Chengyao Qian — accepted AI-conference papers

2026

pH-Strips for Selective Forgetting: A Blunt but Fast Diagnostic Baseline for Machine Unlearning

Chengyao Qian, Jing Wu, Trung Le, Dinh Phung, Mehrtash Harandi

CVPR 2026

Machine Unlearning (MU), erasing undesirable content from Artificial Intelligence (AI) models, plays an essential role in developing safe and trustworthy AI systems.Despite notable advances, the baseline MU methods rely on retraining from scratch without the data to be removed, which is computationa

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2025

A Good Teacher Adapts Their Knowledge for Distillation

Chengyao Qian, Trung Le, Mehrtash Harandi

ICCV 2025poster

Knowledge distillation (KD) is an effective method for enhancing a small model, named student, by training it under the supervision of larger teacher models. However, existing studies indicate that a substantial capacity gap between the student and teacher can lead to poor learning for the student m…

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