Melbourne is the place to be this week! 🇦🇺 #SIGIR2026 has officially kicked off, and while we miss Carsten Eickhoff, Harrisen Scells, and Gregory Polyakov back in the office, the Health NLP Lab is well represented in Melbourne this week.

#FeatureFriday Today, we are celebrating a major achievement for Dr. Tassallah Amina Abdullahi! 🎉 On April 20, 2026, Tassallah successfully defended her PhD thesis, “Towards Trustworthy Clinical AI: Knowledge Grounding, Inference Reliability, and Behavioral Control.”

How can we reliably evaluate whether AI-generated text is actually correct? This question is becoming increasingly important as large language models are deployed in high-stakes domains, from healthcare and education to scientific research.

One by one, our PhD students at Brown University are reaching graduation milestones, and today’s post is dedicated to Dr. Ruochen Zhang! 🎉

#ThrowbackThursday to #ICLR2026, where Dr. Ali Bahreinian presented the paper "When Silence Is Golden: Can LLMs Learn to Abstain in Temporal QA and Beyond?" during the poster session.

Need a thought-provoking read for the weekend? Don’t miss this article by Prof. Carsten Eickhoff: “Half of AI health answers are wrong even though they sound convincing,” published in The Conversation EU.

Six days to go! Apply by April 30 for the Director of our new AI Methods & Software Hub. This is a unique opportunity to build and lead a central hub at the intersection of cutting-edge ML research and scientific applications. More information: uni-tuebingen.de/en/128980#c2...

Great conference ahead! We are traveling to the Netherlands to attend #ECIR2026, and we are particularly excited about our tutorial on Mechanistic Interpretability tutorial on Sunday and the Collab-a-thons. Looking forward to insightful exchanges and constructive conversations.

New video presentation available on YouTube! You can now watch Gregory Polyakov, the first author of "Interpretability Analysis of Arithmetic In-Context Learning in Large Language Models", explain their research question, methodology, and results. You can watch the video here:

Interpretability Analysis of Arithmetic In-Context Learning in Large Language Models

Large language models (LLMs) exhibit sophisticated behavior, notably solving arithmetic with only a few in-context examples (ICEs). Yet the computations that connect those examples to the answer…

youtu.be

New video alert! The video presentation of the paper "A Survey on LLM-Assisted Clinical Trial Recruitment" by Dr. Shrestha Ghosh is now live on YouTube. 🎞️ Check out the video here: www.youtube.com/watch?v=fE_3... And don't forget to subscribe to our YouTube channel for more videos!

Heartfelt congratulations to Dr. Michal Golovanevsky! 🎉 On January 30, 2026, our PhD student at Brown University successfully defended her thesis, "Advancing Attention Mechanisms in Multimodal Deep Learning Models", marking the culmination of years of research excellence and intellectual growth.

Thank you to everyone who joined our invited talk last Friday. We were very happy to welcome Kay Brosien from x-cardiac GmbH and to learn from his practical insights on AI regulation in medicine.

Reminder for the talk tomorrow: see you at the Hörsaal of Maria-von-Linden-Straße 6 at 11:00 A.M.

Health NLP Lab@health-nlp.com · 6mo ago

Next Friday, we’re looking forward to welcoming Kay Brosien, COO of x-cardiac GmbH, to Tübingen for a talk on one of the less glamorous but absolutely critical parts of AI research in medicine: regulation⚖️

Like many areas of machine learning, information retrieval has increasingly adopted large neural models, making mechanistic interpretability more important than ever. A key technique in this space is activation patching, which aims to localize where and how models encode relevance signals.

Next Friday, we’re looking forward to welcoming Kay Brosien, COO of x-cardiac GmbH, to Tübingen for a talk on one of the less glamorous but absolutely critical parts of AI research in medicine: regulation⚖️

@twiml.bsky.social are organizing their 4th workshop to bring together ML researchers and enthusiasts in Tübingen. It’s a wonderful opportunity to meet peers, exchange ideas, discuss research, and share your academic journey. Follow their page and stay tuned for more details about the workshop.

