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/

Global: Zendy Plus annual

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

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Recently, Reinforcement Learning (RL) approaches have demonstrated advancedperformance in image captioning by directly optimizing the metric used fortesting. However, this shaped reward introduces learning biases, which reducesthe readability of generated text. In addition, the large sample space makestraining unstable and slow. To alleviate these issues, we propose a simplecoherent solution that constrains the action space using an n-gram languageprior. Quantitative and qualitative evaluations on benchmarks show that RL withthe simple add-on module performs favorably against its counterpart in terms ofboth readability and speed of convergence. Human evaluation results show thatour model is more human readable and graceful. The implementation will becomepublicly available upon the acceptance of the paper.

Improving Reinforcement Learning Based Image Captioning with Natural Language Prior