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 9, 2025

DriVLM: Domain Adaptation of Vision-Language Models in Autonomous Driving
Xuran Zheng, Chang D. Yoo
Large Language Model Autonomous Driving Domain Adaptation Vision Language Model Multimodal Large Language Model Legal Autonomy Driving Context MLLM Attention
A Text-Based Knowledge-Embedded Soft Sensing Modeling Approach for General Industrial Process Tasks Based on Large Language Model
Shuo Tong, Han Liu, Runyuan Guo, Xueqiong Tian, Wenqing Wang, Ding Liu, Youmin Zhang
Large Language Model Data Driven Soft Sensor Industrial Task
Enhancing Human-Like Responses in Large Language Models
Ethem Yağız Çalık, Talha Rüzgar Akkuş
Large Language Model Artificial Intelligence Natural Language Human Like
Demystifying Domain-adaptive Post-training for Financial LLMs
Zixuan Ke, Yifei Ming, Xuan-Phi Nguyen, Caiming Xiong, Shafiq Joty
Large Language Model Domain Adaptation Domain Adaptive Continual Pre Training Post Training Financial Large Language Model Adversarial Reward
Step-by-Step Mastery: Enhancing Soft Constraint Following Ability of Large Language Models
Qingyu Ren, Jie Zeng, Qianyu He, Jiaqing Liang, Yanghua Xiao, Weikang Zhou, Zeye Sun, Fei Yu
Large Language Model Expert Knowledge Participation Constraint Critique Ability Soft Constraint Multiple Constraint
Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words
Gouki Minegishi, Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo
Large Language Model Inherent Interpretability Individual Representation Sparse Autoencoders Sparse Feature Polysemous Word
$\text{Transformer}^2$: Self-adaptive LLMs
Qi Sun, Edoardo Cetin, Yujin Tang
Large Language Model Language Model Reinforcement Learning Vision Language Task Self Adaptation Task Performance

January 8, 2025

Real-Time Textless Dialogue Generation
Long Mai, Julie Carson-Berndsen
Large Language Model Dialogue System Dialogue Generation Row Turning Paralinguistic Feature
Do Code LLMs Understand Design Patterns?
Zhenyu Pan, Xuefeng Song, Yunkun Wang, Rongyu Cao, Binhua Li, Yongbin Li, Han Liu
Large Language Model Code Generation Real World Code Design Pattern
Utility-inspired Reward Transformations Improve Reinforcement Learning Training of Language Models
Roberto-Rafael Maura-Rivero, Chirag Nagpal, Roma Patel, Francesco Visin
Large Language Model Language Model Training Data Reward Function
Efficient and Responsible Adaptation of Large Language Models for Robust and Equitable Top-k Recommendations
Kirandeep Kaur, Manya Chadha, Vinayak Gupta, Chirag Shah
Large Language Model High Efficiency Robust Version Recommendation Algorithm Traditional Recommender Ranking Task Top N Recommendation Diverse User
FlairGPT: Repurposing LLMs for Interior Designs
Gabrielle Littlefair, Niladri Shekhar Dutt, Niloy J. Mitra
Large Language Model Indoor Environment Optimal Layout Diverse Design FLAIR Embeddings
CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection
Ruijun Feng, Hammond Pearce, Pietro Liguori, Yulei Sui
Large Language Model Data Detection Source Code Vulnerable Code Soft Prompt Tuning Code Graph
When LLMs Struggle: Reference-less Translation Evaluation for Low-resource Languages
Archchana Sindhujan, Diptesh Kanojia, Constantin Orasan, Shenbin Qian
Large Language Model Machine Translation Low Resource Language Quality Estimation Low Resource Language Pair Reference Free Machine Translation
Federated Fine-Tuning of LLMs: Framework Comparison and Research Directions
Na Yan, Yang Su, Yansha Deng, Robert Schober
Large Language Model Fine Tuning New Framework DH Research Interpretable Direction Fine Tuned Large Language Model CG FedLLM
End-to-End Bangla AI for Solving Math Olympiad Problem Benchmark: Leveraging Large Language Model Using Integrated Approach
H.M. Shadman Tabib, Jaber Ahmed Deedar
Large Language Model Retrieval Augmented Generation Reasoning Performance Bangla Natural Language Iterative Reasoning Math Benchmark
Who Does the Giant Number Pile Like Best: Analyzing Fairness in Hiring Contexts
Preethi Seshadri, Seraphina Goldfarb-Tarrant
Large Language Model Procedural Fairness Context Information Retrieval Model Racial Bias Recruitment Domain
RoRA: Efficient Fine-Tuning of LLM with Reliability Optimization for Rank Adaptation
Jun Liu, Zhenglun Kong, Peiyan Dong, Xuan Shen, Pu Zhao, Hao Tang, Geng Yuan, Wei Niu, Wenbin Zhang, Xue Lin, Dong Huang, Yanzhi Wang
Large Language Model Fine Tuning Pruned Model Reliability Assessment Commitment
Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning
Lang Xu, Quentin Anthony, Jacob Hatef, Aamir Shafi, Hari Subramoni, Dhabaleswar K. (DK) Panda
Large Language Model New Frontier GPU Memory Dynamic Bandwidth Computing Cluster

January 7, 2025

HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMs
Ashutosh Singh, Rohitash Chandra
Large Language Model New Framework Social Medium Longitudinal Study

Large Language Model

Papers

DriVLM: Domain Adaptation of Vision-Language Models in Autonomous Driving

A Text-Based Knowledge-Embedded Soft Sensing Modeling Approach for General Industrial Process Tasks Based on Large Language Model

Enhancing Human-Like Responses in Large Language Models

Demystifying Domain-adaptive Post-training for Financial LLMs

Step-by-Step Mastery: Enhancing Soft Constraint Following Ability of Large Language Models

Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words

$\text{Transformer}^2$: Self-adaptive LLMs

Real-Time Textless Dialogue Generation

Do Code LLMs Understand Design Patterns?

Utility-inspired Reward Transformations Improve Reinforcement Learning Training of Language Models

Efficient and Responsible Adaptation of Large Language Models for Robust and Equitable Top-k Recommendations

FlairGPT: Repurposing LLMs for Interior Designs

CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection

When LLMs Struggle: Reference-less Translation Evaluation for Low-resource Languages

Federated Fine-Tuning of LLMs: Framework Comparison and Research Directions

End-to-End Bangla AI for Solving Math Olympiad Problem Benchmark: Leveraging Large Language Model Using Integrated Approach

Who Does the Giant Number Pile Like Best: Analyzing Fairness in Hiring Contexts

RoRA: Efficient Fine-Tuning of LLM with Reliability Optimization for Rank Adaptation

Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning

HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMs