🏆 𝗕𝗲𝘀𝘁 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱 𝗮𝘁 𝗦𝗲𝗺𝗘𝘃𝗮𝗹-𝟮𝟬𝟮𝟲 𝗦𝗵𝗮𝗿𝗲𝗱 𝗧𝗮𝘀𝗸 𝟮! We're proud to share that work from UKP Lab has received the 𝗕𝗲𝘀𝘁 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱 𝗼𝗳 𝗦𝗲𝗺𝗘𝘃𝗮𝗹-𝟮𝟬𝟮𝟲 𝗦𝗵𝗮𝗿𝗲𝗱 𝗧𝗮𝘀𝗸 𝟮, recognizing the scientific contribution behind a system that also topped the leaderboard with 𝟭𝘀𝘁 𝗽𝗹𝗮𝗰𝗲 𝗶𝗻 𝗦𝘂𝗯𝘁𝗮𝘀𝗸𝘀 𝟭 𝗮𝗻𝗱 𝟮𝗔 😲

🎓 𝗚𝘂𝗲𝘀𝘁 𝗧𝗮𝗹𝗸 𝗮𝘁 𝘁𝗵𝗲 𝗨𝗞𝗣 𝗟𝗮𝗯 We were thrilled to welcome our long-term collaborator, co-supervisor of PhD students and close colleague Prof. Preslav Nakov, Professor and Department Chair for #NLP at the #MBZUAI in Abu Dhabi, for an invited talk at the UKP Lab in #TUDarmstadt.

𝗙𝗿𝗼𝗺 𝗗𝗮𝗿𝗺𝘀𝘁𝗮𝗱𝘁 𝘁𝗼 𝗔𝗖𝗟 𝟮𝟬𝟮𝟲 𝗶𝗻 𝗦𝗮𝗻 𝗗𝗶𝗲𝗴𝗼 Four UKP Lab papers got an early audience this week. @timbmg.bsky.social, @ibigoulaeva.bsky.social, and @tongletj.bsky.social presented their work at the Post-CVPR Pre-ICML Poster Session, [...]

👋 𝗡𝗲𝘄 𝗳𝗮𝗰𝗲 𝗮𝘁 𝘁𝗵𝗲 𝗨𝗞𝗣 𝗟𝗮𝗯: 𝗔 𝘄𝗮𝗿𝗺 𝘄𝗲𝗹𝗰𝗼𝗺𝗲 𝘁𝗼 𝗔𝗻𝗱𝗿𝗲𝗮! @andreamoleri.bsky.social joins us as a doctoral researcher, jointly supervised by Prof. Dr. @igurevych.bsky.social and Prof. Dr. Marcus Rohrbach.

🚀 𝗟𝗮𝘁𝗲𝘀𝘁 𝗡𝗟𝗣𝗲𝗲𝗿 𝗥𝗲𝗹𝗲𝗮𝘀𝗲 𝗳𝗿𝗼𝗺 𝗔𝗥𝗥 𝟮𝟬𝟮𝟲 𝗶𝘀 𝗼𝘂𝘁! Grab your Peer Review data: tudatalib.ulb.tu-darmstadt.de/handle/tudat... 📊 𝗘𝗔𝗖𝗟 𝟮𝟲 𝗔𝗰𝗰𝗲𝗽𝘁𝗲𝗱 𝗣𝗮𝗽𝗲𝗿 𝗗𝗮𝘁𝗮: ✅ 647 papers ✅ 942 reviews ✅ 329 meta-reviews ✅ 550 papers with rebuttals

🧮 LREC 2026 proceedings are out, and I just counted the annotation tool citations. 💡 INCEpTION came out on top with 39 citations and 28 of those actually using it! ❤️ Massive thanks to the LREC community for choosing INCEpTION! #lrec2026 #inceptiontap #opensource #textannotation #opensource

INCEpTION @ LREC 2026

As you might know, I am the maintainer of the INCEpTION open source tool for the semantic and linguistic annotation of text documents. And the LREC conference is a good way to gauge how popular INCEpT...

linkedin.com

✨ 𝗨𝗞𝗣 𝗗𝗮𝘆 𝟮𝟬𝟮𝟲 ✨ Once a year, the entire UKP Lab comes together for a day of scientific exchange, discussion, and community building – the UKP Day. On May 28, 2026, we gathered at @tuda.bsky.social to share ideas, learn from one another, and connect with colleagues from across the field.

