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Results: 34
Number of items: 34
  • Open Access
    Eikema, B. (2026). A sampling-based exploration of neural text generation models. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Ferreira, P., Titov, I., & Aziz, W. (2025). Explanation Regularisation through the Lens of Attributions. In O. Rambow, L. Wanner, M. Apidianaki, H. Al-Khalifa, B. Di Eugenio, & S. Schockaert (Eds.), The 31st International Conference on Computational Linguistics : proceedings of the main conference: COLING 2025 : January 19-24, 2025 (pp. 6530–6551). Association for Computational Linguistics. https://aclanthology.org/2025.coling-main.436/
  • Open Access
    Ilia, E., & Aziz, W. (2024). Predict the Next Word: <Humans exhibit uncertainty in this task and language models _____> In Y. Graham, & M. Purver (Eds.), The 18th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : EACL 2024 : March 17-22, 2024 (Vol. 2, pp. 234-255). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.eacl-short.22
  • Open Access
    Baan, J., Fernández, R., Plank, B., & Aziz, W. (2024). Interpreting Predictive Probabilities: Model Confidence or Human Label Variation? In Y. Graham, & M. Purver (Eds.), The 18th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : EACL 2024 : March 17-22, 2024 (Vol. 2, pp. 268-277). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.eacl-short.24
  • Open Access
    De Cao, N. (2024). Entity centric neural models for natural language processing. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Bhargav, S. (2024). Navigating uncertain waters in information retrieval: Adapting to domain shifts and complex information needs. [Thesis, fully internal, Universiteit van Amsterdam].
  • Giulianelli, M., Baan, J., Aziz, W., Fernández, R., & Plank, B. (2023, October 20). whatsnext-scores [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10025272
  • Open Access
    Giulianelli, M., Baan, J., Aziz, W., Fernández, R., & Plank, B. (2023). What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability. In H. Bouamar, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 : Proceedings of the Conference : December 6-10, 2023 (pp. 14349–14371). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.887
  • Open Access
    Abnar, S. (2023). Inductive biases for learning natural language. [Thesis, fully internal, Universiteitsbibliotheek].
  • Open Access
    Eikema, B., & Aziz, W. (2022). Sampling-Based Approximations to Minimum Bayes Risk Decoding for Neural Machine Translation. In Y. Goldberg, Z. Kozareva, & Y. Zhang (Eds.), Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: December 7-11, 2022, Abu Dhabi, United Arab Emirates (pp. 10978-10993). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2108.04718, https://doi.org/10.18653/v1/2022.emnlp-main.754
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