Papers with Event and Entity Coreference Resolution

1 papers
A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution. (2021.findings-emnlp)

Copied to clipboard

Challenge: Existing methods for Coreference Resolution rely on word embeddings for word representation, but performance of different embeddables is largely overlooked.
Approach: They frame their study in the context of Event and Entity Coreference Resolution (EvCR & EnCR) they examine whether there is a trade-off between performance and embedding size .
Outcome: The embeddings achieve 86% of the performance of the largest model while being 1.2% of its size.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations