Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2308.03314.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T15:48:59.363284Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T04:35:15.173925Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation f6ecc4fd-0ac2-4af9-8369-65baeffa363b · inbound
AiRacleX: Automated Detection of Price Oracle Manipulations via LLM-Driven Knowledge Mining and Prompt Generation cites this paper.
AiRacleX: Automated Detection of Price Oracle Manipulations via LLM-Driven Knowledge Mining and Prompt Generation GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T15:48:59.363284Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f22894d-7d3f-4089-bb5e-f876a42f5322 · inbound
Leveraging Large Language Models for Command Injection Vulnerability Analysis in Python: An Empirical Study on Popular Open-Source Projects cites this paper.
Leveraging Large Language Models for Command Injection Vulnerability Analysis in Python: An Empirical Study on Popular Open-Source Projects GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:29:10.412625Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e70451f-9bea-4979-8f8a-1f4836ff50d3 · inbound
Minimizing False Positives in Static Bug Detection via LLM-Enhanced Path Feasibility Analysis cites this paper.
Minimizing False Positives in Static Bug Detection via LLM-Enhanced Path Feasibility Analysis GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T04:35:15.245873Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.