Excited to be at #ICML2025 to present our paper on 'pragmatic misalignment' in (deployed!) RAG systems: narrowly "accurate" responses that can be profoundly misinterpreted by readers. It's especially dangerous for consequential domains like medicine! arxiv.org/pdf/2502.14898

🩺 General LLMs perform well on clinical NLP tasks, even though they never see EHR data. How? 🚀 Our CHIL 2025 paper, led by my PhD student Furong Jia, probes the pre-training datasets behind popular LLMs to investigate how online medical sources drive performance. 📄 Paper: arxiv.org/abs/2505.15024

The AHLI CHIL Doctoral Symposium deadline is fast approaching! 🎓 Apply by March 15, 2025 at chil.ahli.cc/submit/docto... #CHIL2025

Free access link: ai.nejm.org/stoken/defau... This is joint work with @dmshanmugam.bsky.social , @rajmovva.bsky.social, Jon Kleinberg, @monicaagrawal.bsky.social, @mdredze.bsky.social, Kadija Ferryman, Judy Wawira Gichoya, @jurafsky.bsky.social, Pang Wei Koh, @karenlevy.bsky.social...

Using Large Language Models to Promote Health Equity

While the discussion about the effects of large language models (LLMs) on health equity has been largely cautionary, LLMs also present significant opportunities for improving health equity. We high...

ai.nejm.org

Our article on using LLMs to promote health equity is out in New England Journal of Medicine AI! 85% of equity-related LLM papers focus on *harms*. But also vital are the equity-related *opportunities* LLMs create: detecting bias, extracting structured data, and improving access to health info.

We have a new review on generative AI in medicine, to appear in the Annual Review of Biomedical Data Science! We cover over 250 papers in the recent literature to provide an updated overview of use cases and challenges for generative AI in medicine.

I am recruiting PhD students at Duke! Please apply to Duke CS or CBB if you are interested in developing new methods and paradigms for NLP/LLMs in healthcare. For details, see here: monicaagrawal.com/home/researc....