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 8, 2024

EUREKHA: Enhancing User Representation for Key Hackers Identification in Underground Forums
Abdoul Nasser Hassane Amadou, Anas Motii, Saida Elouardi, EL Houcine Bergou
Large Language Model Key Information Extraction User Representation Keystroke Inference Hacker Forum
Enhancing Robustness in Language-Driven Robotics: A Modular Approach to Failure Reduction
Émiland Garrabé, Pierre Teixeira, Mahdi Khoramshahi, Stéphane Doncieux
Large Language Model Native Robustness Natural Language LLM Based Partially Observable Markov Decision Process Physical Robot Modular Approach
Learning the rules of peptide self-assembly through data mining with large language models
Zhenze Yang, Sarah K. Yorke, Tuomas P. J. Knowles, Markus J. Buehler
Large Language Model Data Mining Simple RULE Peptide Source Self Assembly Peptide Level Identification Precision
Gap-Filling Prompting Enhances Code-Assisted Mathematical Reasoning
Mohammad Ghiasvand Mohammadkhani
Large Language Model Language Model Chain of Thought Mathematical Reasoning Structured Prompting
Reasoning Robustness of LLMs to Adversarial Typographical Errors
Esther Gan, Yiran Zhao, Liying Cheng, Yancan Mao, Anirudh Goyal, Kenji Kawaguchi, Min-Yen Kan, Michael Shieh
Large Language Model Closed Source Large Language Model Robust Reasoning Typographic Attack
Exploring the Alignment Landscape: LLMs and Geometric Deep Models in Protein Representation
Dong Shu, Bingbing Duan, Kai Guo, Kaixiong Zhou, Jiliang Tang, Mengnan Du
Large Language Model Multimodal Large Language Model Multimodal Representation Neural Mapping Protein Representation Latent Alignment Geometric Deep Learning Model Multimodal Protein
Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
Tong Chen, Hao Fang, Patrick Xia, Xiaodong Liu, Benjamin Van Durme, Luke Zettlemoyer, Jianfeng Gao, Hao Cheng
Large Language Model Many Parameter Supervised Fine Tuning Low Rank Adapter Forward Pas Contextualized Language Model

November 7, 2024

Abstract2Appendix: Academic Reviews Enhance LLM Long-Context Capabilities
Shengzhi Li, Kittipat Kampa, Rongyu Lin, Bohang Li, Shichao Pei
Large Language Model Long Context Capability Evolution LLM Evaluation User Review Long Context Retrieval
Alopex: A Computational Framework for Enabling On-Device Function Calls with LLMs
Yide Ran, Zhaozhuo Xu, Yuhang Yao, Zijian Hu, Shanshan Han, Han Jin, Alay Dilipbhai Shah, Jipeng Zhang, Dimitris Stripelis, Tong Zhang, Salman Avestimehr, Chaoyang He
Large Language Model Training Data Catastrophic Forgetting Computational Approach Device Use Case Device LLM
Toward Cultural Interpretability: A Linguistic Anthropological Framework for Describing and Evaluating Large Language Models (LLMs)
Graham M. Jones, Shai Satran, Arvind Satyanarayan
Large Language Model Language Model Linguistic Study AI Chatbots Language Technology Cross Cultural Cultural Understanding
Needle Threading: Can LLMs Follow Threads through Near-Million-Scale Haystacks?
Jonathan Roberts, Kai Han, Samuel Albanie
Large Language Model Long Context Needle Insertion Long Context Large Language Model Video Haystack Causal Thread
Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
Weixin Liang, Lili Yu, Liang Luo, Srinivasan Iyer, Ning Dong, Chunting Zhou, Gargi Ghosh, Mike Lewis, Wen-tau Yih, Luke Zettlemoyer, Xi Victoria Lin
Large Language Model Transformer Architecture Many Sparse Mixture of Expert Multi Modal Foundation Model Scalable Architecture
Rethinking Bradley-Terry Models in Preference-Based Reward Modeling: Foundations, Theory, and Alternatives
Hao Sun, Yunyi Shen, Jean-Francois Ton
Large Language Model Theoretical Understanding Reward Model Flawed Foundation Previously Generated Alternative Preference Reward Bradley Terry
BitNet a4.8: 4-bit Activations for 1-bit LLMs
Hongyu Wang, Shuming Ma, Furu Wei
Large Language Model Targeted Activation Penalty Binary Activation
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
Large Language Model Medical Diagnosis Large Language Model Based Diagnosis Diagnosis Task LLM Confidence
FineTuneBench: How well do commercial fine-tuning APIs infuse knowledge into LLMs?
Eric Wu, Kevin Wu, James Zou
Large Language Model Knowledge Based API Usage
GPTKB: Building Very Large Knowledge Bases from Language Models
Yujia Hu, Shrestha Ghosh, Tuan-Phong Nugyen, Simon Razniewski
Large Language Model Language Model Entity Recognition Knowledge Base GPT Neo Domain Specific Knowledge Base Knowledge Base Construction
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Siming Huang, Tianhao Cheng, Jason Klein Liu, Jiaran Hao, Liuyihan Song, Yang Xu, J. Yang, J.H. Liu, Chenchen Zhang, Linzheng Chai, Ruifeng Yuan, Zhaoxiang Zhang, Jie Fu, Qian Liu, Ge Zhang, Zili Wang, Yuan Qi, Yinghui Xu, Wei Chu
Large Language Model Code Generation Real World Code Code LLM Simple Recipe
VTechAGP: An Academic-to-General-Audience Text Paraphrase Dataset and Benchmark Models
Ming Cheng, Jiaying Gong, Chenhan Yuan, William A. Ingram, Edward Fox, Hoda Eldardiry
Large Language Model Model Benchmark Paraphrase Dataset Prompt Based NLP
LuxBank: The First Universal Dependency Treebank for Luxembourgish
Alistair Plum, Caroline Döhmer, Emilia Milano, Anne-Marie Lutgen, Christoph Purschke
Large Language Model Syntactic Information

Large Language Model

Papers

EUREKHA: Enhancing User Representation for Key Hackers Identification in Underground Forums

Enhancing Robustness in Language-Driven Robotics: A Modular Approach to Failure Reduction

Learning the rules of peptide self-assembly through data mining with large language models

Gap-Filling Prompting Enhances Code-Assisted Mathematical Reasoning

Reasoning Robustness of LLMs to Adversarial Typographical Errors

Exploring the Alignment Landscape: LLMs and Geometric Deep Models in Protein Representation

Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass

Abstract2Appendix: Academic Reviews Enhance LLM Long-Context Capabilities

Alopex: A Computational Framework for Enabling On-Device Function Calls with LLMs

Toward Cultural Interpretability: A Linguistic Anthropological Framework for Describing and Evaluating Large Language Models (LLMs)

Needle Threading: Can LLMs Follow Threads through Near-Million-Scale Haystacks?

Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models

Rethinking Bradley-Terry Models in Preference-Based Reward Modeling: Foundations, Theory, and Alternatives

BitNet a4.8: 4-bit Activations for 1-bit LLMs

Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability

FineTuneBench: How well do commercial fine-tuning APIs infuse knowledge into LLMs?

GPTKB: Building Very Large Knowledge Bases from Language Models

OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

VTechAGP: An Academic-to-General-Audience Text Paraphrase Dataset and Benchmark Models

LuxBank: The First Universal Dependency Treebank for Luxembourgish