activity
20242026
most citedTxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools

8 citations · 17 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Do LLMs Know What to Ask and When? Evaluating Multi-Turn Information Seeking

Yepeng Huang, Jiawen Zhang, Michelle Dai +4

When a user question is underspecified, a capable model should recognize that its context is insufficient, identify the missing information, ask for it, and respond only once that…

cs.AI2026

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…

q-bio.GN2026

STRAND: Sequence-Conditioned Transport for Single-Cell Perturbations

Boyang Fu, George Dasoulas, Sameer Gabbita +5

Prediction of the transcriptional response of a cell to a genetic perturbation is a central problem in the computational modeling of gene regulation. Perturbations of the same gene…

cs.CL2025

KnowGuard: Knowledge-Driven Abstention for Multi-Round Clinical Reasoning

Xilin Dang, Kexin Chen, Xiaorui Su +7

In clinical practice, physicians refrain from making decisions when patient information is insufficient. This behavior, known as abstention, is a critical safety mechanism preventi…

cs.AI2025★ 8 cited

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…

q-bio.QM2025★ 2 cited

Multimodal AI predicts clinical outcomes of drug combinations from preclinical data

Yepeng Huang, Xiaorui Su, Varun Ullanat +10

Predicting clinical outcomes from preclinical data is essential for selecting safe and effective drug combinations and for reducing late-stage failures. AI models use molecular str…

cs.CL2025★ 3 cited

Multimodal Medical Code Tokenizer

Xiaorui Su, Shvat Messica, Yepeng Huang +5

Foundation models trained on patient electronic health records (EHRs) require tokenizing medical data into sequences of discrete vocabulary items. Existing tokenizers treat medical…

cs.AI2024★ 4 cited

KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA

Xiaorui Su, Yibo Wang, Shanghua Gao +4

Biomedical reasoning integrates structured, codified knowledge with tacit, experience-driven insights. Depending on the context, quantity, and nature of available evidence, researc…