2 citations · 3 across the 12 of their papers we have counts for
5 papers · 1 filter
HERO: Harnessing Evidence for Test-time Refinement and Prompt Optimization in Program Generation
Mingyu Lu, Timothy Ossowski, Tristan Naumann +2
Harness optimization improves LLMs by refining reusable prompts and scaffolding, yet requires further adaptation for program generation tasks such as text-to-SQL and text-to-Python…
HealthAgentBench: A Unified Benchmark Suite of Realistic Agentic Healthcare Environments for Challenging Frontier AI Agents
Qianchu Liu, Sheng Zhang, Guanghui Qin +18
As AI agents become increasingly capable of complex, long-horizon reasoning, rigorous evaluation is essential for measuring progress toward real-world healthcare applications. Howe…
CodeClinic: Evaluating Automation of Coding Skills for Clinical Reasoning Agents
Timothy Ossowski, Xinchi Liu, Danyal Maqbool +6
Clinical reasoning agents based on large language models (LLMs) aim to automate tasks such as intensive care unit (ICU) monitoring and patient state tracking from electronic health…
RiskCueBench: Benchmarking Anticipatory Reasoning from Early Risk Cues in Video-Language Models
Sha Luo, Yogesh Prabhu, Timothy Ossowski +2
With the rapid growth of video centered social media, the ability to anticipate risky events from visual data is a promising direction for ensuring public safety and preventing rea…
Scaling medical imaging report generation with multimodal reinforcement learning
Qianchu Liu, Sheng Zhang, Guanghui Qin +10
Frontier models have demonstrated remarkable capabilities in understanding and reasoning with natural-language text, but they still exhibit major competency gaps in multimodal unde…