Yingji Li

Unweighted controlled contexts yield the clearest grammatical gender direction, revealing that existing debiasing methods may overlook critical nuances in contextual embeddings.

MLLMs struggle to grasp the nuances of ancient Chinese script evolution, but a glyph-driven fine-tuning approach unlocks surprisingly strong performance even in smaller models.