C2R-KD: Complex to Real Knowledge Distillation (Student Abstract)
DOI:
https://doi.org/10.1609/aaai.v40i48.42301Abstract
In this work, C2R-KD is proposed, applying a Complex-to-Real projection to map complex domain features into the real domain. C2R-KD mitigates complex-real domain mismatch to strengthen the representational capacity of the student model and further improves the knowledge distillation model performance through the hybrid distillation of features and logits simultaneously. Experimental result demonstrates higher accuracy than the conventional KD across all test environments.Downloads
Published
2026-03-14
How to Cite
Youn, B., & Jo, O. (2026). C2R-KD: Complex to Real Knowledge Distillation (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 40(48), 41446–41448. https://doi.org/10.1609/aaai.v40i48.42301
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Section
AAAI Student Abstract and Poster Program