Jasmijn Bastings

Hello

Hi, welcome to my website! My name is Jasmijn (she/they), and I’m a Senior Research Scientist at Google DeepMind. I’d like to make machine learning (or “AI”) work for everyone. To help get there I’m currently interested in the following topics:

• Interpretability, Explainable AI (XAI), explainability
• Bias, gender bias, gender-fair language, gender-fair language technology
• AI & Society
• Trustworthy ML, Trustworthy AI, trustworthiness

I received my PhD from ILLC, University of Amsterdam, where I was advised by Wilker Aziz, Ivan Titov and Khalil Sima’an.

News

• I won an outstanding Area Chair award at ACL 2023!
• June 2023: I will be part of the project “An Interdisciplinary Analysis of gender-based discrimination in Translation Technology”, funded by the Digital Sciences for Society program of Tilburg University, a collaboration with Eva Vanmassenhove (NLP/translation), Hanna Lukkari (Law), Seunghyun Song (Philosophy).
• I started a YouTube channel for BlackboxNLP. Check it out and subscibe here: youtube.com/@blackboxnlp.
• You can now find me on Mastodon: @jasmijn@sigmoid.social or https://sigmoid.social/@jasmijn.

Publications

Recent publications

• New Dissecting Recall of Factual Associations in Auto-Regressive Language Models. Mor Geva, Jasmijn Bastings, Katja Filippova, Amir Globerson. Preprint.
• “Will You Find These Shortcuts?” A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification. Jasmijn Bastings, Sebastian Ebert, Polina Zablotskaia, Anders Sandholm, Katja Filippova. EMNLP 2022. [blog]
• Diagnosing ai explanation methods with folk concepts of behavior. Alon Jacovi, Jasmijn Bastings, Sebastian Gehrmann, Yoav Goldberg, Katja Filippova. 2021.

See my full publication list on my Google Scholar profile.

Highlighted publications

• The elephant in the interpretability room: Why use attention as explanation when we have saliency methods?. Jasmijn Bastings, Katja Filippova. BlackboxNLP 2020.
• Interpretable neural predictions with differentiable binary variables. Jasmijn Bastings, Wilker Aziz, Ivan Titov. ACL 2019.
• Joey NMT: A Minimalist NMT Toolkit for Novices. Julia Kreutzer, Jasmijn Bastings, Stefan Riezler. EMNLP 2019. [code]
• Graph convolutional encoders for syntax-aware neural machine translation Jasmijn Bastings, Ivan Titov, Wilker Aziz, Diego Marcheggiani, Khalil Sima’an. EMNLP 2017.

You can find a full list of my publications on my Google Scholar profile.

Blog posts

• The Annotated Encoder-Decoder. Explains implementing RNN-based NMT models in PyTorch.

Code

• Interpretable Neural Predictions with Differentiable Binary Variables contains the HardKuma distribution that allows (hybrid) binary samples (with true zeros and ones) that allow gradients to pass through.
• Joey NMT is an easy-to-use, educational, and benchmarked NMT toolkit for novices that I developed with Julia Kreutzer and is currently maintained by Mayumi Ohta.
• FREVAL is an all-fragments parser evaluation metric that I developed with Khalil Sima’an.

Talks

• EMNLP 2020 Blackbox NLP. The Elephant in the Interpretability Room. (PDF)
• ACL 2019. Interpretable Neural Predictions with Differentiable Binary Variables (Google Slides)
• EMNLP 2017. Graph Convolutional Encoders for Syntax-Aware Neural Machine Translation (Google Slides)

CV

• 2019-Now, Research Scientist, Google. Berlin & Amsterdam.
• 2015-2020. PhD in AI, ILLC, University of Amsterdam. Defended 8 October 2020.*
• 2009-2012, MSc in AI, University of Amsterdam.
• 2006-2009, BSc in AI, Utrecht University.

Reviewing / Area Chair / Committees

I was a co-organizer of:

• Blackbox NLP 2022 (co-located with EMNLP 2022)
• Blackbox NLP 2021 (co-located with EMNLP 2021)

I was area chair (AC) / action editor (AE) for the following conferences:

• ACL (2021, 2022, 2023) (Interpretability and Analysis of Models for NLP)
• EMNLP (2021, 2022) (Interpretability and Analysis of Models for NLP)
• ACL rolling review (2021-2022)
• EACL (2021) (Machine Learning for NLP)
• NAACL (2021) (Interpretability and Analysis of Models for NLP)

I reviewed for the following conferences and workshops:

• ACL (2019, 2020)
• EMNLP (2018, 2019, 2020)
• CoNNL (2018, 2019)
• ICLR (2020)
• MT Summit (2019)
• WMT (2018, 2019)
• Analyzing and interpreting neural networks for NLP (BlackboxNLP, 2019, 2020)
• Debugging Machine Learning Models (Debug ML, ICLR Workshop, 2019)
• Workshop on Neural Generation and Translation (WNGT, 2018, 2019, 2020)
• Workshop on Representation Learning for NLP (RepL4NLP, 2020)
• Workshop on Structured Prediction for NLP (SPNLP, 2019)

Contact

• Mastodon
• You can find me on Twitter: @jasmijnbastings.
• My code is on Github: github.com/bastings.

https://orcid.org/0000-0002-5445-4417