5 citations · 12 across the 5 of their papers we have counts for
5 papers
LLM-as-a-Verifier: A General-Purpose Verification Framework
Jacky Kwok, Shulu Li, Pranav Atreya +6
Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we identify verification, the abi…
SmartAlert: Implementing Machine Learning-Driven Clinical Decision Support for Inpatient Lab Utilization Reduction
April S. Liang, Fatemeh Amrollahi, Yixing Jiang +21
Repetitive laboratory testing unlikely to yield clinically useful information is a common practice that burdens patients and increases healthcare costs. Education and feedback inte…
BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text
Jiageng Wu, Bowen Gu, Ren Zhou +14
Large language models (LLMs) hold great promise for medical applications and are evolving rapidly, with new models being released at an accelerated pace. However, benchmarking on l…
MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents
Yixing Jiang, Kameron C. Black, Gloria Geng +4
Recent large language models (LLMs) have demonstrated significant advancements, particularly in their ability to serve as agents thereby surpassing their traditional role as chatbo…
Many-Shot In-Context Learning in Multimodal Foundation Models
Yixing Jiang, Jeremy Irvin, Ji Hun Wang +3
Large language models are effective at few-shot in-context learning (ICL). Recent advancements in multimodal foundation models have enabled unprecedentedly long context windows, pr…