Papers with ELMo’s contextualized word vectors

1 papers
Gender Bias in Contextualized Word Embeddings (N19-1)

Copied to clipboard

Challenge: Existing studies show that training word embeddings in large corpora could lead to encoding societal biases present in these human-produced data.
Approach: They conduct several intrinsic analyses to quantify, analyze and mitigate gender bias exhibited in ELMo’s contextualized word vectors.
Outcome: The proposed method mitigates gender bias on WinoBias probing corpus and demonstrates that it can be implemented in other systems.

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