Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Optimizing Retrieval Strategies for Financial Question Answering Documents in Retrieval-Augmented Generation Systems
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.15191.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-30T12:27:46.629948Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T12:34:38.866696Z
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 07b8ea10-d098-4e62-b0e6-c2fd5fe2d3df · inbound
A Picture is Worth a Thousand Words? An Empirical Study of Aggregation Strategies for Visual Financial Document Retrieval cites this paper.
A Picture is Worth a Thousand Words? An Empirical Study of Aggregation Strategies for Visual Financial Document Retrieval Optimizing Retrieval Strategies for Financial Question Answering Documents in Retrieval-Augmented Generation Systems
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T01:48:28.885219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1df6b4ee-9b90-40ce-8dd2-0fc5dcfcc3d7 · inbound
MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration cites this paper.
MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration Optimizing Retrieval Strategies for Financial Question Answering Documents in Retrieval-Augmented Generation Systems
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T12:34:38.868324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.