This is a great follow-up to our recent preprint! This small-scale evaluation introduces a framing-resistant prompt and makes a step toward exploring the mitigation space for the framing sensitivity problem.

Patients ask LLMs medical questions — but how they phrase it matters more than it should. Our new preprint explores how different phrasings of patient health questions can lead to inconsistent conclusions, even with the same evidence. [1/6] Full Paper: arxiv.org/abs/2604.05051

Thrilled to share our research showing how LLM models can be influenced by bias from "spun" medical literature is now featured in Northeastern's Khoury news! This shows critical insights as AI enters healthcare. The full paper can be found at arxiv.org/abs/2502.07963

I am at CHI this week to present my poster (Framing Health Information: The Impact of Search Methods and Source Types on User Trust and Satisfaction in the Age of LLMs) on Wednesday April 30 CHI Program Link: programs.sigchi.org/chi/2025/pro... Looking forward to connecting with you all!

LLM-based chatbots are changing how people search for health information—but how do users perceive their quality and trustworthiness compared to other online sources? Our survey study explores these questions. Check it out! www.jmir.org/2025/1/e68560

I'm searching for some comp/ling experts to provide a precise definition of “slop” as it refers to text (see: corp.oup.com/word-of-the-...) I put together a google form that should take no longer than 10 minutes to complete: forms.gle/oWxsCScW3dJU... If you can help, I'd appreciate your input! 🙏

🚨 Do LLMs fall for spin in medical literature? 🤔 In our new preprint, we find that LLMs are susceptible to biased reporting of clinical treatment benefits in abstracts—more so than human experts. 📄🔍 [1/7] Full Paper: arxiv.org/abs/2502.07963 🧵👇