7 papers
Evaluating Large Language Models in Scientific Discovery
Zhangde Song, Jieyu Lu, Yuanqi Du +53
Large language models (LLMs) are increasingly applied to scientific research, yet prevailing science benchmarks probe decontextualized knowledge and overlook the iterative reasonin…
Generative AI for Biosciences: Emerging Threats and Roadmap to Biosecurity
Zaixi Zhang, Souradip Chakraborty, Amrit Singh Bedi +16
The rapid adoption of generative artificial intelligence (GenAI) in the biosciences is transforming biotechnology, medicine, and synthetic biology. Yet this advancement is intrinsi…
SafeProtein: Red-Teaming Framework and Benchmark for Protein Foundation Models
Jigang Fan, Zhenghong Zhou, Ruofan Jin +3
Proteins play crucial roles in almost all biological processes. The advancement of deep learning has greatly accelerated the development of protein foundation models, leading to si…
Securing the Language of Life: Inheritable Watermarks from DNA Language Models to Proteins
Zaixi Zhang, Ruofan Jin, Le Cong +1
DNA language models have revolutionized our ability to understand and design DNA sequences--the fundamental language of life--with unprecedented precision, enabling transformative…
CRISPR-GPT for Agentic Automation of Gene-editing Experiments
Yuanhao Qu, Kaixuan Huang, Ming Yin +11
The introduction of genome engineering technology has transformed biomedical research, making it possible to make precise changes to genetic information. However, creating an effic…
Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning
Ming Yin, Yuanhao Qu, Ling Yang +2
We investigate how to teach large language models (LLMs) to perform scientific reasoning by leveraging expert discussions as a learning signal. Focusing on the genomics domain, we…