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Sunghyun Baek

2 accepted papers

2026

IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation

ICLR 2026poster

Test-time adaptation (TTA) has been widely explored to prevent performance degradation when test data differ from the training distribution. However, fully leveraging the rich representations of large pretrained models with minimal parameter updates remains underexplored. In this paper, we propose a…

Cited by 0SourcecodeScholar
2021

Linearly Replaceable Filters for Deep Network Channel Pruning

AAAI 2021technical

Convolutional neural networks (CNNs) have achieved remarkable results; however, despite the development of deep learning, practical user applications are fairly limited because heavy networks can be used solely with the latest hardware and software supports. Therefore, network pruning is gaining att…

Cited by 41SourcePDFScholar