Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
PatentGPT: A Large Language Model for Intellectual Property
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2404.18255.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:43:04.926647Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T15:24:50.159445Z
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 277e181c-0f9c-43d4-8b5b-57677c821b50 · inbound
EvoPat: A Multi-LLM-based Patents Summarization and Analysis Agent cites this paper.
EvoPat: A Multi-LLM-based Patents Summarization and Analysis Agent PatentGPT: A Large Language Model for Intellectual Property
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:05:51.204234Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7eaf5880-65ec-4936-8545-a3429618e25d · inbound
Enhancing the Patent Matching Capability of Large Language Models via the Memory Graph cites this paper.
Enhancing the Patent Matching Capability of Large Language Models via the Memory Graph PatentGPT: A Large Language Model for Intellectual Property
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:43:04.926647Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e7d4c09-3d90-4c15-b7cd-3917841609b9 · inbound
When Does Synthetic Patent Data Help? Volume-Fidelity Trade-offs in Low-Resource Multi-Label Classification cites this paper.
When Does Synthetic Patent Data Help? Volume-Fidelity Trade-offs in Low-Resource Multi-Label Classification PatentGPT: A Large Language Model for Intellectual Property
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T15:24:50.160689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.