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
ProSec: Fortifying Code LLMs with Proactive Security Alignment
Xiangzhe Xu, Zian Su, Jinyao Guo, Kaiyuan Zhang, Zhenting Wang, Xiangyu Zhang
Ranking Unraveled: Recipes for LLM Rankings in Head-to-Head AI Combat
Roland Daynauth, Christopher Clarke, Krisztian Flautner, Lingjia Tang, Jason Mars
Probing the Capacity of Language Model Agents to Operationalize Disparate Experiential Context Despite Distraction
Sonny George, Chris Sypherd, Dylan Cashman
Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus
Terufumi Morishita, Gaku Morio, Atsuki Yamaguchi, Yasuhiro Sogawa
AI Flow at the Network Edge
Jiawei Shao, Xuelong Li
Guide-to-Explain for Controllable Summarization
Sangwon Ryu, Heejin Do, Daehee Kim, Yunsu Kim, Gary Geunbae Lee, Jungseul Ok
\textsc{Neon}: News Entity-Interaction Extraction for Enhanced Question Answering
Sneha Singhania, Silviu Cucerzan, Allen Herring, Sujay Kumar Jauhar
GRL-Prompt: Towards Knowledge Graph based Prompt Optimization via Reinforcement Learning
Yuze Liu, Tingjie Liu, Tiehua Zhang, Youhua Xia, Jinze Wang, Zhishu Shen, Jiong Jin, Fei Richard Yu
RedPajama: an Open Dataset for Training Large Language Models
Maurice Weber, Daniel Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
CUE-M: Contextual Understanding and Enhanced Search with Multimodal Large Language Model
Dongyoung Go, Taesun Whang, Chanhee Lee, Hwa-Yeon Kim, Sunghoon Park, Seunghwan Ji, Jinho Kim, Dongchan Kim, Young-Bum Kim
Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers
Tiberiu Musat
Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods
Jai Doshi, Asa Cooper Stickland
Large Language Model for Qualitative Research -- A Systematic Mapping Study
Cauã Ferreira Barros, Bruna Borges Azevedo, Valdemar Vicente Graciano Neto, Mohamad Kassab, Marcos Kalinowski, Hugo Alexandre D. do Nascimento, Michelle C.G.S.P. Bandeira
Popular LLMs Amplify Race and Gender Disparities in Human Mobility
Xinhua Wu, Qi R. Wang
ByteScience: Bridging Unstructured Scientific Literature and Structured Data with Auto Fine-tuned Large Language Model in Token Granularity
Tong Xie, Hanzhi Zhang, Shaozhou Wang, Yuwei Wan, Imran Razzak, Chunyu Kit, Wenjie Zhang, Bram Hoex
Understanding Chain-of-Thought in LLMs through Information Theory
Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu
Bi-Mamba: Towards Accurate 1-Bit State Space Models
Shengkun Tang, Liqun Ma, Haonan Li, Mingjie Sun, Zhiqiang Shen
Tackling prediction tasks in relational databases with LLMs
Marek Wydmuch, Łukasz Borchmann, Filip Graliński
LLM-IE: A Python Package for Generative Information Extraction with Large Language Models
Enshuo Hsu, Kirk Roberts