NEURIPS Spotlight Papers
670 papers found • Page 1 of 14
$\Psi$-Sampler: Initial Particle Sampling for SMC-Based Inference-Time Reward Alignment in Score Models
Taehoon Yoon, Yunhong Min, Kyeongmin Yeo et al.
3D Equivariant Visuomotor Policy Learning via Spherical Projection
Boce Hu, Dian Wang, David Klee et al.
3D Interaction Geometric Pre-training for Molecular Relational Learning
Namkyeong Lee, Yunhak Oh, Heewoong Noh et al.
4DGT: Learning a 4D Gaussian Transformer Using Real-World Monocular Videos
Zhen Xu, Zhengqin Li, Zhao Dong et al.
Absence Bench: Language Models Can’t See What’s Missing
Harvey Yiyun Fu, Aryan Shrivastava, Jared Moore et al.
Absolute Zero: Reinforced Self-play Reasoning with Zero Data
Andrew Zhao, Yiran Wu, Yang Yue et al.
Abstract Rendering: Certified Rendering Under 3D Semantic Uncertainty
Chenxi Ji, Yangge Li, Xiangru Zhong et al.
Accelerating data-driven algorithm selection for combinatorial partitioning problems
Vaggos Chatziafratis, Ishani Karmarkar, Yingxi Li et al.
Accelerating Diffusion LLMs via Adaptive Parallel Decoding
Daniel Israel, Guy Van den Broeck, Aditya Grover
Accelerating Optimization via Differentiable Stopping Time
Zhonglin Xie, Yiman Fong, Haoran Yuan et al.
Accelerating Visual-Policy Learning through Parallel Differentiable Simulation
Haoxiang You, Yilang Liu, Ian Abraham
AceSearcher: Bootstrapping Reasoning and Search for LLMs via Reinforced Self-Play
Ran Xu, Yuchen Zhuang, Zihan Dong et al.
Achieving $\tilde{\mathcal{O}}(1/N)$ Optimality Gap in Restless Bandits through Gaussian Approximation
Chen YAN, Weina Wang, Lei Ying
Achilles' Heel of Mamba: Essential difficulties of the Mamba architecture demonstrated by synthetic data
Tianyi Chen, Pengxiao Lin, Zhiwei Wang et al.
A Closer Look at Graph Transformers: Cross-Aggregation and Beyond
Jiaming Zhuo, Ziyi Ma, Yintong Lu et al.
A Closer Look at Model Collapse: From a Generalization-to-Memorization Perspective
Lianghe Shi, Meng Wu, Huijie Zhang et al.
A Controllable Examination for Long-Context Language Models
Yijun Yang, Zeyu Huang, Wenhao Zhu et al.
Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models
Zekai Zhao, Qi Liu, Kun Zhou et al.
Adaptive 3D Reconstruction via Diffusion Priors and Forward Curvature-Matching Likelihood Updates
Seunghyeok Shin, Dabin Kim, Hongki Lim
Adaptive Defense against Harmful Fine-Tuning for Large Language Models via Bayesian Data Scheduler
Zixuan Hu, Li Shen, Zhenyi Wang et al.
Adaptive Neighborhood-Constrained Q Learning for Offline Reinforcement Learning
Yixiu Mao, Yun Qu, Qi Wang et al.
Adaptive Prediction-Powered AutoEval with Reliability and Efficiency Guarantees
Sangwoo Park, Matteo Zecchin, Osvaldo Simeone
AdaReasoner: Adaptive Reasoning Enables More Flexible Thinking
Xiangqi Wang, Yue Huang, Yanbo Wang et al.
AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
Yuezhou Hu, Jiaxin Guo, Xinyu Feng et al.
Affine-Invariant Global Non-Asymptotic Convergence Analysis of BFGS under Self-Concordance
Qiujiang Jin, Aryan Mokhtari
AgentBreeder: Mitigating the AI Safety Risks of Multi-Agent Scaffolds via Self-Improvement
J Rosser, Jakob Foerster
AGENTIF: Benchmarking Large Language Models Instruction Following Ability in Agentic Scenarios
Yunjia Qi, Hao Peng, Xiaozhi Wang et al.
AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems
Yu Shang, Peijie Liu, Yuwei Yan et al.
Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations
Olawale Salaudeen, Haoran Zhang, Kumail Alhamoud et al.
Agnostic Learning under Targeted Poisoning: Optimal Rates and the Role of Randomness
Bogdan Chornomaz, Yonatan Koren, Shay Moran et al.
A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning
Guan Zhe Hong, Nishanth Dikkala, Enming Luo et al.
AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench
Edan Toledo, Karen Hambardzumyan, Martin Josifoski et al.
AI-Researcher: Autonomous Scientific Innovation
Jiabin Tang, Lianghao Xia, Zhonghang Li et al.
A learnability analysis on neuro-symbolic learning
Hao-Yuan He, Ming LI
Algorithms and SQ Lower Bounds for Robustly Learning Real-valued Multi-Index Models
Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane et al.
Aligning Text-to-Image Diffusion Models to Human Preference by Classification
Longquan Dai, Xiaolu Wei, wang he et al.
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
Daolang Huang, Xinyi Wen, Ayush Bharti et al.
Alligat0R: Pre-Training through Covisibility Segmentation for Relative Camera Pose Regression
Thibaut Loiseau, Guillaume Bourmaud, Vincent Lepetit
AlphaZero Neural Scaling and Zipf's Law: a Tale of Board Games and Power Laws
Oren Neumann, Claudius Gros
A machine learning approach that beats Rubik's cubes
Alexander Chervov, Kirill Khoruzhii, Nikita Bukhal et al.
Ambient Diffusion Omni: Training Good Models with Bad Data
Giannis Daras, Adrian Rodriguez-Munoz, Adam Klivans et al.
Ambient Proteins - Training Diffusion Models on Noisy Structures
Giannis Daras, Jeffrey Ouyang-Zhang, Krithika Ravishankar et al.
Among Us: A Sandbox for Measuring and Detecting Agentic Deception
Satvik Golechha, Adrià Garriga-Alonso
Amortized Variational Transdimensional Inference
Laurence Davies, Daniel MacKinlay, Rafael Oliveira et al.
AnaCP: Toward Upper-Bound Continual Learning via Analytic Contrastive Projection
Saleh Momeni, Changnan Xiao, Bing Liu
An Analysis of Causal Effect Estimation using Outcome Invariant Data Augmentation
Uzair Akbar, Niki Kilbertus, Hao Shen et al.
An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models
Binxu Wang, Cengiz Pehlevan
A Near-Optimal Algorithm for Decentralized Convex-Concave Finite-Sum Minimax Optimization
Hongxu Chen, Ke Wei, Haishan Ye et al.
An Efficient Orlicz-Sobolev Approach for Transporting Unbalanced Measures on a Graph
Tam Le, Truyen Nguyen, Hideitsu Hino et al.
An Evidence-Based Post-Hoc Adjustment Framework for Anomaly Detection Under Data Contamination
Sukanya Patra, Souhaib Ben Taieb