5 papers
Evolutionary Curriculum Learning Improves Biological Sequence Modeling
Richard Zhu, Kento Nishi
Variational autoencoders (VAEs) trained on multiple sequence alignments (MSAs) have emerged as powerful generative models for biological sequences, with applications ranging from d…
An AI agent for treatment reasoning over a biomedical tool universe
Shanghua Gao, Ayush Noori, Richard Zhu +13
Treatment reasoning underpins every therapeutic decision, integrating disease context, comorbidities, medications, contraindications, and evolving biomedical knowledge to select an…
AIA Forecaster: Technical Report
Rohan Alur, Bradly C. Stadie, Daniel Kang +11
This technical report describes the AIA Forecaster, a Large Language Model (LLM)-based system for judgmental forecasting using unstructured data. The AIA Forecaster approach combin…
ToolUniverse: An open platform for democratizing AI scientists
Shanghua Gao, Richard Zhu, Pengwei Sui +8
AI scientists are emerging computational systems that serve as collaborative partners in discovery. These systems remain difficult to build because they are bespoke, tied to rigid…
TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools
Shanghua Gao, Richard Zhu, Zhenglun Kong +5
Precision therapeutics require multimodal adaptive models that generate personalized treatment recommendations. We introduce TxAgent, an AI agent that leverages multi-step reasonin…