39 citations · 41 across the 11 of their papers we have counts for
5 papers · 1 filter
Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model
Yuzhong Hong, Hanshan Zhang, Junwei Bao +2
Since the debut of DPO, it has been shown that aligning a target LLM with human preferences via the KL-constrained RLHF loss is mathematically equivalent to a special kind of rewar…
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…