3 papers
cs.CV2026
Suppression or Deletion: A Restoration-Based Representation-Level Analysis of Machine Unlearning
Yurim Jang, Jaeung Lee, Dohyun Kim +2
As pretrained models are increasingly shared on the web, ensuring that models can forget or delete sensitive, copyrighted, or private information upon request has become crucial. M…
cs.CV2025
Scheduling Weight Transitions for Quantization-Aware Training
Junghyup Lee, Jeimin Jeon, Dohyung Kim +1
Quantization-aware training (QAT) simulates a quantization process during training to lower bit-precision of weights/activations. It learns quantized weights indirectly by updating…
cs.CV2025
Subnet-Aware Dynamic Supernet Training for Neural Architecture Search
Jeimin Jeon, Youngmin Oh, Junghyup Lee +4
N-shot neural architecture search (NAS) exploits a supernet containing all candidate subnets for a given search space. The subnets are typically trained with a static training stra…