Large Language Model
Large language models (LLMs) are sophisticated AI systems designed to process and generate human-like text, aiming to improve various natural language processing tasks. Current research focuses on enhancing LLM safety, efficiency (through techniques like quantization and optimized decoding), and fairness, as well as improving their ability to perform complex reasoning and handle diverse instructions. These advancements are significant because they address critical limitations in current LLMs and pave the way for broader applications across diverse fields, including healthcare, legal tech, and autonomous systems.
Papers
Reliable, Reproducible, and Really Fast Leaderboards with Evalica
Dmitry Ustalov
TrimLLM: Progressive Layer Dropping for Domain-Specific LLMs
Lanxiang Hu, Tajana Rosing, Hao Zhang
RIRO: Reshaping Inputs, Refining Outputs Unlocking the Potential of Large Language Models in Data-Scarce Contexts
Ali Hamdi, Hozaifa Kassab, Mohamed Bahaa, Marwa Mohamed
Task-Oriented Dialog Systems for the Senegalese Wolof Language
Derguene Mbaye, Moussa Diallo
GaLore$+$: Boosting Low-Rank Adaptation for LLMs with Cross-Head Projection
Xutao Liao, Shaohui Li, Yuhui Xu, Zhi Li, Yu Liu, You He
The Superalignment of Superhuman Intelligence with Large Language Models
Minlie Huang, Yingkang Wang, Shiyao Cui, Pei Ke, Jie Tang
Empowering LLMs to Understand and Generate Complex Vector Graphics
Ximing Xing, Juncheng Hu, Guotao Liang, Jing Zhang, Dong Xu, Qian Yu
HC-LLM: Historical-Constrained Large Language Models for Radiology Report Generation
Tengfei Liu, Jiapu Wang, Yongli Hu, Mingjie Li, Junfei Yi, Xiaojun Chang, Junbin Gao, Baocai Yin
Separate the Wheat from the Chaff: A Post-Hoc Approach to Safety Re-Alignment for Fine-Tuned Language Models
Di Wu, Xin Lu, Yanyan Zhao, Bing Qin
Embracing Large Language Models in Traffic Flow Forecasting
Yusheng Zhao, Xiao Luo, Haomin Wen, Zhiping Xiao, Wei Ju, Ming Zhang
LLMs for Literature Review: Are we there yet?
Shubham Agarwal, Gaurav Sahu, Abhay Puri, Issam H. Laradji, Krishnamurthy DJ Dvijotham, Jason Stanley, Laurent Charlin, Christopher Pal
MedG-KRP: Medical Graph Knowledge Representation Probing
Gabriel R. Rosenbaum, Lavender Yao Jiang, Ivaxi Sheth, Jaden Stryker, Anton Alyakin, Daniel Alexander Alber, Nicolas K. Goff, Young Joon (Fred) Kwon, John Markert, Mustafa Nasir-Moin, Jan Moritz Niehues, Karl L. Sangwon, Eunice Yang, Eric Karl Oermann
Can LLMs Help Create Grammar?: Automating Grammar Creation for Endangered Languages with In-Context Learning
Piyapath T Spencer, Nanthipat Kongborrirak
Tokens, the oft-overlooked appetizer: Large language models, the distributional hypothesis, and meaning
Julia Witte Zimmerman, Denis Hudon, Kathryn Cramer, Alejandro J. Ruiz, Calla Beauregard, Ashley Fehr, Mikaela Irene Fudolig, Bradford Demarest, Yoshi Meke Bird, Milo Z. Trujillo, Christopher M. Danforth, Peter Sheridan Dodds
Superhuman performance of a large language model on the reasoning tasks of a physician
Peter G. Brodeur, Thomas A. Buckley, Zahir Kanjee, Ethan Goh, Evelyn Bin Ling, Priyank Jain, Stephanie Cabral, Raja-Elie Abdulnour, Adrian Haimovich, Jason A. Freed, Andrew Olson, Daniel J. Morgan, Jason Hom, Robert Gallo, Eric Horvitz, Jonathan Chen, Arjun K. Manrai, Adam Rodman
Large Language Models for Medical Forecasting -- Foresight 2
Zeljko Kraljevic, Joshua Au Yeung, Daniel Bean, James Teo, Richard J. Dobson
Rethinking Chain-of-Thought from the Perspective of Self-Training
Zongqian Wu, Baoduo Xu, Ruochen Cui, Mengmeng Zhan, Xiaofeng Zhu, Lei Feng
FinGPT: Enhancing Sentiment-Based Stock Movement Prediction with Dissemination-Aware and Context-Enriched LLMs
Yixuan Liang, Yuncong Liu, Boyu Zhang, Christina Dan Wang, Hongyang Yang
HITgram: A Platform for Experimenting with n-gram Language Models
Shibaranjani Dasgupta, Chandan Maity, Somdip Mukherjee, Rohan Singh, Diptendu Dutta, Debasish Jana