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 21, 2024

Planning-Driven Programming: A Large Language Model Programming Workflow
Chao Lei, Yanchuan Chang, Nir Lipovetzky, Krista A. Ehinger
Large Language Model Code Generation Tool Augmented LLM
Schemato -- An LLM for Netlist-to-Schematic Conversion
Ryoga Matsuo, Stefan Uhlich, Arun Venkitaraman, Andrea Bonetti, Chia-Yu Hsieh, Ali Momeni, Lukas Mauch, Augusto Capone, Eisaku Ohbuchi, Lorenzo Servadei
Large Language Model Refined Schema
AutoMixQ: Self-Adjusting Quantization for High Performance Memory-Efficient Fine-Tuning
Changhai Zhou, Shiyang Zhang, Yuhua Zhou, Zekai Liu, Shichao Weng
Large Language Model Deep Learning End to End High Performance Memory Efficient Fine Tuning LLM Framework
Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning
Hang Zhou, Yehui Tang, Haochen Qin, Yujie Yang, Renren Jin, Deyi Xiong, Kai Han, Yunhe Wang
Large Language Model Instruction Tuning Agent Smith Human Instruction LLM Agent Agent System Multi Agent Collaboration Instruction Data Hyper Tune Data Optimization
NewsInterview: a Dataset and a Playground to Evaluate LLMs' Ground Gap via Informational Interviews
Michael Lu, Hyundong Justin Cho, Weiyan Shi, Jonathan May, Alexander Spangher
Large Language Model Data Set Filling Gap Strategic Interaction Interview Data
A Framework for Evaluating LLMs Under Task Indeterminacy
Luke Guerdan, Hanna Wallach, Solon Barocas, Alexandra Chouldechova
Large Language Model New Framework Medical LLM Task Ambiguity Evaluation Corpus

