Large Language
Large language models (LLMs) are rapidly advancing artificial intelligence, aiming to create systems capable of understanding and generating human-like text. Current research focuses on improving efficiency (e.g., through speculative decoding), exploring their intriguing properties in multimodal contexts (combining language with vision), and applying them to diverse fields like healthcare, manufacturing, and software engineering. This work is significant because LLMs are already impacting various sectors, offering potential for improved decision-making, automation, and personalized experiences, while also raising important questions about robustness, security, and ethical implications.
Papers
SuffixDecoding: A Model-Free Approach to Speeding Up Large Language Model Inference
Gabriele Oliaro, Zhihao Jia, Daniel Campos, Aurick Qiao
Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability
Yanjun Gao, Skatje Myers, Shan Chen, Dmitriy Dligach, Timothy A Miller, Danielle Bitterman, Guanhua Chen, Anoop Mayampurath, Matthew Churpek, Majid Afshar
Best Practices for Distilling Large Language Models into BERT for Web Search Ranking
Dezhi Ye, Junwei Hu, Jiabin Fan, Bowen Tian, Jie Liu, Haijin Liang, Jin Ma
Variational Low-Rank Adaptation Using IVON
Bai Cong, Nico Daheim, Yuesong Shen, Daniel Cremers, Rio Yokota, Mohammad Emtiyaz Khan, Thomas Möllenhoff
AI Metropolis: Scaling Large Language Model-based Multi-Agent Simulation with Out-of-order Execution
Zhiqiang Xie, Hao Kang, Ying Sheng, Tushar Krishna, Kayvon Fatahalian, Christos Kozyrakis
The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare
Souren Pashangpour, Goldie Nejat
ReSpAct: Harmonizing Reasoning, Speaking, and Acting Towards Building Large Language Model-Based Conversational AI Agents
Vardhan Dongre, Xiaocheng Yang, Emre Can Acikgoz, Suvodip Dey, Gokhan Tur, Dilek Hakkani-Tür
LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering
Nikita Severin, Aleksei Ziablitsev, Yulia Savelyeva, Valeriy Tashchilin, Ivan Bulychev, Mikhail Yushkov, Artem Kushneruk, Amaliya Zaryvnykh, Dmitrii Kiselev, Andrey Savchenko, Ilya Makarov
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood
Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback
Qinqing Zheng, Mikael Henaff, Amy Zhang, Aditya Grover, Brandon Amos
A Comprehensive Study on Quantization Techniques for Large Language Models
Jiedong Lang, Zhehao Guo, Shuyu Huang
Large Language Model-assisted Speech and Pointing Benefits Multiple 3D Object Selection in Virtual Reality
Junlong Chen, Jens Grubert, Per Ola Kristensson
Large Language Model-Guided Prediction Toward Quantum Materials Synthesis
Ryotaro Okabe, Zack West, Abhijatmedhi Chotrattanapituk, Mouyang Cheng, Denisse Córdova Carrizales, Weiwei Xie, Robert J. Cava, Mingda Li