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In this work we present an approach for generating alternative text (or alt-text) descriptions for images shared on social media, specifically Twitter. More than just a special case of image captioning, alt-text is both more literally descriptive and
Externí odkaz:
http://arxiv.org/abs/2305.14779
Autor:
El-Kishky, Ahmed, Markovich, Thomas, Park, Serim, Verma, Chetan, Kim, Baekjin, Eskander, Ramy, Malkov, Yury, Portman, Frank, Samaniego, Sofía, Xiao, Ying, Haghighi, Aria
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022)
Social networks, such as Twitter, form a heterogeneous information network (HIN) where nodes represent domain entities (e.g., user, content, advertiser, etc.) and edges represent one of many entity interactions (e.g, a user re-sharing content or "fol
Externí odkaz:
http://arxiv.org/abs/2202.05387
In this work we present an approach for generating alternative text (or alt-text) descriptions for images shared on social media, specifically Twitter. This task is more than just a special case of image captioning, as alt-text is both more literally
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dabe0956d4a99efd2a1d30378d9f811d
Autor:
Kasner, Mandy, Schrön, Martin, Weimar, Jannis, Köhli, Markus, Samaniego, Sofia, Schmidt, Ulrich, Zacharias, Steffen
Publikováno v:
Geophysical Research Abstracts; 2019, Vol. 21, p1-1, 1p