NeurIPS 2025 "large language models" Papers

$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning

Xiaojun Guo, Ang Li, Yifei Wang et al.

Accelerating Block Coordinate Descent for LLM Finetuning via Landscape Expansion

Qijun Luo, Yifei Shen, Liangzu Peng et al.

AcuRank: Uncertainty-Aware Adaptive Computation for Listwise Reranking

Soyoung Yoon, Gyuwan Kim, Gyu-Hwung Cho et al.

AdaLRS: Loss-Guided Adaptive Learning Rate Search for Efficient Foundation Model Pretraining

Hongyuan Dong, Dingkang Yang, Xiao Liang et al.

Adaptive Distraction: Probing LLM Contextual Robustness with Automated Tree Search

Yanbo Wang, Zixiang Xu, Yue Huang et al.

AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees

Yangning Li, Shaoshen Chen, Yinghui Li et al.

AgentTTS: Large Language Model Agent for Test-time Compute-optimal Scaling Strategy in Complex Tasks

Fali Wang, Hui Liu, Zhenwei Dai et al.

A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning

Guan Zhe Hong, Nishanth Dikkala, Enming Luo et al.

Alignment of Large Language Models with Constrained Learning

Botong Zhang, Shuo Li, Ignacio Hounie et al.

Alleviating Hallucinations in Large Language Models through Multi-Model Contrastive Decoding and Dynamic Hallucination Detection

Chenyu Zhu, Yefeng Liu, Hao Zhang et al.

AlphaDecay: Module-wise Weight Decay for Heavy-Tailed Balancing in LLMs

Di He, Songjun Tu, Ajay Jaiswal et al.

Analyzing the Power of Chain of Thought through Memorization Capabilities

Lijia Yu, Xiao-Shan Gao, Lijun Zhang

ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data

Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang et al.

AutoDiscovery: Open-ended Scientific Discovery via Bayesian Surprise

Dhruv Agarwal, Bodhisattwa Prasad Majumder, Reece Adamson et al.

Automatic Auxiliary Task Selection and Adaptive Weighting Boost Molecular Property Prediction

Zhiqiang Zhong, Davide Mottin

AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration

Andy Zhou, Kevin Wu, Francesco Pinto et al.

Bits Leaked per Query: Information-Theoretic Bounds for Adversarial Attacks on LLMs

Masahiro Kaneko, Timothy Baldwin

Boosting Skeleton-based Zero-Shot Action Recognition with Training-Free Test-Time Adaptation

Jingmin Zhu, Anqi Zhu, Hossein Rahmani et al.

Bridging Sign and Spoken Languages: Pseudo Gloss Generation for Sign Language Translation

Jianyuan Guo, Peike Li, Trevor Cohn

Calibrating Translation Decoding with Quality Estimation on LLMs

Di Wu, Yibin Lei, Christof Monz

Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation

Qijiong Liu, Jieming Zhu, Lu Fan et al.

Can LLMs Reason Over Non-Text Modalities in a Training-Free Manner? A Case Study with In-Context Representation Learning

Tianle Zhang, Wanlong Fang, Jonathan Woo et al.

Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework

Laura Kopf, Nils Feldhus, Kirill Bykov et al.

Classical Planning with LLM-Generated Heuristics: Challenging the State of the Art with Python Code

Augusto B. Corrêa, André G. Pereira, Jendrik Seipp

ClinBench: A Standardized Multi-Domain Framework for Evaluating Large Language Models in Clinical Information Extraction

Ismael Villanueva Miranda, Zifan Gu, Donghan Yang et al.

Computation and Memory-Efficient Model Compression with Gradient Reweighting

Zhiwei Li, Yuesen Liao, Binrui Wu et al.

Concept-Guided Interpretability via Neural Chunking

Shuchen Wu, Stephan Alaniz, Shyamgopal Karthik et al.

Concept Incongruence: An Exploration of Time and Death in Role Playing

Xiaoyan Bai, Ike Peng, Aditya Singh et al.

ConfTuner: Training Large Language Models to Express Their Confidence Verbally

Yibo Li, Miao Xiong, Jiaying Wu et al.

ConTextTab: A Semantics-Aware Tabular In-Context Learner

Marco Spinaci, Marek Polewczyk, Maximilian Schambach et al.

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles

Chen Xiong, Pin-Yu Chen, Tsung-Yi Ho

DanmakuTPPBench: A Multi-modal Benchmark for Temporal Point Process Modeling and Understanding

Yue Jiang, Jichu Li, Yang Liu et al.

DataSIR: A Benchmark Dataset for Sensitive Information Recognition

Fan Mo, Bo Liu, Yuan Fan et al.

Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing

Yisong Xiao, Aishan Liu, Siyuan Liang et al.

DEXTER: Diffusion-Guided EXplanations with TExtual Reasoning for Vision Models

Simone Carnemolla, Matteo Pennisi, Sarinda Samarasinghe et al.

Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix

Ming Wen, Jiaqi Zhu, Yuedong Xu et al.

Direct Numerical Layout Generation for 3D Indoor Scene Synthesis via Spatial Reasoning

Xingjian Ran, Yixuan Li, Linning Xu et al.

Distribution-Aligned Decoding for Efficient LLM Task Adaptation

Senkang Hu, Xudong Han, Jinqi Jiang et al.

Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness

Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu et al.

Don’t Forget the Enjoin: FocalLoRA for Instruction Hierarchical Alignment in Large Language Models

Zitong Shi, Guancheng Wan, Haixin Wang et al.

Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data

Shlomi Hod, Lucas Rosenblatt, Julia Stoyanovich

DSAS: A Universal Plug-and-Play Framework for Attention Optimization in Multi-Document Question Answering

Jiakai Li, Rongzheng Wang, Yizhuo Ma et al.

Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward

Yanming Wan, Jiaxing Wu, Marwa Abdulhai et al.

Exploring the limits of strong membership inference attacks on large language models

Jamie Hayes, I Shumailov, Christopher A. Choquette-Choo et al.

FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic

FFN Fusion: Rethinking Sequential Computation in Large Language Models

Akhiad Bercovich, Mohammed Dabbah, Omri Puny et al.

FP4 All the Way: Fully Quantized Training of Large Language Models

Brian Chmiel, Maxim Fishman, Ron Banner et al.

From Programs to Poses: Factored Real-World Scene Generation via Learned Program Libraries

Joy Hsu, Emily Jin, Jiajun Wu et al.

Generating Computational Cognitive models using Large Language Models

Milena Rmus, Akshay Kumar Jagadish, Marvin Mathony et al.

Generator-Mediated Bandits: Thompson Sampling for GenAI-Powered Adaptive Interventions

Marc Brooks, Gabriel Durham, Kihyuk Hong et al.