4 papers
AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists
Yifei Li, Hanane Nour Moussa, Ziru Chen +16
Despite long-standing efforts in accelerating scientific discovery with AI, building AI co-scientists remains challenging due to limited high-quality data for training and evaluati…
Large Language Models for Controllable Multi-property Multi-objective Molecule Optimization
Vishal Dey, Xiao Hu, Xia Ning
In real-world drug design, molecule optimization requires selectively improving multiple molecular properties up to pharmaceutically relevant levels, while maintaining others that…
GeLLMO: Generalizing Large Language Models for Multi-property Molecule Optimization
Vishal Dey, Xiao Hu, Xia Ning
Despite recent advancements, most computational methods for molecule optimization are constrained to single- or double-property optimization tasks and suffer from poor scalability…
ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
Ziru Chen, Shijie Chen, Yuting Ning +17
The advancements of large language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked…