2 citations · 4 across the 3 of their papers we have counts for
5 papers · 1 filter
ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domain
Haochen Zhao, Xiangru Tang, Ziran Yang +8
The advancement and extensive application of large language models (LLMs) have been remarkable, including their use in scientific research assistance. However, these models often g…
Step-Back Profiling: Distilling User History for Personalized Scientific Writing
Xiangru Tang, Xingyao Zhang, Yanjun Shao +6
Large language models (LLM) excel at a variety of natural language processing tasks, yet they struggle to generate personalized content for individuals, particularly in real-world…
MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise
Chunyuan Deng, Xiangru Tang, Yilun Zhao +5
Recently, large language models (LLMs) have evolved into interactive agents, proficient in planning, tool use, and task execution across a wide variety of tasks. However, without s…
ChatCell: Facilitating Single-Cell Analysis with Natural Language
Yin Fang, Kangwei Liu, Ningyu Zhang +7
As Large Language Models (LLMs) rapidly evolve, their influence in science is becoming increasingly prominent. The emerging capabilities of LLMs in task generalization and free-for…
GersteinLab at MEDIQA-Chat 2023: Clinical Note Summarization from Doctor-Patient Conversations through Fine-tuning and In-context Learning
Xiangru Tang, Andrew Tran, Jeffrey Tan +1
This paper presents our contribution to the MEDIQA-2023 Dialogue2Note shared task, encompassing both subtask A and subtask B. We approach the task as a dialogue summarization probl…