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Found 4 papers, 1 papers with code
Enhancing Metaphor Detection through Soft Labels and Target Word Prediction
These soft labels provide a similar effect to label smoothing and help prevent the model from becoming over confident and effectively addresses the challenge of data sparsity.
Towards Compact 3D Representations via Point Feature Enhancement Masked Autoencoders
Specifically, to learn more compact features, a share-parameter Transformer encoder is introduced to extract point features from the global and local unmasked patches obtained by global random and local block mask strategies, followed by a specific decoder to reconstruct.
Ranked #3 on
Few-Shot 3D Point Cloud Classification
on ModelNet40 10-way (20-shot)
(using extra training data)
Retrieval-Augmented Meta Learning for Low-Resource Text Classification
However, due to the limited training data in the meta-learning scenario and the inherent properties of parameterized neural networks, poor generalization performance has become a pressing problem that needs to be addressed.
Prompt Learning With Knowledge Memorizing Prototypes For Generalized Few-Shot Intent Detection
Previous GFSID methods rely on the episodic learning paradigm, which makes it hard to extend to a generalized setup as they do not explicitly learn the classification of seen categories and the knowledge of seen intents.
