3 papers
cs.LG2026
Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training
Chengqian Zhang, Wei Zhu, Kyumin Lee
Post-training has become essential for adapting large language models (LLMs) to complex downstream behaviors, including instruction following, preference alignment, and multi-step…
cs.LG2025
Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning
Zhengyu Hu, Yichuan Li, Zhengyu Chen +4
Textual Attributed Graphs (TAGs) are crucial for modeling complex real-world systems, yet leveraging large language models (LLMs) for TAGs presents unique challenges due to the gap…
cs.SE2024
From Critique to Clarity: A Pathway to Faithful and Personalized Code Explanations with Large Language Models
Zexing Xu, Zhuang Luo, Yichuan Li +2
In the realm of software development, providing accurate and personalized code explanations is crucial for both technical professionals and business stakeholders. Technical profess…