Publications

Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ili’c, Daniel Hesslow, Roman Castagn’e, Alexandra Sasha Luccioni, Franccois Yvon, Matthias Gallé, Jonathan Tow, Alexander M. Rush, Stella Rose Biderman, Albert Webson, Pawan Sasanka Ammanamanchi, Thomas Wang, Benoît Sagot, Niklas Muennighoff, Albert Villanova del Moral, et al. 2022. Bloom: A 176b-parameter open-access multilingual language model. Arxiv, abs/2211.05100.

Oskar van der Wal*, Dominik Bachmann*, Alina Leidinger, Leendert van Maanen, Willem Zuidema, and Katrin Schulz. 2024. Undesirable biases in NLP: addressing challenges of measurement. Journal of artificial intelligence research.

Stella Biderman, Hailey Schoelkopf, Quentin Gregory Anthony, Herbie Bradley, Kyle O’Brien, Eric Hallahan, Mohammad Aflah Khan, Shivanshu Purohit, Usvsn Sai Prashanth, Edward Raff, Aviya Skowron, Lintang Sutawika, and Oskar van der Wal. 2023. Pythia: A suite for analyzing large language models across training and scaling. In Proceedings of the 40th international conference on machine learning, volume 202, pages 2397–2430. PMLR.

Abhijith Chintam, Rahel Beloch, Willem Zuidema, Michael Hanna*, and Oskar van der Wal*. 2023. Identifying and adapting transformer-components responsible for gender bias in an english language model. In Proceedings of the 6th blackboxnlp workshop: Analyzing and interpreting neural networks for nlp, pages 379–394.

Jaap Jumelet, Michael Hanna, Marianne de Heer Kloots, Anna Langedijk, Charlotte Pouw, and Oskar van der Wal. 2023. Chapgtp, illc’s attempt at raising a babylm: Improving data efficiency by automatic task formation. In Proceedings of the babylm challenge at the 27th conference on computational natural language learning, pages 74–85.

Gabriele Sarti, Nils Feldhus, Ludwig Sickert, and Oskar van der Wal. 2023. Inseq: An interpretability toolkit for sequence generation models. In Proceedings of the 61st annual meeting of the association for computational linguistics (volume 3: System demonstrations), pages 421–435, Toronto, Canada. Association for Computational Linguistics.

Zeerak Talat, Aurélie Névéol, Stella Biderman, Miruna Clinciu, Manan Dey, Shayne Longpre, Sasha Luccioni, Maraim Masoud, Margaret Mitchell, Dragomir Radev, Shanya Sharma, Arjun Subramonian, Jaesung Tae, Samson Tan, Deepak Tunuguntla, and Oskar van der Wal. 2022. You reap what you sow: On the challenges of bias evaluation under multilingual settings. In Proceedings of bigscience episode \#5 – workshop on challenges & perspectives in creating large language models, pages 26–41, virtual+Dublin. Association for Computational Linguistics.

Oskar van der Wal*, Dominik Bachmann*, Alina Leidinger, Leendert van Maanen, Willem Zuidema, and Katrin Schulz. 2024. Undesirable biases in NLP: addressing challenges of measurement. Journal of artificial intelligence research.

Oskar van der Wal, Jaap Jumelet, Katrin Schulz, and Willem Zuidema. 2022. The birth of bias: A case study on the evolution of gender bias in an english language model. In Proceedings of the 4th workshop on gender bias in natural language processing (gebnlp), page 75.

Oskar van der Wal, Silvan de Boer, Elia Bruni, and Dieuwke Hupkes. 2020. The grammar of emergent languages. In Proceedings of the 2020 conference on empirical methods in natural language processing (emnlp), pages 3339–3359, Online. Association for Computational Linguistics.