Papers with multilingual dense retrieval models

1 papers
mAggretriever: A Simple yet Effective Approach to Zero-Shot Multilingual Dense Retrieval (2023.emnlp-main)

Copied to clipboard

Challenge: MLIR requires human annotations in multiple languages, making training labor-intensive.
Approach: They propose a multilingual information retrieval model that leverages pre-trained multilingual transformers for dense retrieval.
Outcome: Empirical results show that mAggretriever outperforms state-of-the-art models fine-tuned on English training data.

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