Papers with language-shaped learning

2 papers
Data-Efficient Language Shaped Few-shot Image Classification (2021.findings-emnlp)

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Challenge: Existing studies have shown that language is helpful guider for image understanding by neural networks.
Approach: They propose a language-shaped learning method that makes the best use of the few-shot images and the language available only in training.
Outcome: The proposed method outperforms state-of-the-art methods on a few-shot dataset with limited training data.
Shaping Visual Representations with Language for Few-Shot Classification (2020.acl-main)

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Challenge: Existing models use natural language descriptions to classify images, but no model uses it for new tasks.
Approach: They propose a model that regularizes visual representations to predict language in a few-shot setting . they propose to use language to improve few- shot visual classification .
Outcome: The proposed model outperforms baseline models in two challenging few-shot domains.

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