Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
InstructPatentGPT: Training patent language models to follow instructions with human feedback
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.16897.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:55:47.454336Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T18:16:30.548575Z
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 24930c6b-27a9-4e59-b37e-142d3775b242 · inbound
Contextual Candor: Enhancing LLM Trustworthiness Through Hierarchical Unanswerability Detection cites this paper.
Contextual Candor: Enhancing LLM Trustworthiness Through Hierarchical Unanswerability Detection InstructPatentGPT: Training patent language models to follow instructions with human feedback
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:55:47.454336Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12ac24b9-22e2-45c1-8482-4888fcbc8259 · inbound
Harnessing RLHF for Robust Unanswerability Recognition and Trustworthy Response Generation in LLMs cites this paper.
Harnessing RLHF for Robust Unanswerability Recognition and Trustworthy Response Generation in LLMs InstructPatentGPT: Training patent language models to follow instructions with human feedback
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:04:16.765780Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.