Search results
Results: 40
Number of items: 40
-
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
-
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 -
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 -
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 -
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 -
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., & Marelli, M. (2020). Do semantic features capture a syntactic classification of compounds? Insights from compositional distributional semantics. In S. Schulte im Walde, & E. Smolka (Eds.), The role of constituents in multiword expressions: An interdisciplinary, cross-lingual perspective (pp. 33-60). (Phraseology and Multiword Expressions; Vol. 4). Language Science Press. https://doi.org/10.5281/zenodo.3598556 -
Takmaz, E., Giulianelli, M., Pezzelle, S., Sinclair, A., & Fernández, R. (2020). Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts. In B. Webber, T. Cohn, Y. He, & Y. Liu (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp. 4350-4368). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.353 -
Gualdoni, E., Bernardi, R., Fernández, R., & Pezzelle, S. (2020). Grounded and Ungrounded Referring Expressions in Human Dialogues: Language Mirrors Different Grounding Conditions. In J. Monti, F. Dell'Orletta, & F. Tamburini (Eds.), Proceedings of the Seventh Italian Conference on Computational Linguistics: Bologna, Italy, March 1-3, 2021 Article 38 (CEUR Workshop Proceedings; Vol. 2769). CEUR-WS. http://ceur-ws.org/Vol-2769/paper_38.pdf
Page 3 of 4