Supervision

Here you can find links to the PhD and MSc theses I supervised or co-supervised.

PhD

Ongoing: Nicola De Cao, Bryan Eikema, Pedro Ferreira, Joris Baan, Evgenia Ilia.

Completed

• Gonçalo Correia. 2022. Learnable Sparsity and Weak Supervision for Data-Efficient, Transparent, and Compact Neural Models
• Jasmijn Bastings. 2020. A Tale of Two Sequences: Interpretable and Linguistically-Informed Deep Learning for Natural Language Processing
• Philip Schulz. 2020. Latent Variable Models for Machine Translation and How to Learn Them
• Joachim Daiber. 2018. Typologically Robust Statistical Machine Translation
• Miloš Stanojević. 2017. Permutation Forests for Modeling Word Order in Machine Translation

MSc

• Frank Verhoef. 2023. Improving Dialogue Generation in Longer Conversations by Explicitly Modeling Mentalizing and Joint Co-construction
• Damiaan Reijnaers, 2023. Exploiting Machine Translationese for Source Language Identification
• John Gkountouras. 2023. The Fine Art of Quantization: Harnessing Efficiency in Large Language Models
• Gerson Foks. 2023. Towards Efficient Minimum Bayes Risk Decoding
• Ivo Verhoven. 2022. Inductive Biases for Morphologically Informed Neural Machine Translation
• Laurence Bont. 2022. Multilingual synthetic QA corpora generation using round-trip consistency with adapters to partially enable zero-shot cross-lingual transfer
• Nikita Bortych. 2021. Loss calibrating variational neural machine translation
• Claartje Barkhof. 2021. Taking a step back: assessing the TransformerVAE as a latent variable model first
• Mathijs Pieters. 2020. Transparency for Text Classification Models
• Lina Murady. 2020. Probabilistic Models for Joint Classification and Rationale Extraction
• Eelco van der Wel. 2020. Improving Controllable Generation with Semi-supervised Deep Generative Models
• Nuno Mota. 2019. Textual (Generalised) Any-Shot Learning - The Case of Relation Classification
• Ruben Gerritse. 2019. Co-Training Generative Neural Machine Translation Models
• Akash Raj Komarlu Narendra Gupta. 2019. Semi-supervised Morphological Reinflection using Rectified Random Variables
• Dhruba Pujary. 2019. Supervised Neural Disease Normalization
• Daan van Stigt. 2019. Neural Language Models with Latent Syntax
• Tom Pelsmaeker. 2019. Effective Estimation of Deep Generative Models of Language
• Bryan Eikema. 2018. Auto-Encoding Variational Neural Machine Translation
• Sander Bijl de Vroe. 2017. Character-level Neural Architectures for Jointly Predicting Word Alignments and Word-internal Structure in Morphologically Complex Languages