Papers with HME

1 papers
Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition (D19-1)

Copied to clipboard

Challenge: Existing work on name-switching focuses on word-level aspects but neglects subword-level characteristics shared across languages.
Approach: They propose hierarchical meta-Embeddings that combine word-level and subword-level embeddings to create language-agnostic lexical representations.
Outcome: The proposed model achieves state-of-the-art in English-Spanish code-switching scenarios.

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