Search results
Results: 43
Number of items: 43
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Buijtelaar, L., & Pezzelle, S. (2023). A Psycholinguistic Analysis of BERT's Representations of Compounds. In A. Vlachos, & I. Augenstein (Eds.), The 17th Conference of the European Chapter of the Association for Computational Linguistics: EACL 2023 : proceedings of the conference : May 2-6, 2023 (pp. 2230–2241). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2302.07232, https://doi.org/10.18653/v1/2023.eacl-main.163 -
Surikuchi, A., Pezzelle, S., & Fernández, R. (2023). GROOViST: A Metric for Grounding Objects in Visual Storytelling. In H. Bouamor, 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. 3331-3339). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.202 -
Jansen, L., Laichter, Š. L., Sinclair, A., van der Goot, M. J., Fernández, R., & Pezzelle, S. (2022). Controllable Text Generation for All Ages: Evaluating a Plug-and-Play Approach to Age-Adapted Dialogue. In A. Bosselut, K. Chandu, K. Dhole, V. Gangal, S. Gehrmann, Y. Jernite, J. Novikova, & L. Perez-Beltrachini (Eds.), 2nd Workshop on Natural Language Generation, Evaluation and Metrics: GEM 2022 : proceedings of the workshop : December 7, 2022 (pp. 172-188). Association for Computational Linguistics. https://doi.org/https://aclanthology.org/2022.gem-1.14 -
Takmaz, E., Pezzelle, S., & Fernández, R. (2022). Less Descriptive yet Discriminative: Quantifying the Properties of Multimodal Referring Utterances via CLIP. In E. Chersoni, N. Hollenstein, C. Jacobs, Y. Oseki, L. Prévot, & E. Santus (Eds.), Workshop on Cognitive Modeling and Computational Linguistics: CMCL 2022 : proceedings of the workshop : May 26, 2022 (pp. 36-42). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.cmcl-1.4 -
Pezzelle, S., Greco, C., Gandolfi, G., Gualdoni, E., & Bernardi, R. B. (2021, May 12). Be Different to Be Better (BD2BB) [Data set]. GitHub. https://sites.google.com/view/bd2bb/home
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Jolly, S., Pezzelle, S., & Nabi, M. (2021). EaSe: A Diagnostic Tool for VQA Based on Answer Diversity. In K. Toutanova, A. Rumshisky, L. Zettlemoyer, D. Hakkani-Tur, I. Beltagy, S. Bethard, R. Cotterell, T. Chakraborty, & Y. Zhou (Eds.), The 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL-HLT 2021 : proceedings of the conference : June 6-11, 2021 (pp. 2407-2414). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.naacl-main.192 -
Bernardi, R., & Pezzelle, S. (2021). Linguistic issues behind visual question answering. Language and Linguistics Compass, 15(6), Article e12417. https://doi.org/10.1111/lnc3.12417 -
Parfenova, I., Elliott, D., Fernández, R., & Pezzelle, S. (2021). Probing Cross-Modal Representations in Multi-Step Relational Reasoning. In A. Rogers, I. Calixto, I. Vulić, N. Saphra, N. Kassner, O.-M. Camburu, T. Bansal, & V. Shwartz (Eds.), The 6th Workshop on Representation Learning for NLP: RepL4NLP 2021 : proceedings of the workshop : August 6, 2021, Bangkok, Thailand (online) (pp. 152–162). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.repl4nlp-1.16 -
Pezzelle, S., Takmaz, E., & Fernández, R. (2021). Word Representation Learning in Multimodal Pre-Trained Transformers: An Intrinsic Evaluation. Transactions of the Association of Computational Linguistics, 9, 1563–1579. https://doi.org/10.1162/tacl_a_00443 -
Jansen, L., Sinclair, A., van der Goot, M. J., Fernández, R., & Pezzelle, S. (2021). Detecting age-related linguistic patterns in dialogue: Toward adaptive conversational systems. In E. Fersini, M. Passarotti, & V. Patti (Eds.), Proceedings of the Eighth Italian Conference on Computational Linguistics: Milan, Italy, June 29-July 1, 2022 Article 47 (CEUR Workshop Proceedings; Vol. 3033). CEUR-WS. https://ceur-ws.org/Vol-3033/paper47.pdf
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