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Found 5 papers, 3 papers with code
Elucidating the Design Space of Dataset Condensation
Dataset condensation, a concept within data-centric learning, efficiently transfers critical attributes from an original dataset to a synthetic version, maintaining both diversity and realism.
Rethinking Centered Kernel Alignment in Knowledge Distillation
This paper first provides a theoretical perspective to illustrate the effectiveness of CKA, which decouples CKA to the upper bound of Maximum Mean Discrepancy~(MMD) and a constant term.
Enhancing Adversarial Attacks: The Similar Target Method
Deep neural networks are vulnerable to adversarial examples, posing a threat to the models' applications and raising security concerns.
AFN: Adaptive Fusion Normalization via an Encoder-Decoder Framework
The success of deep learning is inseparable from normalization layers.
Syntax-aware Hybrid prompt model for Few-shot multi-modal sentiment analysis
Multimodal Sentiment Analysis (MSA) has been a popular topic in natural language processing nowadays, at both sentence and aspect level.
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