💻 𝗪𝗲𝗹𝗰𝗼𝗺𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗨𝗞𝗣 𝗟𝗮𝗯, 𝗣𝗵𝘂 𝗚𝗶𝗮 𝗛𝗼𝗮𝗻𝗴! We're happy to welcome Phu Gia Hoang as a doctoral researcher at the UKP Lab. At UKP, Phu works on 𝗺𝗲𝗰𝗵𝗮𝗻𝗶𝘀𝘁𝗶𝗰 𝗶𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆, exploring 𝗴𝗲𝗼𝗺𝗲𝘁𝗿𝗶𝗰 𝗶𝗻𝘁𝘂𝗶𝘁𝗶𝗼𝗻 as a lens to better understand how language models represent and process information internally.

🚀 𝗪𝗲'𝗿𝗲 𝗵𝗶𝗿𝗶𝗻𝗴: 𝗣𝗼𝘀𝘁𝗱𝗼𝗰𝘁𝗼𝗿𝗮𝗹 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝗿 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗘𝗥𝗖 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗚𝗿𝗮𝗻𝘁 𝗜𝗻𝘁𝗲𝗿𝗧𝗲𝘅𝘁 𝗮𝘁 𝗨𝗞𝗣 𝗟𝗮𝗯, 𝗧𝗨 𝗗𝗮𝗿𝗺𝘀𝘁𝗮𝗱𝘁 If you work on #LLMs that reason across complex documents, not just within them, this role is for you.

🌍 𝗝𝗼𝗶𝗻𝗶𝗻𝗴 𝘁𝗵𝗲 𝗨𝗞𝗣 𝗟𝗮𝗯: 𝗪𝗲𝗹𝗰𝗼𝗺𝗲, 𝗞𝘂𝗿𝘁 𝗠𝗶𝗰𝗮𝗹𝗹𝗲𝗳! We’re glad to welcome Kurt Micallef as a new postdoctoral researcher at the UKP Lab. Kurt’s previous work focused on 𝗡𝗟𝗣 𝗳𝗼𝗿 𝗠𝗮𝗹𝘁𝗲𝘀𝗲, where he worked on low resource and cross lingual techniques, developed Maltese centric language models, [...]

💬➡️🤖 𝗧𝗵𝗲 𝗢𝗿𝗶𝗴𝗶𝗻 𝗼𝗳 𝘁𝗵𝗲 𝗡𝗲𝘄 𝗪𝗼𝗿𝗹𝗱: 𝗛𝗼𝘄 𝗪𝗲 𝗜𝗻𝘃𝗲𝗻𝘁𝗲𝗱 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 At #BiennaleTecnologia in Turin, I have joined Renato Beninatto to discuss the scientific ideas that helped make today’s #LLMs possible: from decades of machine translation research to the rise of attention and the Transformer.

🤔 How can we innovate reading and writing workflows for students, educators, researchers – and at the same time make it useful to science? 🚀 Meet 𝗖𝗔𝗥𝗘: — now with a 𝗺𝗮𝗷𝗼𝗿 𝘂𝗽𝗱𝗮𝘁𝗲 and 𝗳𝘂𝗹𝗹𝘆 𝗼𝗽𝗲𝗻 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 on GitHub. Check out the 🧵 below if you want to know more.

🗓️ 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

REVAS — AI-Powered Peer Review Feedback for Academics

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

revas.mbzuai.ac.ae

🔍 𝗨𝘀𝗶𝗻𝗴 𝗾𝘂𝗮𝗻𝘁𝗶𝘇𝗲𝗱 𝗟𝗟𝗠𝘀 𝘁𝗼 𝗯𝗼𝗼𝘀𝘁 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆? 𝗪𝗮𝘁𝗰𝗵 𝘁𝗵𝗲 𝘀𝗼𝗰𝗶𝗮𝗹 𝘁𝗿𝗮𝗱𝗲-𝗼𝗳𝗳𝘀, 𝘁𝗼𝗼. ⚠️ Quantization makes LLMs cheaper and more deployable. But what does it do to fairness, toxicity, and bias? 💡 The research gap: a systematic picture of how quantization affects social behavior across models and tasks.

#EACL2026 in Rabat is in full swing ✨ From papers to hallway discussions - it’s great to see our team actively contributing to this year’s #EACL conference. Say hello to this group if you’re on site 👇

🎓 𝗚𝘂𝗲𝘀𝘁 𝗧𝗮𝗹𝗸 𝗮𝘁 𝘁𝗵𝗲 𝗨𝗞𝗣 𝗟𝗮𝗯 👋 We were pleased to welcome Yova Kementchedjhieva, Assistant Professor at the MBZUAI (Mohamed bin Zayed University of Artificial Intelligence), for a guest talk at the UKP Lab in Darmstadt.

🚀 From school project to award-winning AI for mental health Meet Mihai Ghețu (@mihai-eduard-ghetu.bsky.social) - a remarkably talented high school student and the creator of Mental Mint: An Empathic AI-Powered Psychosocial Companion Robot for Victims of Emotional Shocks and Bullying.

LMs that "know more" about toxicity are less toxic! Our #TACL 📄 connects behavior and internals: 💠 LMs amplify toxicity beyond humans 💠 Information about toxicity peaks in lower layers 💠 Bypassing these layers increases toxicity More details👇 #NLProc #interpretability (1/🧵)

𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗿𝗲𝘃𝗶𝗲𝘄𝗲𝗿𝘀 𝗰𝗮𝗻 𝗺𝗶𝘀𝘀 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝗲𝗿𝗿𝗼𝗿𝘀. 👀 LLM-generated reviews may look convincing — but how reliable are they in practice? In our recent TACL paper, we introduce a 𝗰𝗼𝗻𝘁𝗿𝗼𝗹𝗹𝗲𝗱 𝗰𝗼𝘂𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝘁𝘂𝗮𝗹 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 to systematically test automatic reviewers.

𝗘𝗺𝗽𝗮𝘁𝗵𝘆 𝗶𝘀𝗻’𝘁 𝗲𝗻𝗼𝘂𝗴𝗵: 𝗔𝗜-𝗯𝗮𝘀𝗲𝗱 𝘁𝗵𝗲𝗿𝗮𝗽𝗶𝘀𝘁𝘀 𝗰𝗿𝘂𝗰𝗶𝗮𝗹𝗹𝘆 𝗻𝗲𝗲𝗱 𝗰𝘂𝗹𝘁𝘂𝗿𝗮𝗹 𝗰𝗼𝗻𝘁𝗲𝘅𝘁! 🤖🫶🌍 Millions of people worldwide lack access to mental health care. LLMs are increasingly explored as scalable tools for empathetic support, 𝗯𝘂𝘁 they often miss 𝗮 𝗸𝗲𝘆 𝗱𝗶𝗺𝗲𝗻𝘀𝗶𝗼𝗻: 𝗰𝘂𝗹𝘁𝘂𝗿𝗲.

🔥 𝗠𝗲𝘁𝗮-𝗿𝗲𝘃𝗶𝗲𝘄𝗶𝗻𝗴 𝗶𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗮 𝘀𝘂𝗺𝗺𝗮𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻 - 𝗶𝘁’𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴. In our new paper, “𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗠𝗮𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗗𝗲𝗹𝗶𝗯𝗲𝗿𝗮𝘁𝗶𝗼𝗻: 𝗠𝗲𝘁𝗮-𝗿𝗲𝘃𝗶𝗲𝘄𝗶𝗻𝗴 𝗮𝘀 𝗮 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁-𝗴𝗿𝗼𝘂𝗻𝗱𝗲𝗱 𝗗𝗶𝗮𝗹𝗼𝗴𝘂𝗲”, we ask how AI can support meta-reviewers 𝗶𝗻 𝘁𝗵𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 — 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗶𝗻 𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝗶𝗻𝗮𝗹 𝗿𝗲𝗽𝗼𝗿𝘁.

🤔 𝗗𝗶𝗱 𝘆𝗼𝘂𝗿 𝗟𝗟𝗠 𝗿𝗲𝗮𝗹𝗹𝘆 𝗳𝗼𝗿𝗴𝗲𝘁 𝘆𝗼𝘂𝗿 𝗽𝗿𝗶𝘃𝗮𝘁𝗲 𝗱𝗮𝘁𝗮 - 𝗼𝗿 𝗷𝘂𝘀𝘁 𝗴𝗲𝘁 𝗾𝘂𝗶𝗲𝘁𝗲𝗿 𝗮𝗯𝗼𝘂𝘁 𝗶𝘁? 🧠 Machine unlearning aims to remove specific training data (e.g., private info) without full retraining. But does it actually 𝗿𝗲𝗺𝗼𝘃𝗲 𝘁𝗵𝗲 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹?

🧠🔗 How can we link semantically related sentences across documents - 𝙬𝙞𝙩𝙝 𝙯𝙚𝙧𝙤 𝙡𝙖𝙗𝙚𝙡𝙚𝙙 𝙙𝙖𝙩𝙖? Meet 𝗔𝗕𝗖𝗗-𝗟𝗜𝗡𝗞 🚀

“𝗬𝗼𝘂𝗿 𝗽𝗮𝗽𝗲𝗿 𝗶𝘀 𝗻𝗼𝘁 𝗻𝗼𝘃𝗲𝗹 𝗲𝗻𝗼𝘂𝗴𝗵.”🙅 We have all seen this infamous comment from Reviewer #2. But 𝗵𝗼𝘄 𝗿𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗶𝘀 𝘁𝗵𝗲 𝗻𝗼𝘃𝗲𝗹𝘁𝘆 𝗮𝘀𝘀𝗲𝘀𝘀𝗺𝗲𝗻𝘁 𝘁𝗼𝗱𝗮𝘆?🤔

🚨 Introducing 𝗚𝗿𝗶𝘁𝗛𝗼𝗽𝗽𝗲𝗿, the new State-of-the-Art Multi-Hop Dense Retriever 🦗 Current approaches to multi-hop retrieval face critical trade-offs. 🔎 Decomposition-based methods break complex queries into simpler steps, but they are computationally expensive and difficult to train end-to-end.

🎓 𝗗𝗶𝘀𝘀𝗲𝗿𝘁𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝗳𝗲𝗻𝘀𝗲 – 𝗖𝗲𝗰𝗶𝗹𝗶𝗮 Congratulations to @ccliu.bsky.social on the successful PhD defense at the UKP Lab of @tuda.bsky.social In her thesis 𝘎𝘦𝘯𝘦𝘳𝘢𝘭𝘪𝘻𝘢𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘈𝘥𝘢𝘱𝘵𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘓𝘢𝘯𝘨𝘶𝘢𝘨𝘦 𝘔𝘰𝘥𝘦𝘭𝘴 𝘵𝘰 𝘓𝘢𝘯𝘨𝘶𝘢𝘨𝘦𝘴 𝘢𝘯𝘥 𝘊𝘶𝘭𝘵𝘶𝘳𝘦𝘴, Cecilia investigates ...

