Qi-Ming Fu

CL-GGD: Cross-layer Semantic Geometry Distillation for Lightweight Text Embedding Reconstruction

Lightweight sentence embedding models are critical for large-scale retrieval and semantic matching, yet aggressive compression often disrupts the semantic geometry learned by powerful teachers. Existing distillation methods primarily rely on point-wise feature matching or task-specific supervision, which fails to prese...