Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
OMPGPT: A Generative Pre-trained Transformer Model for OpenMP
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.16445.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T11:37:49.524732Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T13:12:44.618691Z
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 068d18bf-3b16-4d51-b4b4-e6ed73a9e3cb · inbound
HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages cites this paper.
HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages OMPGPT: A Generative Pre-trained Transformer Model for OpenMP
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T11:37:49.524732Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18f82041-0a4e-4a14-b812-a6b2f057587f · inbound
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono cites this paper.
ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono OMPGPT: A Generative Pre-trained Transformer Model for OpenMP
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:51:12.374744Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f5cfbd26-3c48-452f-a49e-d01fda50cf17 · inbound
Accelerating Latency-Critical Applications with AI-Powered Semi-Automatic Fine-Grained Parallelization on SMT Processors cites this paper.
Accelerating Latency-Critical Applications with AI-Powered Semi-Automatic Fine-Grained Parallelization on SMT Processors OMPGPT: A Generative Pre-trained Transformer Model for OpenMP
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T13:12:44.622289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.