2025-01-01 · conference-paper · Advanced Graph Neural Networks · en
highly citedClaims drawn from cited facts, not live model generation.
This paper is a conference-paper focused on the primary topic of Advanced Graph Neural Networks, indicating that it has undergone peer review for a conference and therefore carries more evidentiary weight than a preprint. Accordingly, this work's claims should be treated as vetted by the reviewing process, though still limited to its specific contribution.
3 cited facts
A small team of 3 researchers authored this work.
1 cited fact
This work has been cited 16292 times, and with its highly cited status it already serves as an established reference point in the field. It references 0 works.
3 cited facts
Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories is a conference-paper, focusing on Advanced Graph Neural Networks, published in 2025.
Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories has 16,292 citations in our record, placing it among the highly cited works we track.
Our record lists 3 authors for Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories. Author names aren't in our data yet — the source link on the page lists the full byline.
Source facts, citations, and refresh stamp for this record.
Sources: openalex_works