Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.16344.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T23:39:19.511719Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation f4d08ce1-3f90-4620-acbf-5438e6b0e899 · inbound
Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset cites this paper.
Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:39:19.511719Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 08f28854-b0d3-4271-ac50-413e01322e41 · inbound
Towards Automated Regulatory Compliance Verification in Financial Auditing with Large Language Models cites this paper.
Towards Automated Regulatory Compliance Verification in Financial Auditing with Large Language Models Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:12:49.985299Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef924105-433f-4a97-8d17-a4625b5af4b3 · inbound
Artificial Intelligence in Ship Finance: Applications, Opportunities, and a Case Study in AI-Augmented Loan Origination cites this paper.
Artificial Intelligence in Ship Finance: Applications, Opportunities, and a Case Study in AI-Augmented Loan Origination Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T20:02:35.783140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.