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

October 22, 2024

MotionGlot: A Multi-Embodied Motion Generation Model
Sudarshan Harithas, Srinath Sridhar
Large Language Model Human Motion Different Physical Embodiment Motion Skill
Benchmarking Large Language Models for Image Classification of Marine Mammals
Yijiashun Qi, Shuzhang Cai, Zunduo Zhao, Jiaming Li, Yanbin Lin, Zhiqiang Wang
Large Language Model Artificial Intelligence Image Classification Animal Specie Intra Specie Differentiation MARINE Vessel
Distill-SynthKG: Distilling Knowledge Graph Synthesis Workflow for Improved Coverage and Efficiency
Prafulla Kumar Choubey, Xin Su, Man Luo, Xiangyu Peng, Caiming Xiong, Tiep Le, Shachar Rosenman, Vasudev Lal, Phil Mui, Ricky Ho, Phillip Howard, Chien-Sheng Wu
Large Language Model Knowledge Graph High Efficiency Retrieval Augmented Generation Knowledge Base Construction Document Summary Pair Entity Coverage
Dynamic Adaptive Rank Space Exploration for Efficient Sentiment Analysis with Large Language Models
Hongcheng Ding, Fuzhen Hu, Xuanze Zhao, Zixiao Jiang, Shamsul Nahar Abdullah, Deshinta Arrova Dewi
Large Language Model Sentiment Analysis Adaptive Ranking
Optimizing LLMs with Direct Preferences: A Data Efficiency Perspective
Pietro Bernardelle, Gianluca Demartini
Large Language Model Direct Preference Optimization LLM Alignment Data Efficiency

