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

Creating written products is essential to modern life, including writingsabout one's identity and personal experiences. However, writing is often adifficult activity that requires extensive effort to frame the central ideas,the pursued approach to communicate the central ideas, e.g., using analogies,metaphors, or other possible means, the needed presentation structure, and theactual verbal expression. Large Language Models, a recently emerged approach inMachine Learning, can offer a significant help in reducing the effort andimproving the quality of written products. This paper proposes a newcomputational approach to explore prompts that given as inputs to a LargeLanguage Models can generate cues to improve the considered written products.Two case studies on improving write-ups, one based on an analogy and one on ametaphor, are also presented in the paper.

A Large Language Model-based Computational Approach to Improve Identity-Related Write-Ups