English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Conversational machine comprehension requires deep understanding of thedialogue flow, and the prior work proposed FlowQA to implicitly model thecontext representations in reasoning for better understanding. This paperproposes to explicitly model the information gain through dialogue reasoning inorder to allow the model to focus on more informative cues. The proposed modelachieves state-of-the-art performance in a conversational QA dataset QuAC andsequential instruction understanding dataset SCONE, which shows theeffectiveness of the proposed mechanism and demonstrates its capability ofgeneralization to different QA models and tasks.

FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension