Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Structure-Aware Language Model Pretraining Improves Dense Retrieval on Structured Data
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.19912.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T13:04:20.157883Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T05:13:56.856662Z
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 44152f23-ba88-43ec-b6b0-12c588fc7a80 · inbound
Retrieval-Augmented Generation for Large Language Models: A Survey cites this paper.
Retrieval-Augmented Generation for Large Language Models: A Survey Structure-Aware Language Model Pretraining Improves Dense Retrieval on Structured Data
Reference 76
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T05:13:56.859760Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 54958c8b-0cba-4544-b9dc-01ed3ac504cf · inbound
EvoWiki: Evaluating LLMs on Evolving Knowledge cites this paper.
EvoWiki: Evaluating LLMs on Evolving Knowledge Structure-Aware Language Model Pretraining Improves Dense Retrieval on Structured Data
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T13:04:20.157883Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation deff9d20-eea3-4450-8737-6d4d36fa4700 · inbound
Multi-task retriever fine-tuning for domain-specific and efficient RAG cites this paper.
Multi-task retriever fine-tuning for domain-specific and efficient RAG Structure-Aware Language Model Pretraining Improves Dense Retrieval on Structured Data
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:30:51.740527Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.