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

January 16, 2025

Distilling Multi-modal Large Language Models for Autonomous Driving
Deepti Hegde, Rajeev Yasarla, Hong Cai, Shizhong Han, Apratim Bhattacharyya, Shweta Mahajan, Litian Liu, Risheek Garrepalli, Vishal M. Patel, Fatih Porikli
Large Language Model Autonomous Driving Multi Modal LLM
OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking
Zekun Xi, Wenbiao Yin, Jizhan Fang, Jialong Wu, Runnan Fang, Ningyu Zhang, Jiang Yong, Pengjun Xie, Fei Huang, Huajun Chen
Large Language Model New Machine Long Span Human Thinking Knowledge Boundary
The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models
Jonathan Katzy, Razvan Mihai Popescu, Arie van Deursen, Maliheh Izadi
Large Language Model Multilingual Dataset Programming Language Code Datasets Memory Dump Multilingual Code Search Dataset
LLM-Based Routing in Mixture of Experts: A Novel Framework for Trading
Kuan-Ming Liu (1), Ming-Chih Lo (2) ((1) National Chengchi University, College of Commerce, (2) National Yang Ming Chiao Tung University, College of Computer Science)
Large Language Model Deep Learning Mixture Component Expert Knowledge Mixture of Expert Novel Framework Routing Problem Financial Trading Financial Domain
Empowering Large Language Models in Wireless Communication: A Novel Dataset and Fine-Tuning Framework
Yushen Lin, Ruichen Zhang, Wenqi Huang, Kaidi Wang, Zhiguo Ding, Daniel K. C. So, Dusit Niyato
Large Language Model Data Set Fine Tuning Long Form Novel Fine Tuned Model Wireless Research
Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
Chaoqi Wang, Zhuokai Zhao, Yibo Jiang, Zhaorun Chen, Chen Zhu, Yuxin Chen, Jiayi Liu, Lizhu Zhang, Xiangjun Fan, Hao Ma, Sinong Wang
Large Language Model Causal Inference Large Language Model Alignment Reward Hacking
Confidence Estimation for Error Detection in Text-to-SQL Systems
Oleg Somov, Elena Tutubalina
Large Language Model Natural Language Text to SQL Query Information Error Detection Confidence Estimation
Augmenting a Large Language Model with a Combination of Text and Visual Data for Conversational Visualization of Global Geospatial Data
Omar Mena, Alexandre Kouyoumdjian, Lonni Besançon, Michael Gleicher, Ivan Viola, Anders Ynnerman
Large Language Model Text Modality Interactive Visualization Visual Data Visual Analytics Tool
A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy
Huandong Wang, Wenjie Fu, Yingzhou Tang, Zhilong Chen, Yuxi Huang, Jinghua Piao, Chen Gao, Fengli Xu, Tao Jiang, Yong Li
Large Language Model Timely Survey Jailbreak Attack Risk Sensitive Value Alignment State of the Art LLM Real World Application Malicious User Adaptive Mitigation
FASP: Fast and Accurate Structured Pruning of Large Language Models
Hanyu Hu, Pengxiang Zhao, Ping Li, Yi Zheng, Zhefeng Wang, Xiaoming Yuan
Large Language Model Pruning Method Answer Set Programming Structured Pruning Pruning Framework
MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models
Lyudong Jin, Yanning Zhang, Yanhan Li, Shurong Wang, Howard H. Yang, Jian Wu, Meng Zhang
Large Language Model Full Model Mixture of Expert Collaborative Inference Inference Performance Expert Selection
Aligning Instruction Tuning with Pre-training
Yiming Liang, Tianyu Zheng, Xinrun Du, Ge Zhang, Xingwei Qu, Xiang Yue, Chujie Zheng, Jiaheng Liu, Lei Ma, Wenhu Chen, Guoyin Wang, Zhaoxiang Zhang, Wenhao Huang, Jiajun Zhang
Large Language Model Instruction Tuning Pre Training Instruction Paradigm
Rational Tuning of LLM Cascades via Probabilistic Modeling
Michael J. Zellinger, Matt Thomson
Large Language Model Probabilistic Model Parameter Efficient Tuning TF Cascade Dimensional Copula Cascade System
A Study of In-Context-Learning-Based Text-to-SQL Errors
Jiawei Shen, Chengcheng Wan, Ruoyi Qiao, Jiazhen Zou, Hang Xu, Yuchen Shao, Yueling Zhang, Weikai Miao, Geguang Pu
Large Language Model Study Feature Text to SQL Query Language
To Retrieve or Not to Retrieve? Uncertainty Detection for Dynamic Retrieval Augmented Generation
Kaustubh D. Dhole
Large Language Model Retrieval Augmented Generation Question Answering Detection of Uncertainty in Exceedance
Large Language Model is Secretly a Protein Sequence Optimizer
Yinkai Wang, Jiaxing He, Yuanqi Du, Xiaohui Chen, Jianan Canal Li, Li-Ping Liu, Xiaolin Xu, Soha Hassoun
Large Language Model Protein Sequence Fitness Landscape Protein Engineering Sequence Optimization
Perspective Transition of Large Language Models for Solving Subjective Tasks
Xiaolong Wang, Yuanchi Zhang, Ziyue Wang, Yuzhuang Xu, Fuwen Luo, Yile Wang, Peng Li, Yang Liu
Large Language Model Context Learning Commonsense Reasoning New Task Subjective Knowledge Perspective Transform Third Person
Foundations of Large Language Models
Tong Xiao, Jingbo Zhu
Large Language Model Natural Language Processing Generative Model Large Language Flawed Foundation Alignment Approach
FineMedLM-o1: Enhancing the Medical Reasoning Ability of LLM from Supervised Fine-Tuning to Test-Time Training
Hongzhou Yu, Tianhao Cheng, Ying Cheng, Rui Feng
Large Language Model Training Data Medical LLM Reasoning Capability Supervised Fine Tuning Synthetic Medical Data

January 15, 2025

The Veln(ia)s is in the Details: Evaluating LLM Judgment on Latvian and Lithuanian Short Answer Matching
Yevhen Kostiuk, Oxana Vitman, Łukasz Gagała, Artur Kiulian
Large Language Model Question Answer Pair DetAIL VLN Ce

Large Language Model

Papers

Distilling Multi-modal Large Language Models for Autonomous Driving

OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking

The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models

LLM-Based Routing in Mixture of Experts: A Novel Framework for Trading

Empowering Large Language Models in Wireless Communication: A Novel Dataset and Fine-Tuning Framework

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment

Confidence Estimation for Error Detection in Text-to-SQL Systems

Augmenting a Large Language Model with a Combination of Text and Visual Data for Conversational Visualization of Global Geospatial Data

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy

FASP: Fast and Accurate Structured Pruning of Large Language Models

MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models

Aligning Instruction Tuning with Pre-training

Rational Tuning of LLM Cascades via Probabilistic Modeling

A Study of In-Context-Learning-Based Text-to-SQL Errors

To Retrieve or Not to Retrieve? Uncertainty Detection for Dynamic Retrieval Augmented Generation

Large Language Model is Secretly a Protein Sequence Optimizer

Perspective Transition of Large Language Models for Solving Subjective Tasks

Foundations of Large Language Models

FineMedLM-o1: Enhancing the Medical Reasoning Ability of LLM from Supervised Fine-Tuning to Test-Time Training

The Veln(ia)s is in the Details: Evaluating LLM Judgment on Latvian and Lithuanian Short Answer Matching