October 21, 2024

Large language models enabled multiagent ensemble method for efficient EHR data labeling
Jingwei Huang, Kuroush Nezafati, Ismael Villanueva-Miranda, Zifan Gu, Ann Marie Navar, Tingyi Wanyan, Qin Zhou, Bo Yao, Ruichen Rong, Xiaowei Zhan, Guanghua Xiao, Eric D. Peterson, Donghan M. Yang, Yang Xie
Large Language Model Agent Ensemble Ensemble LLM Approach
STAR: A Simple Training-free Approach for Recommendations using Large Language Models
Dong-Ho Lee, Adam Kraft, Long Jin, Nikhil Mehta, Taibai Xu, Lichan Hong, Ed H. Chi, Xinyang Yi
Large Language Model Language Model Multi Task Recommendation System Movie Recommendation Training Free Star Model Next Item
Does your LLM truly unlearn? An embarrassingly simple approach to recover unlearned knowledge
Zhiwei Zhang, Fali Wang, Xiaomin Li, Zongyu Wu, Xianfeng Tang, Hui Liu, Qi He, Wenpeng Yin, Suhang Wang
Large Language Model Medical LLM Unlearned Model Simple Approach Robust Unlearning
A Simple Model of Inference Scaling Laws
Noam Levi
Large Language Model Scientific Inference Simple Model Probabilistic Learning Inferential Strategy
Reflection-Bench: probing AI intelligence with reflection
Lingyu Li, Yixu Wang, Haiquan Zhao, Shuqi Kong, Yan Teng, Chunbo Li, Yingchun Wang
Large Language Model Artificial Intelligence Critical Reflection
CompassJudger-1: All-in-one Judge Model Helps Model Evaluation and Evolution
Maosong Cao, Alexander Lam, Haodong Duan, Hongwei Liu, Songyang Zhang, Kai Chen
Large Language Model Specie Evolution Model Evaluation LLM Based Evaluation Fine Tuned Judge Model Subjective Task
Analyzing Context Contributions in LLM-based Machine Translation
Emmanouil Zaranis, Nuno M. Guerreiro, André F. T. Martins
Large Language Model Anomaly Detection Machine Translation LLM Based Machine Translation Contribution Evaluation
Large Language Models in Computer Science Education: A Systematic Literature Review
Nishat Raihan, Mohammed Latif Siddiq, Joanna C.S. Santos, Marcos Zampieri
Large Language Model Text Generation Code Generation Generative Question Literature Review Foundational Model Computer Science Education
A Realistic Threat Model for Large Language Model Jailbreaks
Valentyn Boreiko, Alexander Panfilov, Vaclav Voracek, Matthias Hein, Jonas Geiping
Large Language Model Jailbreak Attack LLM Fine Tuning Threat Model
Pre-training Distillation for Large Language Models: A Design Space Exploration
Hao Peng, Xin Lv, Yushi Bai, Zijun Yao, Jiajie Zhang, Lei Hou, Juanzi Li
Large Language Model Knowledge Distillation Environment Exploration Teacher Model Design Space Low Temperature Distillation
Comprehensive benchmarking of large language models for RNA secondary structure prediction
L.I. Zablocki, L.A. Bugnon, M. Gerard, L. Di Persia, G. Stegmayer, D.H. Milone
Large Language Model Pre Trained Large Language Model Structure Prediction RNA Sequence RNA Structure miRNA Description
LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulation
Hao Gao, Jingyue Wang, Wenyang Fang, Jingwei Xu, Yunpeng Huang, Taolue Chen, Xiaoxing Ma
Large Language Model Autonomous Driving Simulation Study Autonomous Agent Data Generation Traffic Pattern Natural Language Input Layer Selective Rank Reduction
MagicPIG: LSH Sampling for Efficient LLM Generation
Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Leon Bottou, Zhihao Jia, Beidi Chen
Large Language Model Attention Computation LLM Generation Locality Sensitive Hashing Efficient Approximation Attention Score Dynamic Sparsity
Do LLMs write like humans? Variation in grammatical and rhetorical styles
Alex Reinhart, David West Brown, Ben Markey, Michael Laudenbach, Kachatad Pantusen, Ronald Yurko, Gordon Weinberg
Large Language Model Real Human Style Consistency Linguistic Feature Category Wise Variation Human Written Text Rhetorical Structure
Analysing the Residual Stream of Language Models Under Knowledge Conflicts
Yu Zhao, Xiaotang Du, Giwon Hong, Aryo Pradipta Gema, Alessio Devoto, Hongru Wang, Xuanli He, Kam-Fai Wong, Pasquale Minervini
Large Language Model Language Model Knowledge Based Parametric Knowledge Conflict Classification Contextual Knowledge Residual Stream Knowledge Conflict

Large Language Model

Papers

MotionGlot: A Multi-Embodied Motion Generation Model

Benchmarking Large Language Models for Image Classification of Marine Mammals

Distill-SynthKG: Distilling Knowledge Graph Synthesis Workflow for Improved Coverage and Efficiency

Dynamic Adaptive Rank Space Exploration for Efficient Sentiment Analysis with Large Language Models

Optimizing LLMs with Direct Preferences: A Data Efficiency Perspective

Large language models enabled multiagent ensemble method for efficient EHR data labeling

STAR: A Simple Training-free Approach for Recommendations using Large Language Models

Does your LLM truly unlearn? An embarrassingly simple approach to recover unlearned knowledge

A Simple Model of Inference Scaling Laws

Reflection-Bench: probing AI intelligence with reflection

CompassJudger-1: All-in-one Judge Model Helps Model Evaluation and Evolution

Analyzing Context Contributions in LLM-based Machine Translation

Large Language Models in Computer Science Education: A Systematic Literature Review

A Realistic Threat Model for Large Language Model Jailbreaks

Pre-training Distillation for Large Language Models: A Design Space Exploration

Comprehensive benchmarking of large language models for RNA secondary structure prediction

LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulation

MagicPIG: LSH Sampling for Efficient LLM Generation

Do LLMs write like humans? Variation in grammatical and rhetorical styles

Analysing the Residual Stream of Language Models Under Knowledge Conflicts