Grzegorz Chrupała

I am an Associate Professor affiliated with the Center for Cognitive Science and Artificial Intelligence at Tilburg University, where I lead the Computational Linguistics and Psycholinguistics research unit.

I received my PhD from the School of Computing at Dublin City University. After that I worked as a postdoctoral researcher at the Spoken Language Systems group at Saarland University. I am interested in computation in biological and artificial systems, and connections between them.
See full bio.

News

• New preprint: The rise and evolution of a referential code in populations of bee-like agents.
• Paper accepted to EMNLP 2026: Beyond Decodability: Reconstructing Language Model Representations with an Encoding Probe by Gaofei Shen, Martijn Bentum, Tom Lentz, Afra Alishahi and Grzegorz Chrupała.
• Paper accepted to LREC: Mechanistic Interpretability Meets Cognitive Linguistics: Modelling Locative Image Schemas in the Circuit Framework by Mattia Proietti, Afra Alishahi, Grzegorz Chrupała and Alessandro Lenci.
• Gabriele Sarti, whose work I co-supervised with Arianna Bisazza and Malvina Nissim, defended his PhD thesis, and has thus become the first InDeep PhD.
• Paper accepted to TACL: QE4PE: Word-level Quality Estimation for Human Post-Editing.
• We taught a tutorial on Interpretability Techniques for Speech Models at Interspeech 2025.
• Paper published at Interspeech 2025: On the reliability of feature attribution methods for speech classification.
• Hosein presented Posthoc Disentanglement of Textual and Acoustic Features in Self-Supervised Speech Encoders at an ICML workshop on actionable interpretability.
• I have joined the board of the Dutch Open Speech Technology Foundation.
• I am publicity co-chair for Interspeech 2025.
• I am an action editor for TACL.

People

• Gaofei Shen. PhD candidate, Interpretability techniques for spoken language models.
• Hosein Mohebbi. PhD candidate, Analyzing and interpreting deep neural models of language.
• Lisa Lepp. PhD candidate, Machine Translation for sign and spoken languages.
• Céline Angonin. PhD candidate, bioacoustics.

Alumni

• Gabriele Sarti. PhD thesis: From Insights to Impact: Actionable Interpretability for Neural Machine Translation.
• Chris Emmery. PhD thesis: User-Centered Security in Natural Language Processing.
• Bertrand Higy. Postdoc, Understanding visually grounded spoken language via multi-tasking.
• Patrick Bos and Christiaan Meijer. E-science engineers, Understanding visually grounded spoken language via multi-tasking.
• Ákos Kádár. PhD thesis: Learning Visually Grounded and Multilingual Representations.

Publications

For the complete list of publications check: Google Scholar | Semantic Scholar | DBLP | ACL Anthology | ORCID

Selected papers

1. Shen, G., Watkins, M., Alishahi, A., Bisazza, A., Chrupała, G. (2024). Encoding of lexical tone in self-supervised models of spoken language. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (pp. 4250-4261).
   Paper | Code

2. Nikolaus, M., Alishahi, A. & Chrupała, G. (2022). Learning English with Peppa Pig. Transactions of the Association for Computational Linguistics, 10, 922–936.
   Paper | Code

3. Chrupała, G. (2022). Visually grounded models of spoken language: A survey of datasets, architectures and evaluation techniques. Journal of Artificial Intelligence Research, 73, 673–707.
   Paper

4. Chrupała, G., & Alishahi, A. (2019). Correlating Neural and Symbolic Representations of Language. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 2952–2962).
   Paper | Code

5. Chrupała, G., Gelderloos, L., & Alishahi, A. (2017). Representations of language in a model of visually grounded speech signal. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 613–622).
   Paper | Code

Selected Talks

• Promises and pitfalls of unified NLP, NLG in the Lowlands, 2025
• Putting natural back into Natural Language Processing, Second Dutch Speech Tech Day, 2024
• Opening the black box of foundation models. Indeep Outreach/Amsterdam AI Meetup, 2023.
• TAISIG Talks - The opportunities and limitations of Deep Learning, Tilburg University, 2022.
• Learning language from Peppa Pig. ILLC seminar, University of Amsterdam, 2022.
• Visually Grounded Models of Spoken Language and their Analysis and Evaluation. Lectures on Computational Linguistics, AILC, 2021.

Bio

Grzegorz Chrupała is an Associate Professor at the Center for Cognitive Science and Artificial Intelligence at Tilburg University, where he leads the Computational Linguistics and Psycholinguistics research unit. Previously he did postdoctoral research at the Spoken Language Systems group at Saarland University. He received his doctoral degree from the School of Computing at Dublin City University.

He is interested in computation in biological and artificial systems, and connections between them. His research focuses especially on computational models of learning (spoken) language in naturalistic multimodal settings, as well as analysis and interpretation of representations emerging in deep learning architectures.

He is an Action Editor for TACL, and regularly serves as Senior Area Chair for major NLP and AI conferences such as ACL and EMNLP. He was one of the creators of the popular BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP. His research has been funded by the Dutch Research Council (NWO).

Contact

Grzegorz Chrupała
Center for Cognitive Science and Artificial Intelligence
Department of Intelligent Systems
Tilburg University
PO Box 90153
5000 LE Tilburg
The Netherlands

Bluesky: @grzegorz.chrupala.me
Web: grzegorz.chrupala.me
Email: grzegorz@chrupala.me