ProtoNER: Few Shot Incremental Learning for Named Entity Recognition Using Prototypical Networks

Ritesh Kumar, Saurabh Goyal, Ashish Verma, Vatche Isahagian

Abstract: Key value pair (KVP) extraction or Named Entity Recognition (NER) from visually rich documents has been an active area of research in document understanding and data extraction domain. Several transformer based models such as LayoutLMv2 [1], LayoutLMv3 [2], and LiLT [3] have emerged achieving state of the art results. However, addition of even a single new class to the existing model requires (a) re-annotation of entire training dataset to include this new class and (b) retraining the model again. Both of these issues really slow down the deployment of updated model.