understand Intermediate Representations in Compilers?

Hailong Jiang, Jianfeng Zhu, Yao Wan et al.

Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation

Mingyu Kang, Yong Suk Choi

Learnware Specification via Dual Alignment

Wei Chen, Jun-Xiang Mao, Xiaozheng Wang et al.

On the Importance of Gaussianizing Representations

Daniel Eftekhari, Vardan Papyan

CodeSync: Synchronizing Large Language Models with Dynamic Code Evolution at Scale

Chenlong Wang, Zhaoyang Chu, Zhengxiang Cheng et al.

Adversarial Inception Backdoor Attacks against Reinforcement Learning

Ethan Rathbun, Alina Oprea, Christopher Amato

Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs

Hancheng Min, Rene Vidal

The underlying structures of self-attention: symmetry, directionality, and emergent dynamics in Transformer training

Matteo Saponati, Pascal J. Sager, Pau Vilimelis Aceituno et al.

Novelty Detection in Reinforcement Learning with World Models

Geigh Zollicoffer, Kenneth Eaton, Jonathan Balloch et al.

Relational Invariant Learning for Robust Solvation Free Energy Prediction

Yeyun Chen

Unconstrained Robust Online Convex Optimization

Jiujia Zhang, Ashok Cutkosky

The Hidden Dimensions of LLM Alignment: A Multi-Dimensional Analysis of Orthogonal Safety Directions

Wenbo Pan, Zhichao Liu, Qiguang Chen et al.

Outlier-Aware Post-Training Quantization for Discrete Graph Diffusion Models

Zheng Gong, Ying Sun

ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks

Yufei Guo, Yuhan Zhang, Zhou Jie et al.

Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection

Louis Béthune, David Grangier, Dan Busbridge et al.

Relative Error Fair Clustering in the Weak-Strong Oracle Model

Vladimir Braverman, Prathamesh Dharangutte, Shaofeng Jiang et al.

Doubly Protected Estimation for Survival Outcomes Utilizing External Controls for Randomized Clinical Trials

Chenyin Gao, Shu Yang, Mingyang Shan et al.

Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models

Anshuman Chhabra, Bo Li, Jian Chen et al.

BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation

Lian Liu, Xiandong Zhao, Guanchen Li et al.

Geometric Contact Flows: Contactomorphisms for Dynamics and Control

Andrea Testa, Søren Hauberg, Tamim Asfour et al.

Neural Genetic Search in Discrete Spaces

Hyeonah Kim, Sanghyeok Choi, Jiwoo Son et al.

Sparse Video-Gen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity

Haocheng Xi, Shuo Yang, Yilong Zhao et al.

PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities

Daniel Zilberg, Ron Levie

Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization

Xiuyuan Wang, Chaochao Chen, Weiming Liu et al.

Ad Hoc Teamwork via Offline Goal-Based Decision Transformers

Xinzhi Zhang, Hoehi Chan, Deheng Ye et al.

AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and Treefinement

Pranjal Aggarwal, Bryan Parno, Sean Welleck

The Ripple Effect: On Unforeseen Complications of Backdoor Attacks

Rui Zhang, Yun Shen, Hongwei Li et al.

A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach

Swetha Ganesh, Washim Mondal, Vaneet Aggarwal

Contrastive Localized Language-Image Pre-Training

Hong-You Chen, Zhengfeng Lai, Haotian Zhang et al.

Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks

Yuhang Cai, Kangjie Zhou, Jingfeng Wu et al.

Improved and Oracle-Efficient Online $\ell_1$-Multicalibration

Rohan Ghuge, Vidya Muthukumar, Sahil Singla

One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation

Jianze Li, Jiezhang Cao, Yong Guo et al.

Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation

Jan Pauls, Max Zimmer, Berkant Turan et al.

Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift

chao ying, Jun Jin, Yi Guo et al.

A Sample Efficient Conditional Independence Test in the Presence of Discretization

Boyang Sun, Yu Yao, Xinshuai Dong et al.

"Why Is There a Tumor?": Tell Me the Reason, Show Me the Evidence

Mengmeng Ma, Tang Li, Yunxiang Peng et al.

Diverging Preferences: When do Annotators Disagree and do Models Know?

