Few Shot Relation Classification
Related Papers
Learning to Decouple Relations: Few-Shot Relation Classification with Entity-Guided Attention and Confusion-Aware Training
AbstractThis paper aims to enhance the few-shot relation classification especially for sentences that jointly describe multiple relations. Due to the fact that some relations usually keep high co-occurrence in the …...
Meta-Information Guided Meta-Learning for Few-Shot Relation Classification
AbstractFew-shot classification requires classifiers to adapt to new classes with only a few training instances. State-of-the-art meta-learning approaches such as MAML learn how to initialize and fast adapt parameters from …...
From Learning-to-Match to Learning-to-Discriminate:Global Prototype Learning for Few-shot Relation Classification
AbstractFew-shot relation classification has attracted great attention recently and is regarded as an ef-fective way to tackle the long-tail problem in relation classification. Most previous works onfew-shot relation classification are …...
Dependency-aware Prototype Learning for Few-shot Relation Classification
AbstractFew-shot relation classification aims to classify the relation type between two given entities in a sentence by training with a few labeled instances for each relation. However, most of existing …...