1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
OctoMed: Data Recipes for State-of-the-Art Multimodal Medical Reasoning
Timothy Ossowski, Sheng Zhang, Qianchu Liu +5
High-quality and carefully curated data is a cornerstone of training medical large language models, as it directly impacts both generalization and robustness to unseen clinical tas…
OLIVE: Object Level In-Context Visual Embeddings
Timothy Ossowski, Junjie Hu
Recent generalist vision-language models (VLMs) have demonstrated impressive reasoning capabilities across diverse multimodal tasks. However, these models still struggle with fine-…
How does Multi-Task Training Affect Transformer In-Context Capabilities? Investigations with Function Classes
Harmon Bhasin, Timothy Ossowski, Yiqiao Zhong +1
Large language models (LLM) have recently shown the extraordinary ability to perform unseen tasks based on few-shot examples provided as text, also known as in-context learning (IC…