Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.13902.
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 2026-08-06T15:08:46.522196Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T22:15:10.094969Z
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 5198c2ca-78ff-4dc5-b4d0-bc0d7c1e3291 · inbound
Never Come Up Empty: Adaptive HyDE Retrieval for Improving LLM Developer Support cites this paper.
Never Come Up Empty: Adaptive HyDE Retrieval for Improving LLM Developer Support Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:08:46.522196Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46cdd1c6-3098-4c1c-94a3-8237d206aa50 · inbound
HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways cites this paper.
HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T22:15:10.100836Z
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.