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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper presents the first comprehensive analysis of ChatGPT's Text-to-SQLability. Given the recent emergence of large-scale conversational languagemodel ChatGPT and its impressive capabilities in both conversational abilitiesand code generation, we sought to evaluate its Text-to-SQL performance. Weconducted experiments on 12 benchmark datasets with different languages,settings, or scenarios, and the results demonstrate that ChatGPT has strongtext-to-SQL abilities. Although there is still a gap from the currentstate-of-the-art (SOTA) model performance, considering that the experiment wasconducted in a zero-shot scenario, ChatGPT's performance is still impressive.Notably, in the ADVETA (RPL) scenario, the zero-shot ChatGPT even outperformsthe SOTA model that requires fine-tuning on the Spider dataset by 4.1\%,demonstrating its potential for use in practical applications. To supportfurther research in related fields, we have made the data generated by ChatGPTpublicly available at https://github.com/THU-BPM/chatgpt-sql.

A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability