Prof. dr. C.J. (Kees) van Deemter

Prof. dr. C.J. (Kees) van Deemter

Hoogleraar
Natural Language Processing
c.j.vandeemter@uu.nl

The list below is incomplete. For an up-to-date list of my publications, see my Google Scholar page (that's the Utrecht page, not the out-of-date Aberdeen one).

Publicaties

2023

Wetenschappelijke publicaties

Cafagna, M., van Deemter, K., & Gatt, A. (2023). HL Dataset: Grounding High-Level Linguistic Concepts in Vision. In Proceedings of the 16th International Natural Language Generation Conference (INLG'23) Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2302.12189
Calò, E., Levy, J., Gatt, A., & Van Deemter, K. (2023). Is Shortest Always Best? The Role of Brevity in Logic-to-Text Generation. In A. Palmer, & J. Camacho-collados (Eds.), Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023) (pp. 180-192). Association for Computational Linguistics. https://aclanthology.org/2023.starsem-1.17
Belz, A., Thomson, C., Reiter, E., Abercrombie, G., Alonso-Moral, J. M., Arvan, M., Cheung, J., Cieliebak, M., Clark, E., Deemter, K. V., Dinkar, T., Dušek, O., Eger, S., Fang, Q., Gatt, A., Gkatzia, D., González-Corbelle, J., Hovy, D., Hürlimann, M., ... Yang, D. (2023). Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP. In The Fourth Workshop on Insights from Negative Results in NLP (pp. 1-10). Association for Computational Linguistics. https://aclanthology.org/2023.insights-1.1

2022

Wetenschappelijke publicaties

Cafagna, M., van Deemter, K., & Gatt, A. (2022). Understanding Cross-modal Interactions in V&L Models that Generate Scene Descriptions. In Proceedings of the First Unimodal and Multimodal Induction of Linguistic Structures Workshop @ EMNLP (UM-IoS'22)
Caló, E., van der Werf, E., Gatt, A., & van Deemter, K. (2022). Enhancing and Evaluating the Grammatical Framework Approach to Logic-to-Text Generation. In Proceedings of the 2nd Generation, Evaluation and Metrics Workshop (GEM'22)

2021

Wetenschappelijke publicaties

Cafagna, M., van Deemter, K., & Gatt, A. (2021). What Vision-Language Models `See' when they See Scenes. (pp. 1-12). arXiv. https://doi.org/10.48550/arXiv.2109.07301
Chen, G., Same, F., & van Deemter, K. (2021). What can Neural Referential Form Selectors Learn? In Proceedings of the 14th International Conference on Natural Language Generation (pp. 154-166). Association for Computational Linguistics. https://aclanthology.org/2021.inlg-1.15
Järnfors, J., Chen, G., van Deemter, K., & Sybesma, R. (2021). Using BERT for choosing classifiers in Mandarin. In Proceedings of the 14th International Conference on Natural Language Generation (pp. 172-176). Association for Computational Linguistics. https://aclanthology.org/2021.inlg-1.17

2020

Wetenschappelijke publicaties

van Miltenburg, E., Lu, W-T., Krahmer, E., Gatt, A., Chen, G., & van Deemter, K. (2020). Gradations of error severity in automatic image description. In Proceedings of the 13th International Conference on Natural Language Genration (INLG'20)
Maas, L., Geurtsen, M., Nouwt, F., Schouten, S., Water, R. V. D., Dulmen, S. V., Dalpiaz, F., Deemter, K. V., & Brinkkemper, S. (2020). The Care2Report System: Automated Medical Reporting as an Integrated Solution to Reduce Administrative Burden in Healthcare. In Proceedings of the 53rd Hawaii International Conference on System Sciences (HICSS 2020) (pp. 1-10)
van Miltenburg, E., Lu, W-T., Krahmer, E., Gatt, A., Chen, G., Li, L., & van Deemter, K. (2020). Gradations of Error Severity in Automatic Image Descriptions. In B. Davis, Y. Graham, J. Kelleher, & Y. Sripada (Eds.), Proceedings of the 13th International Conference on Natural Language Generation (pp. 398-411). Association for Computational Linguistics (ACL). https://www.aclweb.org/anthology/2020.inlg-1.45
Chen, G., & van Deemter, K. (2020). Lessons from Computational Modelling of Reference Production in Mandarin and English. In B. Davis, Y. Graham, J. Kelleher, & Y. Sripada (Eds.), Proceedings of the 13th International Conference on Natural Language Generation (pp. 263-272). Association for Computational Linguistics (ACL). https://www.aclweb.org/anthology/2020.inlg-1.33
Mickus, T., Paperno, D., Constant, M., & van Deemter, C. J. (2020). What do you mean, BERT? Assessing BERT as a Distributional Semantic Model. 350-361. Paper presented at Proceedings of the Society for Computation in Linguistics (SCiL) 2020. https://doi.org/10.7275/t778-ja71

2019

Wetenschappelijke publicaties

van Deemter, C. J., Lin, C., & Takamura, H. (Eds.) (2019). Proceedings of the 12th International Conference on Natural Language Generation. Association for Computational Linguistics (ACL).
Li, L., van Deemter, K., Paperno, D., & Fan, J. (2019). Choosing between long and short word forms in Mandarin. In Proceedings of the 12th International Conference on Natural Language Generation (pp. 34-39). Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-8605
Green, M., & van Deemter, K. (2019). The elusive benefits of vagueness: the evidence so far. In R. Dietz (Ed.), Vagueness and rationality in language use and cognition (pp. 63-86). (Language, cognition, and mind; Vol. 5). Springer. https://doi.org/10.1007/978-3-030-15931-3_5
van Gompel, R. P. G., van Deemter, K., Gatt, A., Snoeren, R., & Krahmer, E. (2019). Conceptualisation in reference production: Probabilistic modelling and experimental testing: Probabilistic modeling and experimental testing. Psychological Review, 126(3), 345-373. https://doi.org/10.1037/rev0000138
Ramos, A., Alonso, J. M., Reiter, E., van Deemter, K., & Gatt, A. (2019). Fuzzy-based language grounding of geographical references: From writers to readers. International Journal of Computational Intelligence Systems, 12(2), 970-983. https://doi.org/10.2991/ijcis.d.190826.002
Chen, G., van Deemter, C. J., & Lin, C. (2019). Generating quantified descriptions of abstract visual scenes. In Proceedings of the 12th International Conference on Natural Language Generation (pp. 529–539). Association for Computational Linguistics (ACL). https://www.aclweb.org/anthology/W19-8667.pdf
Chen, G., van Deemter, C. J., Silvia, P., Smalbil, L., & Lin, C. (2019). QTUNA: A Corpus for Understanding How Speakers Use Quantification. In Proceedings of the 12th International Conference on Natural Language Generation (pp. 124-129). Association for Computational Linguistics (ACL). https://www.aclweb.org/anthology/W19-8616.pdf

2018

Wetenschappelijke publicaties

Chen, G., van Deemter, C. J., & Lin, C. (2018). SimpleNLG-ZH: a Linguistic Realisation Engine for Mandarin. In Proceedings of the 11th International Conference on Natural Language Generation (pp. 57–66). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/W18-6506
Chen, G., van Deemter, C. J., & Lin, C. (2018). Modelling Pro-drop with the Rational Speech Acts Model. In Proceedings of the 11th International Conference on Natural Language Generation (pp. 57–66). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/W18-6519
Chen, G., van Deemter, C. J., & Lin, C. (2018). Modelling Various Kinds of Specifications. Abstract from Computational Models of Language Generation and Processing in Pragmatics, Bochum, Germany.
https://dspace.library.uu.nl/bitstream/handle/1874/369711/Modelling_Various_Kinds_of_Specifications.pdf?sequence=1

2017

Wetenschappelijke publicaties

Gatt, A., Krahmer, E., van Deemter, K., & van Gompel, R. P. G. (2017). Reference Production as Search: The Impact of Domain Size on the Production of Distinguishing Descriptions. Cognitive Science. https://doi.org/10.1111/cogs.12375

2013

Wetenschappelijke publicaties

Masthoff, J., Van Deemter, K., & Langrial, S. (2013). Personalizing triggers for charity actions. In Persuasive Technology (Vol. 7822 LNCS, pp. 125-136). (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-642-37157-8_16

2007

Wetenschappelijke publicaties

Paraboni, I., Van Deemter, K., & Masthoff, J. (2007). Generating Referring Expressions. Computational Linguistics, 33(2), 229-254. https://doi.org/10.1162/coli.2007.33.2.229