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Paper Citation Record · LEDGER

Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.16344.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2305.16344 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:12:49.985299Z

measured 1 of 1 external citation measurements

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 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.

source=pdf_text observed=2026-08-06T15:12:49.985299Z digest=sha256:74d9f6d8cc90b753c25ccfdabab63973e234fb4d54c13d93470bf92ce10cab7e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T19:56:19.838206Z digest=sha256:306bf6c3575a632bd24391e6ca325356992eb8bd8fe8912155d3dde8984a58c3