Poster "large language models" Papers
740 papers found • Page 1 of 15
Conference
$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
Xiaojun Guo, Ang Li, Yifei Wang et al.
3D-AffordanceLLM: Harnessing Large Language Models for Open-Vocabulary Affordance Detection in 3D Worlds
Hengshuo Chu, Xiang Deng, Qi Lv et al.
A$^3$E: Towards Compositional Model Editing
Hongming Piao, Hao Wang, Dapeng Wu et al.
ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration
Andrew Estornell, Jean-Francois Ton, Yuanshun Yao et al.
Accelerating Block Coordinate Descent for LLM Finetuning via Landscape Expansion
Qijun Luo, Yifei Shen, Liangzu Peng et al.
Accelerating RL for LLM Reasoning with Optimal Advantage Regression
Kianté Brantley, Mingyu Chen, Zhaolin Gao et al.
A Closer Look at Machine Unlearning for Large Language Models
Xiaojian Yuan, Tianyu Pang, Chao Du et al.
ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints
Divij Handa, Pavel Dolin, Shrinidhi Kumbhar et al.
Activation-Guided Consensus Merging for Large Language Models
Yuxuan Yao, Shuqi LIU, Zehua Liu et al.
AcuRank: Uncertainty-Aware Adaptive Computation for Listwise Reranking
Soyoung Yoon, Gyuwan Kim, Gyu-Hwung Cho et al.
Ada-K Routing: Boosting the Efficiency of MoE-based LLMs
Zijia Zhao, Longteng Guo, Jie Cheng 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.
Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
Richard Suwandi, Feng Yin, Juntao Wang et al.
Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models
Zeman Li, Xinwei Zhang, Peilin Zhong et al.
AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees
Yangning Li, Shaoshen Chen, Yinghui Li et al.
Advancing LLM Reasoning Generalists with Preference Trees
Lifan Yuan, Ganqu Cui, Hanbin Wang et al.
AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
Anselm Paulus, Arman Zharmagambetov, Chuan Guo et al.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Mingzhe Du, Anh Tuan Luu, Yue Liu et al.
Agents' Room: Narrative Generation through Multi-step Collaboration
Fantine Huot, Reinald Kim Amplayo, Jennimaria Palomaki 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.
AI as Humanity’s Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text
Ximing Lu, Melanie Sclar, Skyler Hallinan et al.
AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements
Adriana-Eufrosina Bora, Pierre-Luc St-Charles, Mirko Bronzi et al.
Alignment of Large Language Models with Constrained Learning
Botong Zhang, Shuo Li, Ignacio Hounie et al.
ALLaM: Large Language Models for Arabic and English
M Saiful Bari, Yazeed Alnumay, Norah Alzahrani 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.
A Multi-Power Law for Loss Curve Prediction Across Learning Rate Schedules
Kairong Luo, Haodong Wen, Shengding Hu et al.
Analyzing the Power of Chain of Thought through Memorization Capabilities
Lijia Yu, Xiao-Shan Gao, Lijun Zhang
An Intelligent Agentic System for Complex Image Restoration Problems
Kaiwen Zhu, Jinjin Gu, Zhiyuan You et al.
AnoLLM: Large Language Models for Tabular Anomaly Detection
Che-Ping Tsai, Ganyu Teng, Phillip Wallis et al.
API Pack: A Massive Multi-Programming Language Dataset for API Call Generation
Gavin (Zhen) Guo, Adriana Meza Soria, Wei Sun et al.
Approximately Aligned Decoding
Daniel Melcer, Sujan Kumar Gonugondla, Pramuditha Perera et al.
A Probabilistic Perspective on Unlearning and Alignment for Large Language Models
Yan Scholten, Stephan Günnemann, Leo Schwinn
AREAL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning
Wei Fu, Jiaxuan Gao, Xujie Shen et al.
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni, Josh Engels, Senthooran Rajamanoharan et al.
A Simple yet Effective Layout Token in Large Language Models for Document Understanding
Zhaoqing Zhu, Chuwei Luo, Zirui Shao et al.
Ask, and it shall be given: On the Turing completeness of prompting
Ruizhong Qiu, Zhe Xu, Wenxuan Bao et al.
A Statistical Approach for Controlled Training Data Detection
Zirui Hu, Yingjie Wang, Zheng Zhang et al.
ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data
Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang et al.
A Training-Free Sub-quadratic Cost Transformer Model Serving Framework with Hierarchically Pruned Attention
Heejun Lee, Geon Park, Youngwan Lee et al.
AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution
Fengyuan Liu, Nikhil Kandpal, Colin Raffel
AutoData: A Multi-Agent System for Open Web Data Collection
Tianyi Ma, Yiyue Qian, Zheyuan Zhang et al.
Automatic Auxiliary Task Selection and Adaptive Weighting Boost Molecular Property Prediction
Zhiqiang Zhong, Davide Mottin
Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks
Rushang Karia, Daniel Bramblett, Daksh Dobhal et al.
AutoPrompt: Automated Red-Teaming of Text-to-Image Models via LLM-Driven Adversarial Prompts
Yufan Liu, Wanqian Zhang, Huashan Chen et al.
AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration
Andy Zhou, Kevin Wu, Francesco Pinto et al.
Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression
Jingcun Wang, Yu-Guang Chen, Ing-Chao Lin et al.
Bayesian Concept Bottleneck Models with LLM Priors
Jean Feng, Avni Kothari, Lucas Zier et al.
Better autoregressive regression with LLMs via regression-aware fine-tuning
Michal Lukasik, Zhao Meng, Harikrishna Narasimhan et al.