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

Generating texts in scientific papers requires not only capturing the contentcontained within the given input but also frequently acquiring the externalinformation called \textit{context}. We push forward the scientific textgeneration by proposing a new task, namely \textbf{context-aware textgeneration} in the scientific domain, aiming at exploiting the contributions ofcontext in generated texts. To this end, we present a novel challenginglarge-scale \textbf{Sci}entific Paper Dataset for Conte\textbf{X}t-Aware Text\textbf{Gen}eration (SciXGen), consisting of well-annotated 205,304 papers withfull references to widely-used objects (e.g., tables, figures, algorithms) in apaper. We comprehensively benchmark, using state-of-the-arts, the efficacy ofour newly constructed SciXGen dataset in generating description and paragraph.Our dataset and benchmarks will be made publicly available to hopefullyfacilitate the scientific text generation research.

SciXGen: A Scientific Paper Dataset for Context-Aware Text Generation