🎓 𝗔𝗜 𝘁𝗼 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝗰𝗼𝘂𝗿𝘀𝗲 𝗶𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗼𝗿𝘀 𝗻𝗼𝘁 𝘁𝗼 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝘁𝗵𝗲𝗺! In 𝘄𝗶𝗻𝘁𝗲𝗿 𝘀𝗲𝗺𝗲𝘀𝘁𝗲𝗿 𝟮𝟬𝟮𝟱/𝟮𝟲, our AI-based system 𝗟𝗟𝗠𝗲𝗻𝘁𝗼𝗿 has supported teaching the course 𝘐𝘯𝘵𝘳𝘰𝘥𝘶𝘤𝘵𝘪𝘰𝘯 𝘵𝘰 𝘚𝘤𝘪𝘦𝘯𝘵𝘪𝘧𝘪𝘤 𝘞𝘰𝘳𝘬 at @cs-tudarmstadt.bsky.social

Thanks a lot to everyone for the support, guidance, mentoring, collaboration, and great moments over the past years! 🙏 Without you, this journey wouldn't have been such a pleasure — and now excited to see what the future brings! 🚀

UKP Lab@ukplab.bsky.social · 5mo ago

🎓 𝗣𝗵𝗗 𝗱𝗲𝗳𝗲𝗻𝘀𝗲 𝗰𝗼𝗻𝗴𝗿𝗮𝘁𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗔𝗻𝗱𝗿𝗲𝗮𝘀 𝗪𝗮𝗹𝗱𝗶𝘀! Congratulations to @tresiwald.bsky.social on the successful defense of his dissertation “𝘈𝘯 𝘐𝘯𝘵𝘦𝘨𝘳𝘢𝘭 𝘝𝘪𝘦𝘸 𝘰𝘯 𝘵𝘩𝘦 𝘙𝘦𝘭𝘪𝘢𝘣𝘪𝘭𝘪𝘵𝘺 𝘰𝘧 𝘓𝘢𝘯𝘨𝘶𝘢𝘨𝘦 𝘔𝘰𝘥𝘦𝘭𝘴 𝘧𝘰𝘳 𝘊𝘰𝘮𝘱𝘶𝘵𝘢𝘵𝘪𝘰𝘯𝘢𝘭 𝘈𝘳𝘨𝘶𝘮𝘦𝘯𝘵𝘢𝘵𝘪𝘰𝘯”, held at Technische Universität Darmstadt on February 17th, 2026.

📣🧪 𝗡𝗲𝘄 𝗿𝗲𝘀𝘂𝗹𝘁𝘀: 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗻𝗴 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗪𝗿𝗶𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗘𝘅𝗽𝗲𝗿𝘁 𝗣𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 👉 Today we are presenting our first two papers that build on HAI-Co2, our recent position paper on human-ai text co-construction in expert domains:

🎓 𝗣𝗵𝗗 𝗱𝗲𝗳𝗲𝗻𝘀𝗲 𝗰𝗼𝗻𝗴𝗿𝗮𝘁𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗔𝗻𝗱𝗿𝗲𝗮𝘀 𝗪𝗮𝗹𝗱𝗶𝘀! Congratulations to @tresiwald.bsky.social on the successful defense of his dissertation “𝘈𝘯 𝘐𝘯𝘵𝘦𝘨𝘳𝘢𝘭 𝘝𝘪𝘦𝘸 𝘰𝘯 𝘵𝘩𝘦 𝘙𝘦𝘭𝘪𝘢𝘣𝘪𝘭𝘪𝘵𝘺 𝘰𝘧 𝘓𝘢𝘯𝘨𝘶𝘢𝘨𝘦 𝘔𝘰𝘥𝘦𝘭𝘴 𝘧𝘰𝘳 𝘊𝘰𝘮𝘱𝘶𝘵𝘢𝘵𝘪𝘰𝘯𝘢𝘭 𝘈𝘳𝘨𝘶𝘮𝘦𝘯𝘵𝘢𝘵𝘪𝘰𝘯”, held at Technische Universität Darmstadt on February 17th, 2026.