39 citations · 41 across the 11 of their papers we have counts for
7 papers · 1 filter
FABSVer: Faster Training and Better Self-Verification for LLM Mathematical Reasoning
Haihui Pan, Junwei Bao, Hongfei Jiang +1
While large language models have made significant progress in mathematical reasoning, they remain unreliable at judging the correctness of their own solutions. Existing approaches…
Elo-Evolve: A Co-evolutionary Framework for Language Model Alignment
Jing Zhao, Ting Zhen, Junwei Bao +2
Current alignment methods for Large Language Models (LLMs) rely on compressing vast amounts of human preference data into static, absolute reward functions, leading to data scarcit…
Quality-constrained Entropy Maximization Policy Optimization for LLM Diversity
Haihui Pan, Yuzhong Hong, Kaichen Zhang +4
In many large language model (LLM) alignment applications, users expect not only high-quality outputs but also substantial diversity. However, existing methods often face a fundame…
Preference-Oriented Supervised Fine-Tuning: Favoring Target Model Over Aligned Large Language Models
Yuchen Fan, Yuzhong Hong, Qiushi Wang +3
Alignment, endowing a pre-trained Large language model (LLM) with the ability to follow instructions, is crucial for its real-world applications. Conventional supervised fine-tunin…
BoRA: Bi-dimensional Weight-Decomposed Low-Rank Adaptation
Qiushi Wang, Yuchen Fan, Junwei Bao +2
In recent years, Parameter-Efficient Fine-Tuning (PEFT) methods like Low-Rank Adaptation (LoRA) have significantly enhanced the adaptability of large-scale pre-trained models. Weig…
Multi-Turn Interactions for Text-to-SQL with Large Language Models
Guanming Xiong, Junwei Bao, Hongfei Jiang +2
This study explores text-to-SQL parsing by leveraging the powerful reasoning capabilities of large language models (LLMs). Despite recent advancements, existing LLM-based methods a…
Interactive-KBQA: Multi-Turn Interactions for Knowledge Base Question Answering with Large Language Models
Guanming Xiong, Junwei Bao, Wen Zhao
This study explores the realm of knowledge base question answering (KBQA). KBQA is considered a challenging task, particularly in parsing intricate questions into executable logica…