5 citations · 16 across the 9 of their papers we have counts for
10 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…
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…
GeneBreaker: Jailbreak Attacks against DNA Language Models with Pathogenicity Guidance
Zaixi Zhang, Zhenghong Zhou, Ruofan Jin +2
DNA, encoding genetic instructions for almost all living organisms, fuels groundbreaking advances in genomics and synthetic biology. Recently, DNA Foundation Models have achieved s…
FoldMark: Protecting Protein Generative Models with Watermarking
Zaixi Zhang, Ruofan Jin, Kaidi Fu +3
Protein structure is key to understanding protein function and is essential for progress in bioengineering, drug discovery, and molecular biology. Recently, with the incorporation…
Latent Diffusion Models for Controllable RNA Sequence Generation
Kaixuan Huang, Yukang Yang, Kaidi Fu +3
This work presents RNAdiffusion, a latent diffusion model for generating and optimizing discrete RNA sequences of variable lengths. RNA is a key intermediary between DNA and protei…
A 5' UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions
Yanyi Chu, Dan Yu, Yupeng Li +5
The 5' UTR, a regulatory region at the beginning of an mRNA molecule, plays a crucial role in regulating the translation process and impacts the protein expression level. Language…
Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization
Hui Yuan, Chengzhuo Ni, Huazheng Wang +4
Directed Evolution (DE), a landmark wet-lab method originated in 1960s, enables discovery of novel protein designs via evolving a population of candidate sequences. Recent advances…