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 21, 2024

Fine-Tuning LLMs for Reliable Medical Question-Answering Services
Ali Anaissi, Ali Braytee, Junaid Akram
Large Language Model Medical Text Fine Tuned Large Language Model Service Provider Medical Reasoning Health Outcome
CartesianMoE: Boosting Knowledge Sharing among Experts via Cartesian Product Routing in Mixture-of-Experts
Zhenpeng Su, Xing Wu, Zijia Lin, Yizhe Xiong, Minxuan Lv, Guangyuan Ma, Hui Chen, Songlin Hu, Guiguang Ding
Large Language Model Expert Knowledge Mixture of Expert Matrix Factorization Inference Cost Routing Problem Knowledge Sharing Cartesian Pose
Are Language Model Logits Calibrated?
Charles Lovering, Michael Krumdick, Viet Dac Lai, Nilesh Kumar, Varshini Reddy, Rik Koncel-Kedziorski, Chris Tanner
Large Language Model Language Model Probabilistic Model Scientific Model
Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering
Yu Zhao, Alessio Devoto, Giwon Hong, Xiaotang Du, Aryo Pradipta Gema, Hongru Wang, Kam-Fai Wong, Pasquale Minervini
Large Language Model Open Domain Question Answering Knowledge Conflict Knowledge Selection Representation Engineering
Large Language Models for Cross-lingual Emotion Detection
Ram Mohan Rao Kadiyala
Large Language Model Experienced Emotion Emotion Detection Error Analysis Cross Lingual Emotion
Self-Explained Keywords Empower Large Language Models for Code Generation
Lishui Fan, Mouxiang Chen, Zhongxin Liu
Large Language Model Code Generation Faithful Generation Real World Code DeepSeek Coder
CausalGraph2LLM: Evaluating LLMs for Causal Queries
Ivaxi Sheth, Bahare Fatemi, Mario Fritz
Large Language Model Causal Graph Causal Query
Mesa-Extrapolation: A Weave Position Encoding Method for Enhanced Extrapolation in LLMs
Xin Ma, Yang Liu, Jingjing Liu, Xiaoxu Ma
Large Language Model Extrapolation Framework Attention Matrix Cartesian Product Extrapolation Extrapolation Performance Position Encoding
LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation
Tejumade Afonja, Ivaxi Sheth, Ruta Binkyte, Waqar Hanif, Thomas Ulas, Matthias Becker, Mario Fritz
Large Language Model Global Evaluation Causal Discovery Synthetic Data Generation Regulatory Network Single Cell RNA scRNA Seq
Mitigating Hallucinations of Large Language Models in Medical Information Extraction via Contrastive Decoding
Derong Xu, Ziheng Zhang, Zhihong Zhu, Zhenxi Lin, Qidong Liu, Xian Wu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen
Large Language Model Information Extraction Mitigating Hallucination Contrastive Decoding Medical Information Extraction Token Level Contrastive
DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization
Haohan Yuan, Haopeng Zhang
Large Language Model Domain Generalization Abstractive Summarization Internet Service Domain Summarization Model Abstractive Text Summarization
Revealing and Mitigating the Local Pattern Shortcuts of Mamba
Wangjie You, Zecheng Tang, Juntao Li, Lili Yao, Min Zhang
Large Language Model Mamba in Mamba Attention Based Model Long Context Task Memory Constraint Mamba Based Model Local Binary Pattern
Long Term Memory: The Foundation of AI Self-Evolution
Xun Jiang, Feng Li, Han Zhao, Jiaying Wang, Jun Shao, Shihao Xu, Shu Zhang, Weiling Chen, Xavier Tang, Yize Chen, Mengyue Wu, Weizhi Ma, Mengdi Wang, Tianqiao Chen
Large Language Model Artificial Intelligence Model Internal Representation Flawed Foundation Memory Formation Self Evolution
Understanding and Alleviating Memory Consumption in RLHF for LLMs
Jin Zhou, Hanmei Yang, Steven (Jiaxun) Tang, Mingcan Xiang, Hui Guan, Tongping Liu
Large Language Model Reinforcement Learning Fine Tuning Human Understanding Reinforcement Learning From Human Feedback Memory Management Memory Reduction
Boosting Jailbreak Transferability for Large Language Models
Hanqing Liu, Lifeng Zhou, Huanqian Yan
Large Language Model Jailbreak Attack Better Alignment Grand Challenge Model Attack Adversarial Suffix
Guardians of Discourse: Evaluating LLMs on Multilingual Offensive Language Detection
Jianfei He, Lilin Wang, Jiaying Wang, Zhenyu Liu, Hongbin Na, Zimu Wang, Wei Wang, Qi Chen
Large Language Model Augmented Data Offensive Language Offensive Language Detection Discourse Level Language Detection
On The Global Convergence Of Online RLHF With Neural Parametrization
Mudit Gaur, Amrit Singh Bedi, Raghu Pasupathy, Vaneet Aggarwal
Large Language Model Reinforcement Learning Neural Network Reinforcement Learning From Human Feedback Global Convergence Reward Learning AI Alignment
A Comprehensive Survey of Datasets, Theories, Variants, and Applications in Direct Preference Optimization
Wenyi Xiao, Zechuan Wang, Leilei Gan, Shuai Zhao, Wanggui He, Luu Anh Tuan, Long Chen, Hao Jiang, Zhou Zhao, Fei Wu
Large Language Model Reinforcement Learning Data Set Financial Application Comprehensive Survey Direct Preference Optimization Preference Optimization Model Alignment Natural Language Oriented Variant Preference Datasets
Stacking Small Language Models for Generalizability
Laurence Liang
Large Language Model Language Model Natural Language Stronger Generalizability Natural Language Processing Benchmark
Pruning Foundation Models for High Accuracy without Retraining
Pu Zhao, Fei Sun, Xuan Shen, Pinrui Yu, Zhenglun Kong, Yanzhi Wang, Xue Lin
Large Language Model Pruning Method Model Pruning Transformer Based Large Language Model High Accuracy Retraining Method

Large Language Model

Papers

Fine-Tuning LLMs for Reliable Medical Question-Answering Services

CartesianMoE: Boosting Knowledge Sharing among Experts via Cartesian Product Routing in Mixture-of-Experts

Are Language Model Logits Calibrated?

Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering

Large Language Models for Cross-lingual Emotion Detection

Self-Explained Keywords Empower Large Language Models for Code Generation

CausalGraph2LLM: Evaluating LLMs for Causal Queries

Mesa-Extrapolation: A Weave Position Encoding Method for Enhanced Extrapolation in LLMs

LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation

Mitigating Hallucinations of Large Language Models in Medical Information Extraction via Contrastive Decoding

DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization

Revealing and Mitigating the Local Pattern Shortcuts of Mamba

Long Term Memory: The Foundation of AI Self-Evolution

Understanding and Alleviating Memory Consumption in RLHF for LLMs

Boosting Jailbreak Transferability for Large Language Models

Guardians of Discourse: Evaluating LLMs on Multilingual Offensive Language Detection

On The Global Convergence Of Online RLHF With Neural Parametrization

A Comprehensive Survey of Datasets, Theories, Variants, and Applications in Direct Preference Optimization

Stacking Small Language Models for Generalizability

Pruning Foundation Models for High Accuracy without Retraining