Domain-incremental video learning that permits forgetting through per-domain LoRA adapters and recovers the matching adapter at inference via test-time training on a self-supervised MAE reconstruction head.
Rethinking patch dependence for masked autoencoders
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
AaSP learns aliasing-stable audio representations by augmenting patch tokens with adaptive subband features from alias-prone bands and using teacher-student masked modeling plus multi-mask contrastive regularization, reaching SOTA on AS-20K, ESC-50, and NSynth under fine-tuning.
citing papers explorer
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Remembering by Reconstructing: Domain Incremental Learning With Test-Time Training on Video Streams
Domain-incremental video learning that permits forgetting through per-domain LoRA adapters and recovers the matching adapter at inference via test-time training on a self-supervised MAE reconstruction head.
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AaSP: Aliasing-aware Self-Supervised Pre-Training for Audio Spectrogram Transformers
AaSP learns aliasing-stable audio representations by augmenting patch tokens with adaptive subband features from alias-prone bands and using teacher-student masked modeling plus multi-mask contrastive regularization, reaching SOTA on AS-20K, ESC-50, and NSynth under fine-tuning.