most citedDrugImproverGPT: A Large Language Model for Drug Optimization with Fine-Tuning via Structured Policy Optimization

1 citations · 1 across the 8 of their papers we have counts for

collaborators

11 papers

cs.AI2026

Wrong but Useful: Trajectory Value Beyond Answer Correctness in Multi-Agent Messages

Chih-Hsuan Yang, Anjir Ahmed Chowdhury, Cheng-Hau Yang +7

Multi-agent reasoning systems often use agreement, confidence, or automated scores to decide which messages should shape a final answer. Such filtering assumes that a message likel…

cs.RO2026

AEGIS: Assay-Aware Protocol Validation and Runtime Monitoring for Open-Source Liquid Handling Robots

Priyanka V. Setty, Arvind Ramanathan, Ian Foster +1

Self-driving laboratories increasingly rely on low-cost liquid handlers such as the Opentrons OT-2, which ship without the pressure-based aspiration monitoring of Hamilton or Tecan…

cs.AI2026

Precise but Uncoupled: Reviewer Precision Does Not Guarantee Critique Uptake in Multi-Agent Math Reasoning

Chih-Hsuan Yang, Jingyan Jiang, Vikram Vasudevan +7

Many math- and science-oriented agent systems use hierarchical designs with specialized reviewer roles, assuming that a dedicated review stage should help turn wrong candidates int…

cs.AI2026

BioAlchemy: Distilling Biological Literature into Reasoning-Ready Reinforcement Learning Training Data

Brian Hsu, Ozan Gökdemir, Carlo Siebenschuh +7

Despite the large corpus of biology training text, the impact of reasoning models on biological research generally lags behind math and coding. In this work, we show that biology q…

cs.RO2026

PRISM: Protocol Refinement through Intelligent Simulation Modeling

Brian Hsu, Priyanka V Setty, Rory M Butler +7

Automating experimental protocol design and execution remains as a fundamental bottleneck in realizing self-driving laboratories. We introduce PRISM (Protocol Refinement through In…

cs.LG2025

FragmentGPT: A Unified GPT Model for Fragment Growing, Linking, and Merging in Molecular Design

Xuefeng Liu, Songhao Jiang, Qinan Huang +5

Fragment-Based Drug Discovery (FBDD) is a popular approach in early drug development, but designing effective linkers to combine disconnected molecular fragments into chemically an…