Jannis Vamvas, PhD
Language AI Researcher at University of Zurich
Recent posts
Just Released: Machine Translation Engine for Romansh
Covering the six varieties of the Romansh language.
Read post
OpenAI's Speculative Decoding,
Reverse-Engineered
Why LLMs are faster if we give them a draft to complete.
Read postWenn ChatGPT den Smartvote-Fragebogen ausfüllt
Sind Sprachmodelle politisch voreingenommen?
Read postRecent publications
Vilém Zouhar, Niyati Bafna, Mukund Choudhary, Maike Züfle, Sara Rajaee, Pinzhen Chen, Jannis Vamvas, and 237 others. 2026. Last Translation Benchmark. Pre-print. [cite] [data] [code]
Jannis Vamvas, Ignacio Pérez Prat, Angela Heldstab, Dominic P. Fischer, Sina Ahmadi and Rico Sennrich. 2026. Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varieties. Accepted to Findings of EMNLP 2026. [cite] [data] [model] [code]
Michelle Wastl, Jannis Vamvas and Rico Sennrich. 2026. Scaling Unsupervised Word Alignment to Documents via Structural Constraints. Accepted to EMNLP 2026. [cite] [data] [code, code]
Hanxu Hu, Zdeněk Šnajdr, Pinzhen Chen, Jannis Vamvas and Rico Sennrich. 2026. Reinforcement Learning Elicits Contextual Learning of Unseen Language Translation. Accepted to Findings of EMNLP 2026. [cite] [code]
Michelle Wastl, Jannis Vamvas and Rico Sennrich. 2026. SwissGov-RSD: A Human-annotated, Cross-lingual Benchmark for Token-level Recognition of Semantic Differences Between Related Documents. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 31134–31163, San Diego, California, United States. Association for Computational Linguistics. [cite] [data] [code] ★ Selected as SAC Highlight
Recent teaching
| Fall 2026 | Lecturer Fundamentals of Large Language Models |
| Fall 2026 | Lecturer Mathematical Foundations for Language Technology 1 |
| Fall 2026 | Co-instructor Ethics of AI for Language and Speech |
| Spring 2026 | Lecturer CAS Generative AI |
| Spring 2026 | Lecturer Text Generation with Language Models |