Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
JDocQA: Japanese Document Question Answering Dataset for Generative Language Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.19454.
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 2026-08-05T19:02:49.968303Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T20:28:13.953130Z
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 19557e47-b97d-482d-a573-b0ccde1569cf · inbound
AdaDocVQA: Adaptive Framework for Long Document Visual Question Answering in Low-Resource Settings cites this paper.
AdaDocVQA: Adaptive Framework for Long Document Visual Question Answering in Low-Resource Settings JDocQA: Japanese Document Question Answering Dataset for Generative Language Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T19:02:49.968303Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4884590f-a1f7-416d-8839-3366d241e831 · inbound
Overcoming the "Impracticality" of RAG: Proposing a Real-World Benchmark and Multi-Dimensional Diagnostic Framework cites this paper.
Overcoming the "Impracticality" of RAG: Proposing a Real-World Benchmark and Multi-Dimensional Diagnostic Framework JDocQA: Japanese Document Question Answering Dataset for Generative Language Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T20:28:13.954640Z
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.