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Paper Citation Record · LEDGER

Augmenting Neural Networks with First-order Logic

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1906.06298.

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

pith.paper-citation-record.v1
1906.06298 v3

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:15:55.469529Z

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

4
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 5a2d0a16-58a2-4a55-b449-ef7842e2dedd · inbound

LogiCoL: Logically-Informed Contrastive Learning for Set-based Dense Retrieval cites this paper.

LogiCoL: Logically-Informed Contrastive Learning for Set-based Dense Retrieval Augmenting Neural Networks with First-order Logic

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:15:55.469529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:15:55.469529Z digest=sha256:ee3206b524ac9a7f70b7db08045748bba101e4fa0f277b30e6ede74e186c2a87

Observation 41164e5b-caf4-4a67-9a2d-0b3784fd4360 · inbound

Structure-Preserving Document Translation via Multi-Stage LLM Pipeline: A Case Study in Marathi cites this paper.

Structure-Preserving Document Translation via Multi-Stage LLM Pipeline: A Case Study in Marathi Augmenting Neural Networks with First-order Logic

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-06-30T10:04:35.282282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T09:59:20.602618Z digest=sha256:779ad11d870fc9978201b2947ae01ba487bf683dd7d478cc479b01fc0e7261fa