Multimodal Sexism Identification and Characterization using Large Language Models and Gradient Boosting 事件

Multimodal Sexism Identification and Characterization using Large Language Models and Gradient Boosting arXiv:2606.05997v1 Announce Type: new Abstract: We present the AILS-NTUA submission to the EXIST 2026 Lab at CLEF, addressing multimodal sexism identification and characterization in memes (Task 2) and short-form videos (Task 3). Our system follows a feature-engineered late-fusion pipeline built around gradient-boosted regression models and hierarchical post-processing. For memes, we combine