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SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis
October 03, 2022 ยท Declared Dead ยท ๐ International Workshop on Semantic Evaluation
"No code URL or promise found in abstract"
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Authors
Jiaxin Pei, Vรญtor Silva, Maarten Bos, Yozon Liu, Leonardo Neves, David Jurgens, Francesco Barbieri
arXiv ID
2210.01108
Category
cs.CL: Computation & Language
Cross-listed
cs.CY,
cs.LG
Citations
29
Venue
International Workshop on Semantic Evaluation
Last Checked
4 months ago
Abstract
We propose MINT, a new Multilingual INTimacy analysis dataset covering 13,372 tweets in 10 languages including English, French, Spanish, Italian, Portuguese, Korean, Dutch, Chinese, Hindi, and Arabic. We benchmarked a list of popular multilingual pre-trained language models. The dataset is released along with the SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis (https://sites.google.com/umich.edu/semeval-2023-tweet-intimacy).
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