Mastodawn

🔗 𝗥𝗲𝗹𝗮𝘁𝗲𝗱 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀
ARR Data Collection: https://arr-data.aclweb.org/

Dagstuhl Seminar 2024 on Peer Review: https://www.dagstuhl.de/en/seminars/seminar-calendar/seminar-details/24052

#NLP #NLProc #PeerReview #MachineLearning #ArtificialIntelligence #NLPeer #ARR #EACL2026 #OpenScience #OpenData #ResearchData #AIResearch #LanguageTechnology #UKPLab #TUDarmstadt

ACL Rolling Review Data Collection (ARR-DC)

Collecting and curating a large-scale dataset of peer reviews and associated metadata from the ACL community.

ARR Data Collection

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UKP Lab May 21

Learn more about Phu and his work: https://phusroyal.github.io/

Welcome to the team, Phu! 👋

#UKPLab #TUDarmstadt #MBZUAI #NLP #NLProc #MechanisticInterpretability #LLMs #AIInterpretability

Homepage - PhusRoyal

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UKP Lab Apr 29

At UKP, he will apply his expertise in 𝗺𝗼𝗱𝗲𝗹 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴 to the 𝗱𝗼𝗺𝗮𝗶𝗻 𝗮𝗱𝗮𝗽𝘁𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗺𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗺𝗼𝗱𝗲𝗹𝘀, with a focus on aligning models with 𝗵𝘂𝗺𝗮𝗻 𝗽𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 and better understanding 𝗺𝗼𝗱𝗲𝗹 𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝗶𝗲𝘀.

Learn more about Kurt and his work: https://www.kurtmica.com/

Looking forward to having you on the team, Kurt! 👋

#UKPLab #TUDarmstadt #NLP #NLProc #MultimodalAI #LowResourceNLP #LLMs

Kurt Micallef

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UKP Lab Apr 22

Maintained at @UKPLab .

Follow for more updates! Let’s build this together 🚀

#UKPLab #OpenScience #EdTech #AI #NLP #NLProc #PeerReview #ResearchSoftware #HigherEducation

🧵6/6

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UKP Lab Mar 27

Authors: Federico Marcuzzi (INSAIT - Institute for Computer Science, Artificial Intelligence and Technology), Xuefei Ning (Tsinghua University), Roy Schwartz (The Hebrew University of Jerusalem), and Iryna Gurevych (UKP Lab, Technische Universität Darmstadt and ATHENE Center).

See you at #EACL2026 in Rabat 🕌!

#UKPLab #NLProc #ResponsibleAI #Quantization #MLSafety #Fairness #TrustworthyAI #ModelCompression #LLMSafety #EthicalAI #NLP #AIResearch

UKP Lab Mar 26

#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 👇

#NLP #NLProc #UKPLab #LLMs #AIResearch #AcademicLife #TUDa

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UKP Lab Mar 25

🔍 Prof. Kementchedjhieva also discussed alternative approaches to improve vision-to-language alignment while maintaining strong language capabilities.

💬 We thank Prof. Kementchedjhieva for the insightful talk and the discussion with UKP members on multimodal modeling and the future of vision-language systems.

#UKPLab #MultimodalAI #VisionLanguageModels #NLP #GuestTalk #NLProc #MBZUAI #TUDa

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UKP Lab Mar 24

🏆 We’re proud to share that his project won 𝟭𝘀𝘁 𝗣𝗿𝗶𝘇𝗲 𝗮𝘁 𝘁𝗵𝗲 𝗥𝗲𝗴𝗶𝗼𝗻𝗮𝗹 𝗣𝗵𝗮𝘀𝗲, qualifying him for the national phase!

Congratulations, Mihai, on this well-deserved success and on addressing such an important and timely challenge with empathy and innovation. 👏

Follow Mihai’s journey:
LinkedIn: https://www.linkedin.com/in/mihai-eduard-ghetu
Bluesky: https://bsky.app/profile/mihai-eduard-ghetu.bsky.social

#AIforMentalHealth #JugendForscht #AIInnovation #MentalHealthTech #NextGenAI #AIforGood #YoungTalent #UKPLab

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UKP Lab Mar 23

Work by Nils Dycke & Iryna Gurevych (Ubiquitous Knowledge Processing (UKP) Lab, Technische Universität Darmstadt and National Research Center for Applied Cybersecurity ATHENE)

See you at #EACL2026 in Rabat 🕌!

#UKPLab #LLMs #PeerReview #AIforScience #TrustworthyAI #NLP #Evaluation

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UKP Lab Mar 18

📄 Paper: https://arxiv.org/abs/2508.07902

💻 Code and data: https://github.com/UKPLab/eacl2026-culturecare

🔗 Project: https://github.com/UKPLab/arxiv2025-culturecare

Follow the authors Chen Cecilia Liu, Hiba Arnaout, Nils Kovacic, and Iryna Gurevych from the UKP Lab, Technische Universität Darmstadt and hessian.ai, as well as Dana Atzil-Slonim from the Psychology Department, Bar-Ilan University.

See you this week in Rabat 🕌! #EACL2026

#UKPLab #CulturalNLP #ResponsibleAI #NLProc #NLP4MentalHealth #NLPsych #NLP #MentalHealth

Tailored Emotional LLM-Supporter: Enhancing Cultural Sensitivity

Large language models (LLMs) show promise in offering emotional support and generating empathetic responses for individuals in distress, but their ability to deliver culturally sensitive support remains underexplored due to a lack of resources. In this work, we introduce CultureCare, the first dataset designed for this task, spanning four cultures and including 1729 distress messages, 1523 cultural signals, and 1041 support strategies with fine-grained emotional and cultural annotations. Leveraging CultureCare, we (i) develop and test four adaptation strategies for guiding three state-of-the-art LLMs toward culturally sensitive responses; (ii) conduct comprehensive evaluations using LLM-as-a-Judge, in-culture human annotators, and clinical psychologists; (iii) show that adapted LLMs outperform anonymous online peer responses, and that simple cultural role-play is insufficient for cultural sensitivity; and (iv) explore the application of LLMs in clinical training, where experts highlight their potential in fostering cultural competence in novice therapists.

arXiv.org