Michael Zhang, Zhilin Wang, Jena Hwang et al.

Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning

Qi Xu, Junyang Zhu, Dongdong Zhou et al.

Active Treatment Effect Estimation via Limited Samples

Zhiheng Zhang, Haoxiang Wang, Haoxuan Li et al.

Random Policy Evaluation Uncovers Policies of Generative Flow Networks

Haoran He, Emmanuel Bengio, Qingpeng Cai et al.

Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization

Duo Liu, Zhiquan Tan, Linglan Zhao et al.

Inductive Gradient Adjustment for Spectral Bias in Implicit Neural Representations

Kexuan Shi, Hai Chen, Leheng Zhang et al.

Learning Efficient Robotic Garment Manipulation with Standardization

zhou changshi, Feng Luan, hujiarui et al.

Efficient Heterogeneity-Aware Federated Active Data Selection

Yingpeng Tang, Chao Ren, Xiaoli Tang et al.

Preconditioned Riemannian Gradient Descent Algorithm for Low-Multilinear-Rank Tensor Completion

Yuanwei Zhang, Fengmiao Bian, Xiaoqun Zhang et al.

Grammar-Forced Translation of Natural Language to Temporal Logic using LLMs

William English, Dominic Simon, Sumit Jha et al.

Equivariant Neural Tangent Kernels

Philipp Misof, Pan Kessel, Jan Gerken

Empowering World Models with Reflection for Embodied Video Prediction

Xiaowei Chi, Chun-Kai Fan, Hengyuan Zhang et al.

LoRA-Gen: Specializing Large Language Model via Online LoRA Generation

Yicheng Xiao, Lin Song, Rui Yang et al.

Protein Structure Tokenization: Benchmarking and New Recipe

Xinyu Yuan, Zichen Wang, Marcus Collins et al.

How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects

Wonkwang Lee, Jongwon Jeong, Taehong Moon et al.

Tensorized Multi-View Multi-Label Classification via Laplace Tensor Rank

Qiyu Zhong, Yi Shan, Haobo Wang et al.

Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding

Tian Jin, Ellie Cheng, Zachary Ankner et al.

Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Bart Bussmann, Noa Nabeshima, Adam Karvonen et al.

Grokking in the Wild: Data Augmentation for Real-World Multi-Hop Reasoning with Transformers

Roman Abramov, Felix Steinbauer, Gjergji Kasneci

Code-Generated Graph Representations Using Multiple LLM Agents for Material Properties Prediction

Jiao Huang, Qianli Xing, Jinglong Ji et al.

FeatSharp: Your Vision Model Features, Sharper

Mike Ranzinger, Greg Heinrich, Pavlo Molchanov et al.

Private Lossless Multiple Release

Joel Daniel Andersson, Lukas Retschmeier, Boel Nelson et al.

Disentangling and Integrating Relational and Sensory Information in Transformer Architectures

Awni Altabaa, John Lafferty

Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning

Zeyu Gan, Yun Liao, Yong Liu

Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models

Samira Abnar, Harshay Shah, Dan Busbridge et al.

A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents

Kaiwen Wang, Dawen Liang, Nathan Kallus et al.

LIMEFLDL: A Local Interpretable Model-Agnostic Explanations Approach for Label Distribution Learning

Xiuyi Jia, Jinchi Li, Yunan Lu et al.

Hardware and Software Platform Inference

Cheng Zhang, Hanna Foerster, Robert Mullins et al.

Nonlinearly Preconditioned Gradient Methods under Generalized Smoothness

Konstantinos Oikonomidis, Jan Quan, Emanuel Laude et al.

What Limits Bidirectional Model's Generative Capabilities? A Uni-Bi-Directional Mixture-of-Expert Method For Bidirectional Fine-tuning

Zuchao Li, Yonghua Hei, Qiwei Li et al.

How to Evaluate and Mitigate IP Infringement in Visual Generative AI?

Zhenting Wang, Chen Chen, Vikash Sehwag et al.

Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing

Zhuoran Zhang, Yongxiang Li, Zijian Kan et al.

On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization

Undral Byambadalai, Tomu Hirata, Tatsushi Oka et al.