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Paper Citation Record · LEDGER

Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.19340.

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

pith.paper-citation-record.v1
2403.19340 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:57:49.961950Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T14:33:13.598561Z

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 ad484788-f370-4bef-8384-b385bcdde7b1 · inbound

A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models

Reference 305

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:33:13.604288Z

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.

source=pdf_text observed=2026-08-07T14:33:13.561958Z digest=sha256:c0faeb4c14bc21ae2e756a9fe2743135947f2d6742d686a85a21831aec545b00

Observation e29db08b-945a-49f3-ae70-8450c0c665dd · inbound

DBMS-LLM Integration Strategies in Industrial and Business Applications: Current Status and Future Challenges cites this paper.

DBMS-LLM Integration Strategies in Industrial and Business Applications: Current Status and Future Challenges Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-15T17:57:49.961950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:57:49.961950Z digest=sha256:06534ca0ae10a350381fe196403eacc378f03587c49504d66f55142f8aa85fc1