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

November 19, 2024

Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus
Terufumi Morishita, Gaku Morio, Atsuki Yamaguchi, Yasuhiro Sogawa
Large Language Model Large Corpus Logical Reasoning Reasoning Path Logical Reasoning Datasets Formal Logic Synthetic Reasoning Logic Pre Training
AI Flow at the Network Edge
Jiawei Shao, Xuelong Li
Large Language Model Information Flow Edge Network Model Inference
Guide-to-Explain for Controllable Summarization
Sangwon Ryu, Heejin Do, Daehee Kim, Yunsu Kim, Gary Geunbae Lee, Jungseul Ok
Large Language Model Structured Summary Abstractive Summarization Linguistic Feature Controllable Summarization
\textsc{Neon}: News Entity-Interaction Extraction for Enhanced Question Answering
Sneha Singhania, Silviu Cucerzan, Allen Herring, Sujay Kumar Jauhar
Large Language Model Yes No Question Open Information Extraction Entity Relation Extraction Entity Centric Query
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
Large Language Model Language Model Open Dataset Open Source Language Model Large Language Model Training Sleep Datasets
CUE-M: Contextual Understanding and Enhanced Search with Multimodal Large Language Model
Dongyoung Go, Taesun Whang, Chanhee Lee, Hwayeon Kim, Sunghoon Park, Seunghwan Ji, Dongchan Kim, Young-Bum Kim
Large Language Model Retrieval Augmented Generation Search Query Query Generation Contextual Understanding Cue Generation Multimodal Search Multimodal Query

November 18, 2024

Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers
Tiberiu Musat
Large Language Model Transformer Megatron Decepticons Reasoning Task Path Breaking Emergence Attention Map Functional Mechanism Multi Head Attention Prompting Strategy
Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods
Jai Doshi, Asa Cooper Stickland
Large Language Model NCD Method Unlearning Framework Harmful Unlearning Model Capability LLM Unlearning Weapon of Mass Destruction Proxy
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 Zhangand Bram Hoex
Large Language Model Natural Language Processing Large Corpus Natural Language Processing Model Unstructured Text Structured Document Scientific Data Token Correlation
Understanding Chain-of-Thought in LLMs through Information Theory
Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu
Large Language Model Chain of Thought Reasoning Task Information Theory
Bi-Mamba: Towards Accurate 1-Bit State Space Models
Shengkun Tang, Liqun Ma, Haonan Li, Mingjie Sun, Zhiqiang Shen
Large Language Model State Space Model Inference Memory Usage Autoregressive Distillation
Tackling prediction tasks in relational databases with LLMs
Marek Wydmuch, Łukasz Borchmann, Filip Graliński
Large Language Model Prediction Task Relational Database Relation Information
LLM-IE: A Python Package for Generative Information Extraction with Large Language Models
Enshuo Hsu, Kirk Roberts
Large Language Model Medical LLM Entity Recognition Python Library Generative Information Extraction
BitMoD: Bit-serial Mixture-of-Datatype LLM Acceleration
Yuzong Chen, Ahmed F. AbouElhamayed, Xilai Dai, Yang Wang, Marta Andronic, George A. Constantinides, Mohamed S. Abdelfattah
Large Language Model LLM Quantization
Moral Persuasion in Large Language Models: Evaluating Susceptibility and Ethical Alignment
Allison Huang, Yulu Niki Pi, Carlos Mougan
Large Language Model Moral Dilemma Persuasive Capability
Technical Report: Enhancing LLM Reasoning with Reward-guided Tree Search
Jinhao Jiang, Zhipeng Chen, Yingqian Min, Jie Chen, Xiaoxue Cheng, Jiapeng Wang, Yiru Tang, Haoxiang Sun, Jia Deng, Wayne Xin Zhao, Zheng Liu, Dong Yan, Jian Xie, Zhongyuan Wang, Ji-Rong Wen
Large Language Model Reasoning Task Technical Report LLM Reasoning Reward Tree
AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning
Kun Xiang, Zhili Liu, Zihao Jiang, Yunshuang Nie, Runhui Huang, Haoxiang Fan, Hanhui Li, Weiran Huang, Yihan Zeng, Jianhua Han, Lanqing Hong, Hang Xu, Xiaodan Liang
Large Language Model Complex Reasoning Atomic Knowledge Large Scale Multimodal Multimodal Mathematical
FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training
Anjia Cao, Xing Wei, Zhiheng Ma
Large Language Model Text to Image Retrieval Frozen Large Language Model Efficient Image Language Image Pre Training Long Context Retrieval
Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation
Peng Shu, Junhao Chen, Zhengliang Liu, Hui Wang, Zihao Wu, Tianyang Zhong, Yiwei Li, Huaqin Zhao, Hanqi Jiang, Yi Pan, Yifan Zhou, Constance Owl, Xiaoming Zhai, Ninghao Liu, Claudio Saunt, Tianming Liu
Large Language Model Low Resource Language Low Resource Translation Quality Human Translation Linguistic Landscape
LP Data Pipeline: Lightweight, Purpose-driven Data Pipeline for Large Language Models
Yungi Kim, Hyunsoo Ha, Seonghoon Yang, Sukyung Lee, Jihoo Kim, Chanjun Park
Large Language Model Language Model Lightweight High Large Scale Datasets Data Pipeline

Large Language Model

Papers

Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus

AI Flow at the Network Edge

Guide-to-Explain for Controllable Summarization

\textsc{Neon}: News Entity-Interaction Extraction for Enhanced Question Answering

RedPajama: an Open Dataset for Training Large Language Models

CUE-M: Contextual Understanding and Enhanced Search with Multimodal Large Language Model

Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers

Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods

ByteScience: Bridging Unstructured Scientific Literature and Structured Data with Auto Fine-tuned Large Language Model in Token Granularity

Understanding Chain-of-Thought in LLMs through Information Theory

Bi-Mamba: Towards Accurate 1-Bit State Space Models

Tackling prediction tasks in relational databases with LLMs

LLM-IE: A Python Package for Generative Information Extraction with Large Language Models

BitMoD: Bit-serial Mixture-of-Datatype LLM Acceleration

Moral Persuasion in Large Language Models: Evaluating Susceptibility and Ethical Alignment

Technical Report: Enhancing LLM Reasoning with Reward-guided Tree Search

AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning

FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training

Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation

LP Data Pipeline: Lightweight, Purpose-driven Data Pipeline for Large Language Models