Papers with robust Hangeul word embedding model

1 papers
Handling Out-Of-Vocabulary Problem in Hangeul Word Embeddings (2021.eacl-main)

Copied to clipboard

Challenge: Word embedding is considered an essential factor in improving the performance of various Natural Language Processing (NLP) models.
Approach: They propose a Hangeul word embedding model that infers original word embeds from typos while maintaining high performance.
Outcome: The proposed model performs well against typos while maintaining high performance.

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