It is a binary classification task that consists of deciding whether a given video contains sexist expressions or behaviors (i.e., it is sexist itself, describes a sexist situation, or criticizes sexist behavior). In this task, a soft-soft evaluation is considered, where the probability of each label predicted by the system is compared with the probability defined based on annotation disagreement in the gold standard.
Publication
Plaza, L. et al. (2025). Overview of EXIST 2025: Learning with Disagreement for Sexism Identification and Characterization in Tweets, Memes, and TikTok Videos. In: Carrillo-de-Albornoz, J., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2025. Lecture Notes in Computer Science, vol 16089. Springer, Cham.
Language
Spanish
English
URL Task
NLP topic
Dataset
Year
2025
Publication link
Ranking metric
ICMSoft
Task results
| System | ICM Soft Sort ascending |
|---|---|
| LaVellaPremium_2 | 0.3362 |
| LaVellaPremium | 0.3362 |
| MIARFID ducks_2 | 0.2968 |
| MIARFID ducks_1 | 0.2956 |
| YesWeEXIST_1 | 0.2759 |
