A few-shot text classifier that learns attention from distributional word statistics (frequency and class skew) generalizes to unseen classes better than lexical-feature meta-learners.
Attentive task-agnostic meta-learning for few-shot text classification,
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Few-shot Text Classification with Distributional Signatures
A few-shot text classifier that learns attention from distributional word statistics (frequency and class skew) generalizes to unseen classes better than lexical-feature meta-learners.