@twiml.bsky.social · 6mo ago

🚀 Exciting news! The 4th TWiML Workshop is coming soon 📅 March 6, 2026 Incredible speakers, insightful discussions, and great social moments ahead. More details coming soon—save the date!

🚀 #JobAlert! Permanent Administrative Staff Member position open at the Tübingen AI Center, a vibrant AI research hub at @unituebingen.bsky.social. You’ll support our Central Office in financial and HR administration and help run everyday office operations. 🔗 tuebingen.ai/careers/admi...

Did you know...? 🤔 Health NLP Lab also has a YouTube channel! We are reviving our YouTube channel as a platform for paper presentations and science communication. We hope this will make our research more accessible to a broader audience. 🔗 Subscribe here: www.youtube.com/@health-nlp

Meet Miriam Rateike, and join us in welcoming Health NLP Lab's newest member!

Last week, we had the pleasure of hosting Maik Fröbe @maik-froebe.bsky.social, from Friedrich Schiller University Jena, who was invited to give a guest lecture and a talk to our group about his recent work on evaluation in information retrieval.

#ThrowbackThursday to SIGIR 2024, where Catherine Chen presented two papers of hers. Both presentations were recorded and are available on the ACM YouTube channel (links below) 👇

Last week, Dr. Nils Feldhus @nfel.bsky.social, postdoctoral researcher at @tuberlin.bsky.social and @bifold.berlin, visited our lab and presented his research during our weekly lab meeting.

We are starting off 2026 with exciting news: Our paper "Beyond Multiple Choice: Evaluating Steering Vectors for Adaptive Free-Form Summarization" got accepted at #EACL2026! ✒️ Authors: Joschka Braun, Carsten Eickhoff, and Ali Bahrainian 📃 Paper: arxiv.org/abs/2505.24859

Beyond Multiple Choice: Evaluating Steering Vectors for Adaptive Free-Form Summarization

Steering vectors are a lightweight method for controlling text properties by adding a learned bias to language model activations at inference time. So far, steering vectors have predominantly been…

arxiv.org

As we wrap up 2025, we’re grateful for a year of great ideas, meaningful discussions, and fruitful collaborations that help advance research and knowledge. Thank you to our collaborators, colleagues, and community; we look forward to continuing our endeavors in 2026. Wishing everyone happy holidays!

We’re excited to share that Dr. Shrestha Ghosh will be presenting her work at the IJCNLP–AACL 2025 (@aaclmeeting.bsky.social) 📍 Mumbai, India 🎤 Paper presentation: 22.12.2025 @ 14:45 🧠 Paper: "Cohort Discovery: A Survey on LLM-Assisted Clinical Trial Recruitment"

👋 Meet Gregory Polyakov: PhD researcher based in Tübingen! Gregory completed his Master’s in Applied Mathematics and Computer Science at MIPT, and after working as an NLP research engineer at Huawei’s Noah’s Ark Lab, he joined the Health NLP Lab to dive deeper into academic ML research.

#ResearchHighlight 🔬 Like many fields, drug discovery has been revolutionized by advances in Machine Learning and Artificial Intelligence, and a key player has been molecular representation — turning molecules into machine-understandable and processable formats.

👋 Meet Florian Rottach — Data Scientist at @boehringerglobal.bsky.social and PhD researcher in our lab! He brings a unique interdisciplinary background and a passion for applying machine learning to life sciences. #MeetTheLab

🗓️Today in San Diego: Dr. Shrestha Ghosh presents “Investigating RAG-based Approaches in Clinical Trial and Patient Matching” at #ML4H. Her work tests how RAG handles clinical-trial matching across varying task complexity, longitudinal evidence, and abstention—showing what truly drives performance.

Amina @amilah-dul.bsky.social presents her latest work on Knowledge Graphs at @wimlworkshop.bsky.social next week. Building on her previous work (arxiv.org/abs/2502.13344), she extends KG-guided reasoning beyond biomedicine to broader knowledge discovery. #ResearchHighligh #LLM #KnowledgeGraph