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 14, 2024

LoLCATs: On Low-Rank Linearizing of Large Language Models
Michael Zhang, Simran Arora, Rahul Chalamala, Alan Wu, Benjamin Spector, Aaryan Singhal, Krithik Ramesh, Christopher Ré
Large Language Model Linear Attention Reverse Graph Linearization
ForgeryGPT: Multimodal Large Language Model For Explainable Image Forgery Detection and Localization
Jiawei Li, Fanrui Zhang, Jiaying Zhu, Esther Sun, Qiang Zhang, Zheng-Jun Zha
Large Language Model Multimodal Phenomenon Visual Explanation Forgery Detection Specific Forgery
Minimum Tuning to Unlock Long Output from LLMs with High Quality Data as the Key
Yingda Chen, Xingjun Wang, Jintao Huang, Yunlin Mao, Daoze Zhang, Yuze Zhao
Large Language Model Medical LLM Structured Output High Quality Data Parameter Tuning
Is Parameter Collision Hindering Continual Learning in LLMs?
Shuo Yang, Kun-Peng Ning, Yu-Yang Liu, Jia-Yu Yao, Yong-Hong Tian, Yi-Bing Song, Li Yuan
Large Language Model Continual LEArning Continual Learning Orthogonal Statistical Learning
Jailbreak Instruction-Tuned LLMs via end-of-sentence MLP Re-weighting
Yifan Luo, Zhennan Zhou, Meitan Wang, Bin Dong
Large Language Model Jailbreak Attack Explanatory Inference Unsafe Prompt MLP Layer
$α$-DPO: Adaptive Reward Margin is What Direct Preference Optimization Needs
Junkang Wu, Xue Wang, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Rong Jin, Xiangnan He
Large Language Model Optimization Purpose Direct Preference Optimization Preference Feedback Preference Optimization
AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models
Haiquan Lu, Yefan Zhou, Shiwei Liu, Zhangyang Wang, Michael W. Mahoney, Yaoqing Yang
Large Language Model Large Relevance Improvement Heavy Tailed Layer Pruning Layerwise Sparsity

October 13, 2024

A Multi-LLM Orchestration Engine for Personalized, Context-Rich Assistance
Sumedh Rasal
Large Language Model Language Understanding Context Information Personalized Subject HELP Request AI Assistance Egocentric AI
Safety-Aware Fine-Tuning of Large Language Models
Hyeong Kyu Choi, Xuefeng Du, Yixuan Li
Large Language Model Fine Tuning Safety Fine Tuning Harmful Data
Collu-Bench: A Benchmark for Predicting Language Model Hallucinations in Code
Nan Jiang, Qi Li, Lin Tan, Tianyi Zhang
Large Language Model New Benchmark Real World Code MT Bench Language Model Hallucination Code Hallucination
Evaluating Gender Bias of LLMs in Making Morality Judgements
Divij Bajaj, Yuanyuan Lei, Jonathan Tong, Ruihong Huang
Large Language Model Gender Bias Moral Judgment
Self-Data Distillation for Recovering Quality in Pruned Large Language Models
Vithursan Thangarasa, Ganesh Venkatesh, Nish Sinnadurai, Sean Lie
Large Language Model Full Model Quality Issue Structured Pruning Shot Pruning
Learning to Rank for Multiple Retrieval-Augmented Models through Iterative Utility Maximization
Alireza Salemi, Hamed Zamani
Large Language Model LeArning Abstract Retrieval Augmented Stable Rank Retrieval Augmentation Search Engine Knowledge Intensive Utility Maximization
Equitable Access to Justice: Logical LLMs Show Promise
Manuj Kant, Manav Kant, Marzieh Nabi, Preston Carlson, Megan Ma
Large Language Model Complex Reasoning Reasoning Capability Logic Programming Information Access Logic Program Vision Science JUSTICE
RMB: Comprehensively Benchmarking Reward Models in LLM Alignment
Enyu Zhou, Guodong Zheng, Binghai Wang, Zhiheng Xi, Shihan Dou, Rong Bao, Wei Shen, Limao Xiong, Jessica Fan, Yurong Mou, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang
Large Language Model Reward Model Downstream Task LLM Alignment Optimal Alignment
EasyJudge: an Easy-to-use Tool for Comprehensive Response Evaluation of LLMs
Yijie Li, Yuan Sun
Large Language Model Medical LLM Model Evaluation LLM Evaluation Closed Source Model Response Evaluation
'Quis custodiet ipsos custodes?' Who will watch the watchmen? On Detecting AI-generated peer-reviews
Sandeep Kumar, Mohit Sahu, Vardhan Gacche, Tirthankar Ghosal, Asif Ekbal
Large Language Model Data Detection Text Detection Peer Review AI Text Detector
BiDoRA: Bi-level Optimization-Based Weight-Decomposed Low-Rank Adaptation
Peijia Qin, Ruiyi Zhang, Pengtao Xie
Large Language Model Language Generation Parameter Efficient Fine Tuning Adaptation Concern Multiple Level
Surgical-LLaVA: Toward Surgical Scenario Understanding via Large Language and Vision Models
Juseong Jin, Chang Wook Jeong
Large Language Model Large Vision Language Model Human Language Visual Question Answering Vision Model LLaVA HD Surgical Scene Understanding Multimodal Behavior
Taming Overconfidence in LLMs: Reward Calibration in RLHF
Jixuan Leng, Chengsong Huang, Banghua Zhu, Jiaxin Huang
Large Language Model Reward Model Reinforcement Learning From Human Feedback Confidence Scoring

Large Language Model

Papers

LoLCATs: On Low-Rank Linearizing of Large Language Models

ForgeryGPT: Multimodal Large Language Model For Explainable Image Forgery Detection and Localization

Minimum Tuning to Unlock Long Output from LLMs with High Quality Data as the Key

Is Parameter Collision Hindering Continual Learning in LLMs?

Jailbreak Instruction-Tuned LLMs via end-of-sentence MLP Re-weighting

$α$-DPO: Adaptive Reward Margin is What Direct Preference Optimization Needs

AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models

A Multi-LLM Orchestration Engine for Personalized, Context-Rich Assistance

Safety-Aware Fine-Tuning of Large Language Models

Collu-Bench: A Benchmark for Predicting Language Model Hallucinations in Code

Evaluating Gender Bias of LLMs in Making Morality Judgements

Self-Data Distillation for Recovering Quality in Pruned Large Language Models

Learning to Rank for Multiple Retrieval-Augmented Models through Iterative Utility Maximization

Equitable Access to Justice: Logical LLMs Show Promise

RMB: Comprehensively Benchmarking Reward Models in LLM Alignment

EasyJudge: an Easy-to-use Tool for Comprehensive Response Evaluation of LLMs

'Quis custodiet ipsos custodes?' Who will watch the watchmen? On Detecting AI-generated peer-reviews

BiDoRA: Bi-level Optimization-Based Weight-Decomposed Low-Rank Adaptation

Surgical-LLaVA: Toward Surgical Scenario Understanding via Large Language and Vision Models

Taming Overconfidence in LLMs: Reward Calibration in RLHF