November 20, 2024

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Yoel Zimmermann, Adib Bazgir, Zartashia Afzal, Fariha Agbere, Qianxiang Ai, Nawaf Alampara, Alexander Al-Feghali, Mehrad Ansari, Dmytro Antypov, Amro Aswad, Jiaru Bai, Viktoriia Baibakova, Devi Dutta Biswajeet, Erik Bitzek, Joshua D. Bocarsly, Anna Borisova, Andres M Bran, L. Catherine Brinson, Marcel Moran Calderon, Alessandro Canalicchio, Victor Chen, Yuan Chiang, Defne Circi, Benjamin Charmes, Vikrant Chaudhary, Zizhang Chen, Min-Hsueh Chiu, Judith Clymo, Kedar Dabhadkar, Nathan Daelman, Archit Datar, Wibe A. de Jong, Matthew L. Evans, Maryam Ghazizade Fard, Giuseppe Fisicaro, Abhijeet Sadashiv Gangan, Janine George, Jose D. Cojal Gonzalez, Michael Götte, Ankur K. Gupta, Hassan Harb, Pengyu Hong, Abdelrahman Ibrahim, Ahmed Ilyas, Alishba Imran, Kevin Ishimwe, Ramsey Issa, Kevin Maik Jablonka, Colin Jones, Tyler R. Josephson, Greg Juhasz, Sarthak Kapoor, Rongda Kang, Ghazal Khalighinejad, Sartaaj Khan, Sascha Klawohn, Suneel Kuman, Alvin Noe Ladines, Sarom Leang, Magdalena Lederbauer, Sheng-Lun (Mark) Liao, Hao Liu, Xuefeng Liu, Stanley Lo, Sandeep Madireddy, Piyush Ranjan Maharana, Shagun Maheshwari, Soroush Mahjoubi, José A. Márquez, Rob Mills, Trupti Mohanty, Bernadette Mohr, Seyed Mohamad Moosavi, Alexander Moßhammer, Amirhossein D. Naghdi, Aakash Naik, Oleksandr Narykov, Hampus Näsström, Xuan Vu Nguyen, Xinyi Ni, Dana O'Connor, Teslim Olayiwola, Federico Ottomano, Aleyna Beste Ozhan, Sebastian Pagel, Chiku Parida, Jaehee Park, Vraj Patel, Elena Patyukova, Martin Hoffmann Petersen, Luis Pinto, José M. Pizarro, Dieter Plessers, Tapashree Pradhan, Utkarsh Pratiush, Charishma Puli, Andrew Qin, Mahyar Rajabi, Francesco Ricci, Elliot Risch, Martiño Ríos-García, Aritra Roy, Tehseen Rug, Hasan M Sayeed, Markus Scheidgen, Mara Schilling-Wilhelmi, Marcel Schloz, Fabian Schöppach, Julia Schumann, Philippe Schwaller, Marcus Schwarting, Samiha Sharlin, Kevin Shen, Jiale Shi, Pradip Si, Jennifer D'Souza, Taylor Sparks, Suraj Sudhakar, Leopold Talirz, Dandan Tang, Olga Taran, Carla Terboven, Mark Tropin, Anastasiia Tsymbal, Katharina Ueltzen, Pablo Andres Unzueta, Archit Vasan, Tirtha Vinchurkar, Trung Vo, Gabriel Vogel, Christoph Völker, Jan Weinreich, Faradawn Yang, Mohd Zaki, Chi Zhang, Sylvester Zhang, Weijie Zhang, Ruijie Zhu, Shang Zhu, Jan Janssen, Calvin Li, Ian Foster, Ben Blaiszik et al. (96 additional authors not shown) You must enabled JavaScript to view entire author list.
Large Language Model Financial Application Design Space Material SCIence National AI Misinformation Hackathon
Assessing Gender Bias in LLMs: Comparing LLM Outputs with Human Perceptions and Official Statistics
Tetiana Bas
Large Language Model Gender Bias Gender Inclusive Text LLM Output
Utilizing Large Language Models to Synthesize Product Desirability Datasets
John D. Hastings, Sherri Weitl-Harms, Joseph Doty, Zachary L. Myers, Warren Thompson
Large Language Model Data Set User Sentiment Easy to Use Toolkit Sentiment Score Synthetic Preference
S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning
Mingze Yin, Hanjing Zhou, Jialu Wu, Yiheng Zhu, Yuxuan Zhan, Zitai Kong, Hongxia Xu, Chang-Yu Hsieh, Jintai Chen, Tingjun Hou, Jian Wu
Large Language Model Language Model Therapeutic Antibody Epitope Prediction Antibody Structure
CryptoFormalEval: Integrating LLMs and Formal Verification for Automated Cryptographic Protocol Vulnerability Detection
Cristian Curaba, Denis D'Ambrosi, Alessandro Minisini, Natalia Pérez-Campanero Antolín
Large Language Model Formal Verification Cryptographic Protocol
A Survey on Human-Centric LLMs
Jing Yi Wang, Nicholas Sukiennik, Tong Li, Weikang Su, Qianyue Hao, Jingbo Xu, Zihan Huang, Fengli Xu, Yong Li
Large Language Model Timely Survey Human Ai Collaboration Human Cognition Social Cognition
FASTNav: Fine-tuned Adaptive Small-language-models Trained for Multi-point Robot Navigation
Yuxuan Chen, Yixin Han, Xiao Li
Large Language Model Language Model Natural Language
AIDBench: A benchmark for evaluating the authorship identification capability of large language models
Zichen Wen, Dadi Guo, Huishuai Zhang
Large Language Model New Benchmark Capability Evolution Peer Review Multiple Authorship Authorship Verification
Existential Conversations with Large Language Models: Content, Community, and Culture
Murray Shanahan, Beth Singler
Large Language Model Language Model Artificial Intelligence Conversational AI Community Conversation Local Culture Forming Community
The Information Security Awareness of Large Language Models
Ofir Cohen, Gil Ari Agmon, Asaf Shabtai, Rami Puzis
Large Language Model Chatbot Response
Closer Look at Efficient Inference Methods: A Survey of Speculative Decoding
Hyun Ryu, Eric Kim
Large Language Model Timely Survey LLM Inference Efficient Inference Speculative Decoding Accurate Decoding Speculative Exploration
DMQR-RAG: Diverse Multi-Query Rewriting for RAG
Zhicong Li, Jiahao Wang, Zhishu Jiang, Hangyu Mao, Zhongxia Chen, Jiazhen Du, Yuanxing Zhang, Fuzheng Zhang, Di Zhang, Yong Liu
Large Language Model Information Retrieval Kg Rag
Patience Is The Key to Large Language Model Reasoning
Yijiong Yu
Large Language Model Complex Reasoning Reasoning Ability Reasoning Process Clinical Reasoning
Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training
Jared Fernandez, Luca Wehrstedt, Leonid Shamis, Mostafa Elhoushi, Kalyan Saladi, Yonatan Bisk, Emma Strubell, Jacob Kahn
Large Language Model Neural Network Model Model Training Hardware Accelerator Customer Service LLM Training Positive Scaling

Large Language Model

Papers

Planning-Driven Programming: A Large Language Model Programming Workflow

Schemato -- An LLM for Netlist-to-Schematic Conversion

AutoMixQ: Self-Adjusting Quantization for High Performance Memory-Efficient Fine-Tuning

Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning

NewsInterview: a Dataset and a Playground to Evaluate LLMs' Ground Gap via Informational Interviews

A Framework for Evaluating LLMs Under Task Indeterminacy

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Assessing Gender Bias in LLMs: Comparing LLM Outputs with Human Perceptions and Official Statistics

Utilizing Large Language Models to Synthesize Product Desirability Datasets

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning

CryptoFormalEval: Integrating LLMs and Formal Verification for Automated Cryptographic Protocol Vulnerability Detection

A Survey on Human-Centric LLMs

FASTNav: Fine-tuned Adaptive Small-language-models Trained for Multi-point Robot Navigation

AIDBench: A benchmark for evaluating the authorship identification capability of large language models

Existential Conversations with Large Language Models: Content, Community, and Culture

The Information Security Awareness of Large Language Models

Closer Look at Efficient Inference Methods: A Survey of Speculative Decoding

DMQR-RAG: Diverse Multi-Query Rewriting for RAG

Patience Is The Key to Large Language Model Reasoning

Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training