4 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Simple, Efficient and Scalable Structure-aware Adapter Boosts Protein Language Models
Yang Tan, Mingchen Li, Bingxin Zhou +7
Fine-tuning Pre-trained protein language models (PLMs) has emerged as a prominent strategy for enhancing downstream prediction tasks, often outperforming traditional supervised lea…
cs.CL2023★ 2 cited
PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications
Yang Tan, Mingchen Li, Pan Tan +4
Large protein language models are adept at capturing the underlying evolutionary information in primary structures, offering significant practical value for protein engineering. Co…
cs.CL2023★ 4 cited
MedChatZH: a Better Medical Adviser Learns from Better Instructions
Yang Tan, Mingchen Li, Zijie Huang +2
Generative large language models (LLMs) have shown great success in various applications, including question-answering (QA) and dialogue systems. However, in specialized domains li…