Paper Citation Record · LEDGER

Formally Verified Neurosymbolic Trajectory Learning via Tensor-based Linear Temporal Logic on Finite Traces

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2501.13712.

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

pith.paper-citation-record.v1
2501.13712 v1

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 2026-08-06T06:34:29.942622+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:14:54.850851Z

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 a1a1e9a9-e753-42cf-abaf-ab2cbac433f5 · inbound

AI Can Learn Scientific Taste cites this paper.

AI Can Learn Scientific Taste Formally Verified Neurosymbolic Trajectory Learning via Tensor-based Linear Temporal Logic on Finite Traces

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-02T18:14:54.850851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7732d74-ded1-4955-ae51-20de8c7a3620 · inbound

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

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification Formally Verified Neurosymbolic Trajectory Learning via Tensor-based Linear Temporal Logic on Finite Traces

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-14T17:32:30.190321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5fce39d8-154b-45e9-babe-34f013313ad7 · inbound

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

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification Formally Verified Neurosymbolic Trajectory Learning via Tensor-based Linear Temporal Logic on Finite Traces

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:45:05.436288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e0906816-2fcc-4a5e-a344-35275c900371 · inbound

Event-B Agent: Towards LLM Agent for Formal Model Synthesis and Repair cites this paper.

Event-B Agent: Towards LLM Agent for Formal Model Synthesis and Repair Formally Verified Neurosymbolic Trajectory Learning via Tensor-based Linear Temporal Logic on Finite Traces

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-19T22:52:49.973184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.