News & Updates

The latest announcements, achievements, and events from the WüNLP Chair.

August 9, 2026

WueNLP members will present six papers at EMNLP26!

Six papers (co-)authored by WueNLP members will be presented at EMNLP26 (5 at Main conference and one in Findings), Oct 24-29 in Budapest! Paper links coming soon!

July 16, 2026

Three open research positions at WüNLP open_in_new

We are hiring! The WüNLP group has three open positions for PhD students and/or postdoctoral researchers. The advertised topics span LLM post-training, modular architectures for sample-efficient adaptation of language models, and vision-language-action models for robotic manipulation. All positions are open until filled, with the earliest possible starting dates — get in touch if you are interested.

April 15, 2026

Two papers accepted at ACL 2026

Two of our papers have been accepted at ACL 2026: "Compositional Steering of Large Language Models with Steering Tokens" in the Main Conference, and "One Script to Rule Them All" in Findings. Congratulations to all co-authors!

March 20, 2026

Outstanding Senior Area Chair Award at EACL 2026 open_in_new

Goran Glavaš received an Outstanding Senior Area Chair (SAC) Award at EACL 2026. The award recognizes outstanding service to the community in steering the review process and shaping the program of a major area at the conference.

March 10, 2026

Gregor Geigle completes his PhD with summa cum laude open_in_new

Congratulations to Gregor Geigle, who successfully completed his PhD on multilingual vision-language models with the highest distinction, summa cum laude. His work advanced the state of the art in building, scaling, and evaluating large multilingual vision-language models.

January 20, 2026

Paper on vision-language embedding models accepted at EACL 2026 open_in_new

Our short paper "Mind Your Special Tokens in Vision-Language Embedding Models" has been accepted at EACL 2026. The work analyzes the outsized role that special tokens play in the representations produced by vision-language embedding models, and what this means for downstream retrieval and matching.