6 citations · 16 across the 8 of their papers we have counts for
4 papers · 1 filter
Completion Collaboration: Scaling Collaborative Effort with Agents
Shannon Zejiang Shen, Valerie Chen, Ken Gu +11
Current evaluations of agents remain centered around one-shot task completion, failing to account for the inherently iterative and collaborative nature of many real-world problems,…
Diagnosing our datasets: How does my language model learn clinical information?
Furong Jia, David Sontag, Monica Agrawal
Large language models (LLMs) have performed well across various clinical natural language processing tasks, despite not being directly trained on electronic health record (EHR) dat…
CodingGenie: A Proactive LLM-Powered Programming Assistant
Sebastian Zhao, Alan Zhu, Hussein Mozannar +3
While developers increasingly adopt tools powered by large language models (LLMs) in day-to-day workflows, these tools still require explicit user invocation. To seamlessly integra…
Large Language Models are Powerful Electronic Health Record Encoders
Stefan Hegselmann, Georg von Arnim, Tillmann Rheude +5
Electronic Health Records (EHRs) offer considerable potential for clinical prediction, but their complexity and heterogeneity challenge traditional machine learning. Domain-specifi…