Jasmijn Bastings
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Graph convolutional encoders for syntax-aware neural machine translation
J Bastings, I Titov, W Aziz, D Marcheggiani, K Sima'an
EMNLP, 2017
Exploiting semantics in neural machine translation with graph convolutional networks
D Marcheggiani, J Bastings, I Titov
NAACL, 2018
Interpretable neural predictions with differentiable binary variables
J Bastings, W Aziz, I Titov
ACL, 2019
Joey NMT: A minimalist NMT toolkit for novices
J Kreutzer, J Bastings, S Riezler
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
Jump to better conclusions: SCAN both left and right
J Bastings, M Baroni, J Weston, K Cho, D Kiela
EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2018
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models
I Tenney, J Wexler, J Bastings, T Bolukbasi, A Coenen, S Gehrmann, ...
arXiv preprint arXiv:2008.05122, 2020
The elephant in the interpretability room: Why use attention as explanation when we have saliency methods?
J Bastings, K Filippova
Proceedings of the 2020 EMNLP Workshop BlackboxNLP: Analyzing and …, 2020
We Need to Talk About Random Splits
A Søgaard, S Ebert, J Bastings, K Filippova
EACL, 2021
Modeling latent sentence structure in neural machine translation
J Bastings, W Aziz, I Titov, K Sima'an
WNMT 2018 (Extended Abstract), 2019
All Fragments Count in Parser Evaluation
J Bastings, K Sima'an
LREC, 78-82, 2014
The MultiBERTs: BERT Reproductions for Robustness Analysis
T Sellam, S Yadlowsky, J Wei, N Saphra, A D'Amour, T Linzen, J Bastings, ...
arXiv preprint arXiv:2106.16163, 2021
A tale of two sequences Interpretable and linguistically-informed deep learning for natural language processing
J Bastings
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