Dirk Hovy

@dirkhovy.bsky.social

Professor @milanlp.bsky.social for #NLProc, compsocsci, #ML Also at http://dirkhovy.com/

Text as Data has been a wonderful, long-running, non-archival workshop for empirical research at the intersection of AI and social science (especially work involving text). After a few years off, it will be happening again this year as a one-day event in early October!

Denis@dpeskoff.bsky.social · 3w ago

Do you work across computational methods, social sciences, and the humanities? Submit to Text as Data 2026! 📄 One-page submissions 🔓 Non-archival ⏰ Due August 1 📍 October 5 @UCBerkeley tada2026.org

Thank you, @punarpuli.bsky.social, for a great article! Find our paper and more insights from Jiaxin Pei, Sanmi Koyejo, @dirkhovy.bsky.social, and me in this thread👇 bsky.app/profile/joac...

Joachim Baumann@joachimbaumann.bsky.social · 3mo ago

Can you boost your AI review scores by asking an LLM to rewrite your paper? Yes! We call it paper laundering Our @icmlconf.bsky.social spotlight paper argues current AI reviewers aren't ready to automate peer review, and outlines what a science of peer review automation should look like 🧵👇 #ICML2026

First page of the ICML 2026 spotlight paper "Stop Automating Peer Review Without Rigorous Evaluation" by Joachim Baumann, Jiaxin Pei, Sanmi Koyejo, and Dirk Hovy (Stanford University and Bocconi University). The abstract argues that today's AI systems should not be used to produce paper reviews, grounded in two empirical findings: a "hivemind effect" where AI reviewers show excessive agreement and reduce perspective diversity, and "paper laundering," where prompting an LLM to rewrite a paper trivially increases AI reviewer scores through stylistic changes rather than scientific improvements. The paper calls for a science of peer review automation rather than wholesale deployment of general-purpose LLMs.

Could not be prouder of @zeerak.bsky.social for this accomplishment: from first paper ever (based on an MSc thesis) to 10-year ToT award. We could not have anticipated the lasting impact of this paper, but it's a great honor – and a wonderful story for any student/advisor team (see Zee's thread).

Zeerak Talat زیرک طلعت (they/them)@zeerak.bsky.social · 4w ago

Thrilled to have been awarded the Association for Computational Linguistics 2016 test of time award for my first ever paper, written with/under the guidance of @dirkhovy.bsky.social A couple of cute things about the paper/its genesis/its outcomes

Photo of a test of time award for the paper "Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter"

On the heels of a fantastic Dagstuhl seminar on Social Intelligence in AI (thx, @jennhu.bsky.social, @maartensap.bsky.social, @tomerullman.bsky.social, & Lucie Flek), a callback to how we thought about this 5 years ago.

MilaNLP Lab@milanlp.bsky.social · 2mo ago

#TBT #NLProc 'Importance of Modeling Social Factors of Language: Theory and Practice' by @dirkhovy.bsky.social, Diyi Yang discusses NLP limitations, calling for focus on social factors, not just content. aclanthology.org/2021.naacl-m...

📢⚠️ IMPORTANT DATE CORRECTION: the ARR deadline for EACL 2027 is Aug 3, 2026 (not Aug 6 as previously announced). EACL is earlier than usual in '27, so this is the only viable ARR cycle! 📚 All areas of CL/NLP + related fields welcome. Full CfP coming soon. #NLProc #EACL2027

EACL 2027@eaclmeeting.bsky.social · 3mo ago

Attention #NLProc researchers, the EACL 2027 website is officially LIVE: 2027.eacl.org! 🎉 🇬🇷 Join us in Athens, Greece (Mar 9-13, 2027) at #EACL2027 📅 ARR submission deadline: Aug 6, 2026. Open to all areas of CL/NLP + related fields. Stay tuned for the detailed CfP soon!

Picture of the Acropolis in Athens, Greece

🗓️ The ARR March review deadline is approaching: April 20 AoE. Finishing up your review? Run it through REVAS, a peer review assistant that makes your suggestions more actionable, flags unsupported claims, and grounds your feedback in the paper. 👉 revas.mbzuai.ac.ae

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REVAS analyzes the weakness section of your peer review, scoring each paragraph on actionability, helpfulness, grounding, and verifiability.

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