Papers with labeled text data

1 papers
A Simple and Efficient Multi-Task Learning Approach for Conditioned Dialogue Generation (2021.naacl-main)

Copied to clipboard

Challenge: Existing studies have focused on conditioned dialogue generation, but there is a scarcity of labeled responses.
Approach: They propose a multi-task learning approach to leverage labeled dialogue and text data to generate conditioned dialogues.
Outcome: The proposed approach outperforms the state-of-the-art models by leveraging the labeled texts and obtains larger improvement compared to the previous methods to leverage text 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