Yibo Chen

This paper introduces scPEFT, a parameter-efficient fine-tuning framework for scLLMs that improves task adaptation with reduced computational costs and enhances performance in disease-specific and cross-species analyses.

This study improves gene relationship prediction using iterative prompt refinement with ChatGPT, achieving better performance for complex gene interactions.

This paper evaluates 21 large language models for mining gene interactions and pathway knowledge, finding significant performance differences between API-based and open-source models.