You can find our data and interface here: github.com/SebaJoe/deci.... Many thanks to my co-lead @sebajoe.bsky.social and our amazing collaborators Barry Wei, @mackert.bsky.social, @ijmarshall.bsky.social, Paul Liang, @ramezkouzy.bsky.social, @byron.bsky.social, and @jessyjli.bsky.social!

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To address these challenges, we propose a communication model that:
- clarifies intent through dialogue
- guides claims toward verifiable evidence
- explains diverse expert perspectives instead of forcing consensus

It reframes medical fact-checking as patient–expert dialogue

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Verifying medical claims wasn’t straightforward for experts. They struggled with:

1️⃣ linking claims to evidence
2️⃣ interpreting underspecified or misguided claims
3️⃣ labeling nuanced claims—often with disagreement

These challenges are inherent to end-to-end fact-checking 🚧

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We study real-world medical claims from Reddit, preserving post context and verifying them with RCT abstracts. 📄
Six experts annotated 20 claims, each with 10 abstracts.

Annotations span:
1️⃣ abstract relevance
2️⃣ claim-level evidence quality
3️⃣ explanations citing abstracts

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Are we fact-checking medical claims the right way? 🩺🤔

Probably not. In our study, even experts struggled to verify Reddit health claims using end-to-end systems.

We show why—and argue fact-checking should be a dialogue, with patients in the loop

arxiv.org/abs/2506.20876

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