We invite you to participate in the shared task on Explainability of Cross-lingual Emotion Detection (EXALT), organized as part of WASSA 2024 at ACL 2024. The goal of this task
is two-fold: developing highly performant models for cross-lingual emotion detection while also encouraging model explainability and interpretability.
**Task Description**
You can participate in three different tracks:
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Track 1: Cross-Lingual Emotion Detection, which involves emotion classification with 5 labels with transfer from English to a multi-lingual test set that also includes French, Spanish, Dutch
and Russian tweets.
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Track 2: Trigger Word detection (binary), a task where participants have to identify which words in a text are most essential for expressing emotion. For this track, we treat trigger word detection
as a binary classification task.
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Track 3: Trigger Word detection (numerical), a task where participants have to identify which words in a text are most essential for expressing emotion. For this track, participants can provide
numerical importance scores for each individual word.
For more information, please refer to the web page:
https://lt3.ugent.be/exalt/
The data is available through:
https://codalab.lisn.upsaclay.fr/competitions/17730
**Important Dates**
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15 February, 2024: first call for participation. Training and validation data released, CodaLab opens for team
registrations.
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13 May, 2024: Evaluation period/phase begins (= test data released)
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15 May, 2024: Evaluation period/phase ends (= system submission deadline)
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17 May, 2024: Announcement of final results
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22 May, 2024: Submission of system description papers for review (we encourage participants to share models,
code, fact sheets, extra data, etc. with the community through github or other repositories on paper publication.)
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22 June, 2024: Notification of Acceptance
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01 July, 2024: Camera-ready deadline
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15-16 August, 2024: Presentations of the systems at the WASSA 2024 workshop (Bangkok, Thailand)
**Task Organizers**
Aaron Maladry
LT3, Ghent University
Pranaydeep Singh
LT3, Ghent University
Els Lefever
LT3, Ghent University
**Contact**
You can contact all organizers of the shared task at
exalt-wassa2024@googlegroups.com