NeurIPS "large language models" Papers
181 papers found • Page 3 of 4
ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models
Zhuo Chen, YIZHEN ZHENG, Huan Yee Koh et al.
More of the Same: Persistent Representational Harms Under Increased Representation
Jennifer Mickel, Maria De-Arteaga, Liu Leqi et al.
Multi-Agent Collaboration via Evolving Orchestration
Yufan Dang, Chen Qian, Xueheng Luo et al.
No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization
Wenhang Shi, Yiren Chen, Shuqing Bian et al.
Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
Subhojyoti Mukherjee, Viet Lai, Raghavendra Addanki et al.
One Filters All: A Generalist Filter For State Estimation
Shiqi Liu, Wenhan Cao, Chang Liu et al.
Optimization Inspired Few-Shot Adaptation for Large Language Models
Boyan Gao, Xin Wang, Yibo Yang et al.
PANORAMA: A Dataset and Benchmarks Capturing Decision Trails and Rationales in Patent Examination
Hyunseung Lim, Sooyohn Nam, Sungmin Na et al.
ParamMute: Suppressing Knowledge-Critical FFNs for Faithful Retrieval-Augmented Generation
Pengcheng Huang, Zhenghao Liu, Yukun Yan et al.
Perceive Anything: Recognize, Explain, Caption, and Segment Anything in Images and Videos
Weifeng Lin, Xinyu Wei, Ruichuan An et al.
PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models
Shi Qiu, Shaoyang Guo, Zhuo-Yang Song et al.
PlanU: Large Language Model Reasoning through Planning under Uncertainty
Ziwei Deng, Mian Deng, Chenjing Liang et al.
Preference-driven Knowledge Distillation for Few-shot Node Classification
Xing Wei, Chunchun Chen, Rui Fan et al.
Private Training Large-scale Models with Efficient DP-SGD
Liangyu Wang, Junxiao Wang, Jie Ren et al.
Probabilistic Reasoning with LLMs for Privacy Risk Estimation
Jonathan Zheng, Alan Ritter, Sauvik Das et al.
Probabilistic Token Alignment for Large Language Model Fusion
Runjia Zeng, James Liang, Cheng Han et al.
Progress Reward Model for Reinforcement Learning via Large Language Models
Xiuhui Zhang, Ning Gao, Xingyu Jiang et al.
Prompting as Scientific Inquiry
Ari Holtzman, Chenhao Tan
PseuZO: Pseudo-Zeroth-Order Algorithm for Training Deep Neural Networks
Pengyun Yue, Xuanlin Yang, Mingqing Xiao et al.
Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning
Arian Raje, Baris Askin, Divyansh Jhunjhunwala et al.
Reasoning Models Better Express Their Confidence
Dongkeun Yoon, Seungone Kim, Sohee Yang et al.
Reinforcement Learning with Backtracking Feedback
Bilgehan Sel, Vaishakh Keshava, Phillip Wallis et al.
Reliable Decision‑Making via Calibration‑Oriented Retrieval‑Augmented Generation
Chaeyun Jang, Deukhwan Cho, Seanie Lee et al.
ReMA: Learning to Meta-Think for LLMs with Multi-agent Reinforcement Learning
Ziyu Wan, Yunxiang Li, Xiaoyu Wen et al.
Representation Consistency for Accurate and Coherent LLM Answer Aggregation
Junqi Jiang, Tom Bewley, Salim I. Amoukou et al.
RESAnything: Attribute Prompting for Arbitrary Referring Segmentation
Ruiqi Wang, Hao Zhang
ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning
Mingyang Chen, Linzhuang Sun, Tianpeng Li et al.
Rethinking Residual Distribution in Locate-then-Edit Model Editing
Xiaopeng Li, Shangwen Wang, Shasha Li et al.
Revising and Falsifying Sparse Autoencoder Feature Explanations
George Ma, Samuel Pfrommer, Somayeh Sojoudi
Revolutionizing Training-Free NAS: Towards Efficient Automatic Proxy Discovery via Large Language Models
Haidong Kang, Lihong Lin, Hanling Wang
RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility
Haoyu He, Haozheng Luo, Yan Chen et al.
Risk-aware Direct Preference Optimization under Nested Risk Measure
Lijun Zhang, Lin Li, Yajie Qi et al.
Robust Hallucination Detection in LLMs via Adaptive Token Selection
Mengjia Niu, Hamed Haddadi, Guansong Pang
RSAVQ: Riemannian Sensitivity-Aware Vector Quantization for Large Language Models
Zukang Xu, Xing Hu, Qiang Wu et al.
rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset
Yifei Liu, Li Lyna Zhang, Yi Zhu et al.
Scaling and context steer LLMs along the same computational path as the human brain
Joséphine Raugel, Jérémy Rapin, Stéphane d'Ascoli et al.
scPilot: Large Language Model Reasoning Toward Automated Single-Cell Analysis and Discovery
Yiming Gao, Zhen Wang, Jefferson Chen et al.
Self-Evolving Pseudo-Rehearsal for Catastrophic Forgetting with Task Similarity in LLMs
Jun Wang, Liang Ding, Shuai Wang et al.
Self Iterative Label Refinement via Robust Unlabeled Learning
Hikaru Asano, Tadashi Kozuno, Yukino Baba
Self-Verification Provably Prevents Model Collapse in Recursive Synthetic Training
Shi Fu, Yingjie Wang, Yuzhu Chen et al.
SeRL: Self-play Reinforcement Learning for Large Language Models with Limited Data
Wenkai Fang, Shunyu Liu, Yang Zhou et al.
ShiQ: Bringing back Bellman to LLMs
Pierre Clavier, Nathan Grinsztajn, Raphaël Avalos et al.
Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical Evidence
Shaopeng Fu, Liang Ding, Jingfeng ZHANG et al.
SilentStriker: Toward Stealthy Bit-Flip Attacks on Large Language Models
HAOTIAN XU, Qingsong Peng, Jie Shi et al.
Simulating Society Requires Simulating Thought
Chance Jiajie Li, Jiayi Wu, Zhenze MO et al.
SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning
Wanjia Zhao, Mert Yuksekgonul, Shirley Wu et al.
S'MoRE: Structural Mixture of Residual Experts for Parameter-Efficient LLM Fine-tuning
Hanqing Zeng, Yinglong Xia, Zhuokai Zhao et al.
Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling
Yitian Chen, Jingfan Xia, Siyu Shao et al.
Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning
Yong Liu, Zirui Zhu, Chaoyu Gong et al.
SSTAG: Structure-Aware Self-Supervised Learning Method for Text-Attributed Graphs
Ruyue Liu, Rong Yin, Xiangzhen Bo et al.