C2R-KD: Complex to Real Knowledge Distillation (Student Abstract)

Authors

  • Byunghyuk Youn Chungbuk National University
  • Ohyun Jo Chungbuk National University

DOI:

https://doi.org/10.1609/aaai.v40i48.42301

Abstract

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.

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