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Team DMG at CMCL 2022 Shared Task: Transformer Adapters for the Multi- and Cross-Lingual Prediction of Human Reading Behavior

Autor: Takmaz, E., Chersoni, E., Hollenstein, N., Jacobs, C., Oseki, Y., Prévot, L., Santus, E.

Publikováno v: Workshop on Cognitive Modeling and Computational Linguistics: CMCL 2022 : proceedings of the workshop : May 26, 2022, 136-144
STARTPAGE=136;ENDPAGE=144;TITLE=Workshop on Cognitive Modeling and Computational Linguistics

In this paper, we present the details of our approaches that attained the second place in the shared task of the ACL 2022 Cognitive Modeling and Computational Linguistics Workshop. The shared task is focused on multi- and cross-lingual prediction of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52b2ba41f4fad521a8aefe4f59515c7a
https://aclanthology.org/2022.cmcl-1.16.mp4

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Less Descriptive yet Discriminative: Quantifying the Properties of Multimodal Referring Utterances via CLIP

Autor: Takmaz, E., Pezzelle, S., Fernández, R., Chersoni, E., Hollenstein, N., Jacobs, C., Oseki, Y., Prévot, L., Santus, E.

Publikováno v: Workshop on Cognitive Modeling and Computational Linguistics: CMCL 2022 : proceedings of the workshop : May 26, 2022, 36-42
STARTPAGE=36;ENDPAGE=42;TITLE=Workshop on Cognitive Modeling and Computational Linguistics

In this work, we use a transformer-based pre-trained multimodal model, CLIP, to shed light on the mechanisms employed by human speakers when referring to visual entities. In particular, we use CLIP to quantify the degree of descriptiveness (how well

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::085dd3645b64e910ffec6169d15f51cd
https://dare.uva.nl/personal/pure/en/publications/less-descriptive-yet-discriminative-quantifying-the-properties-of-multimodal-referring-utterances-via-clip(60c3bc42-b3b0-4dcf-af49-5fb65967bdb9).html

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Generating Image Descriptions via Sequential Cross-Modal Alignment Guided by Human Gaze

Autor: Takmaz, E., Pezzelle, S., Beinborn, L., Fernández, R., Webber, B., Cohn, T., He, Y., Liu, Y.

Publikováno v: Takmaz, E, Pezzelle, S, Beinborn, L & Fernández, R 2020, Generating Image Descriptions via Sequential Cross-Modal Alignment Guided by Human Gaze . in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) . Association for Computational Linguistics, pp. 4664-4677 . https://doi.org/10.18653/v1/2020.emnlp-main.377
EMNLP (1)
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020
2020 Conference on Empirical Methods in Natural Language Processing
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 4664-4677
STARTPAGE=4664;ENDPAGE=4677;TITLE=Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

When speakers describe an image, they tend to look at objects before mentioning them. In this paper, we investigate such sequential cross-modal alignment by modelling the image description generation process computationally. We take as our starting p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0de5296d4ab58b0425a667f2c4e05b8f
https://doi.org/10.18653/v1/2020.emnlp-main.377

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Refer, Reuse, Reduce

Autor: Takmaz, E., Giulianelli, M., Pezzelle, S., Sinclair, A., Fernández, R., Webber, B., Cohn, T., He, Y., Liu, Y.

Publikováno v: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
EMNLP (1)
2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020, 4350-4368
STARTPAGE=4350;ENDPAGE=4368;TITLE=2020 Conference on Empirical Methods in Natural Language Processing

Dialogue participants often refer to entities or situations repeatedly within a conversation, which contributes to its cohesiveness. Subsequent references exploit the common ground accumulated by the interlocutors and hence have several interesting p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0318e951c5d453ac84860dc50be4544e
https://dare.uva.nl/personal/pure/en/publications/refer-reuse-reduce(a461423f-25d5-49cd-94e9-505c20a7d797).html

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Evaluating the Representational Hub of Language and Vision Models

Autor: Shekhar, R., Takmaz, E., Fernández, R., Bernardi, R., Dobnik, S., Chatzikyriakidis, S., Demberg, V.

Publikováno v: Proceedings of the 13th International Conference on Computational Semantics-Long Papers: IWCS 2019 : 23-27 May, 2019, University of Gothenburg, Gothenburg, Sweden, 211-222
STARTPAGE=211;ENDPAGE=222;TITLE=Proceedings of the 13th International Conference on Computational Semantics-Long Papers
IWCS (1)
Scopus-Elsevier

The multimodal models used in the emerging field at the intersection of computational linguistics and computer vision implement the bottom-up processing of the `Hub and Spoke' architecture proposed in cognitive science to represent how the brain proc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5d32e8963e21ddd4f6a79d158e40dce

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The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue

Autor: Haber, J., Baumgärtner, T., Takmaz, E., Gelderloos, L., Bruni, E., Fernández, R., Korhonen, A., Traum, D., Màrquez, L.

Publikováno v: ACL (1)
The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy, 1895-1910
STARTPAGE=1895;ENDPAGE=1910;TITLE=The 57th Annual Meeting of the Association for Computational Linguistics
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 1895-1910
STARTPAGE=1895;ENDPAGE=1910;TITLE=Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

This paper introduces the PhotoBook dataset, a large-scale collection of visually-grounded, task-oriented dialogues in English designed to investigate shared dialogue history accumulating during conversation. Taking inspiration from seminal work on d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2065e9abd576ebf578dae7cd5502e58
https://doi.org/10.18653/v1/p19-1184

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