Few-Shot Relation Classification

3 papers with code • 0 benchmarks • 2 datasets

Few-Shot Relation Classification is a particular relation classification task under minimum annotated data, where a model is required to classify a new incoming query instance given only few support instances (e.g., 1 or 5) during testing.

Source: MICK: A Meta-Learning Framework for Few-shot Relation Classification with Little Training Data

Greatest papers with code

FewRel 2.0: Towards More Challenging Few-Shot Relation Classification

thunlp/fewrel IJCNLP 2019

We present FewRel 2. 0, a more challenging task to investigate two aspects of few-shot relation classification models: (1) Can they adapt to a new domain with only a handful of instances?

Domain Adaptation Few-Shot Relation Classification +1