Chuan Yu

TriGuard-Lite: Parameter-Efficient Harmful Meme Recognition with Harm-aware Local Regions and Gated Multimodal Fusion

Harmful memes distribute risk signals across global scene context, localized visual cues, and embedded text, resisting unimodal detection. We propose TRIGUARD-LITE, a parameter-efficient framework that integrates three complementary views—global image semantics, five-region local crops, and embedded text features—throu...

An Enhanced Knowledge Distillation Framework via Teacher-Student Mutual Learning for Image Classification