6 citations · 21 across the 12 of their papers we have counts for
6 papers · 1 filter
Stanford Sleep Bench: Evaluating Polysomnography Pre-training Methods for Sleep Foundation Models
Magnus Ruud Kjaer, Rahul Thapa, Gauri Ganjoo +7
Polysomnography (PSG), the gold standard test for sleep analysis, generates vast amounts of multimodal clinical data, presenting an opportunity to leverage self-supervised represen…
Disentangling Reasoning and Knowledge in Medical Large Language Models
Rahul Thapa, Qingyang Wu, Kevin Wu +11
Medical reasoning in large language models (LLMs) aims to emulate clinicians' diagnostic thinking, but current benchmarks such as MedQA-USMLE, MedMCQA, and PubMedQA often mix reaso…
How Well Can General Vision-Language Models Learn Medicine By Watching Public Educational Videos?
Rahul Thapa, Andrew Li, Qingyang Wu +8
Publicly available biomedical videos, such as those on YouTube, serve as valuable educational resources for medical students. Unlike standard machine learning datasets, these video…
MedCaseReasoning: Evaluating and learning diagnostic reasoning from clinical case reports
Kevin Wu, Eric Wu, Rahul Thapa +7
Doctors and patients alike increasingly use Large Language Models (LLMs) to diagnose clinical cases. However, unlike domains such as math or coding, where correctness can be object…
SMIR: Efficient Synthetic Data Pipeline To Improve Multi-Image Reasoning
Andrew Li, Rahul Thapa, Rahul Chalamala +3
Vision-Language Models (VLMs) excel at understanding single images, aided by high-quality instruction datasets. However, multi-image reasoning remains underexplored in the open-sou…
OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning
Pan Lu, Bowen Chen, Sheng Liu +3
Solving complex reasoning tasks may involve visual understanding, domain knowledge retrieval, numerical calculation, and multi-step reasoning. Existing methods augment large langua…