Paper Citation Record · LEDGER

A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.19466.

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

pith.paper-citation-record.v1
2503.19466 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:48:46.081704Z

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

0
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 66948541-ee31-4448-9911-04814050b725 · inbound

A General Framework for Property-Driven Machine Learning cites this paper.

A General Framework for Property-Driven Machine Learning A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T04:48:46.081704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f8f8ee7-3eca-4b2f-a376-12c5d582018e · inbound

How to Approximate Inference with Subtractive Mixture Models cites this paper.

How to Approximate Inference with Subtractive Mixture Models A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:22:37.084438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4d04bb01-3f64-4e78-8e46-b02e171a3f00 · inbound

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification cites this paper.

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-14T17:32:30.546269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e989a0a9-9dfc-43f1-a3c3-ea7cd6d56561 · inbound

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification cites this paper.

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:45:05.230693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.