NEURIPS "large language models" Papers
298 papers found • Page 2 of 6
Classical Planning with LLM-Generated Heuristics: Challenging the State of the Art with Python Code
Augusto B. Corrêa, André G. Pereira, Jendrik Seipp
CLAWS:Creativity detection for LLM-generated solutions using Attention Window of Sections
Keuntae Kim, Eunhye Jeong, Sehyeon Lee et al.
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.
Conditional Representation Learning for Customized Tasks
Honglin Liu, Chao Sun, Peng Hu et al.
Conflict-Aware Knowledge Editing in the Wild: Semantic-Augmented Graph Representation for Unstructured Text
Zhange Zhang, Zhicheng Geng, Yuqing Ma 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
Cost-aware LLM-based Online Dataset Annotation
Eray Can Elumar, Cem Tekin, Osman Yagan
Creativity or Brute Force? Using Brainteasers as a Window into the Problem-Solving Abilities of Large Language Models
Sophia Han, Howard Dai, Stephen Xia et al.
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.
Deep Value Benchmark: Measuring Whether Models Generalize Deep values or Shallow Preferences
Joshua Ashkinaze, Hua Shen, Saipranav Avula et al.
Detecting High-Stakes Interactions with Activation Probes
Alex McKenzie, Urja Pawar, Phil Blandfort 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.
DISCO: Disentangled Communication Steering for Large Language Models
Max Torop, Aria Masoomi, Masih Eskandar et al.
Discovering Important Experts for Mixture-of-Experts Models Pruning Through a Theoretical Perspective
Weizhong Huang, Yuxin Zhang, Xiawu Zheng et al.
Disentangled Concepts Speak Louder Than Words: Explainable Video Action Recognition
Jongseo Lee, Wooil Lee, Gyeong-Moon Park et al.
Distribution-Aligned Decoding for Efficient LLM Task Adaptation
Senkang Hu, Xudong Han, Jinqi Jiang et al.
DNA-DetectLLM: Unveiling AI-Generated Text via a DNA-Inspired Mutation-Repair Paradigm
Xiaowei Zhu, Yubing Ren, Fang Fang et al.
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Yang Yue, Zhiqi Chen, Rui Lu 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.
DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs
Ruokai Yin, Yuhang Li, Donghyun Lee et al.
DynaAct: Large Language Model Reasoning with Dynamic Action Spaces
Xueliang Zhao, Wei Wu, Jian Guan et al.
Dynamic Bundling with Large Language Models for Zero-Shot Inference on Text-Attributed Graphs
Yusheng Zhao, Qixin Zhang, Xiao Luo et al.
DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation
Jiashuo Sun, Xianrui Zhong, Sizhe Zhou et al.
EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test
Yuhui Li, Fangyun Wei, Chao Zhang et al.
Embracing Trustworthy Brain-Agent Collaboration as Paradigm Extension for Intelligent Assistive Technologies
Yankai Chen, Xinni Zhang, Yifei Zhang et al.
Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward
Yanming Wan, Jiaxing Wu, Marwa Abdulhai et al.
Enhancing Safety in Reinforcement Learning with Human Feedback via Rectified Policy Optimization
Xiyue Peng, Hengquan Guo, Jiawei Zhang et al.
ErrorTrace: A Black-Box Traceability Mechanism Based on Model Family Error Space
Chuanchao Zang, Xiangtao Meng, Wenyu Chen et al.
EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving
Shihan Dou, Ming Zhang, Chenhao Huang et al.
Evaluating Program Semantics Reasoning with Type Inference in System $F$
Yifeng He, Luning Yang, Christopher Gonzalo et al.
Every Rollout Counts: Optimal Resource Allocation for Efficient Test-Time Scaling
Xinglin Wang, Yiwei Li, Shaoxiong Feng et al.
Exploring the limits of strong membership inference attacks on large language models
Jamie Hayes, I Shumailov, Christopher A. Choquette-Choo et al.
Factorio Learning Environment
Jack Hopkins, Mart Bakler, Akbir Khan
FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
Kanghyun Choi, Hyeyoon Lee, Sunjong Park et al.
Far from the Shallow: Brain-Predictive Reasoning Embedding through Residual Disentanglement
Linyang He, Tianjun Zhong, Richard Antonello et al.
Few-Shot Knowledge Distillation of LLMs With Counterfactual Explanations
Faisal Hamman, Pasan Dissanayake, Yanjun Fu et al.
FFN Fusion: Rethinking Sequential Computation in Large Language Models
Akhiad Bercovich, Mohammed Dabbah, Omri Puny et al.
Finding and Reactivating Post-Trained LLMs' Hidden Safety Mechanisms
Mingjie Li, Wai Man Si, Michael Backes et al.