2 papers
cs.CL2017
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling
Dung Thai, Shikhar Murty, Trapit Bansal +3
In textual information extraction and other sequence labeling tasks it is now common to use recurrent neural networks (such as LSTM) to form rich embedded representations of long-t…
cs.CL2017
RelNet: End-to-End Modeling of Entities & Relations
Trapit Bansal, Arvind Neelakantan, Andrew McCallum
We introduce RelNet: a new model for relational reasoning. RelNet is a memory augmented neural network which models entities as abstract memory slots and is equipped with an additi…