Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.15912.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T11:54:21.046418Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T15:27:05.494386Z
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 c152cc6e-f778-47ac-a218-725b289361a9 · inbound
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents cites this paper.
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T11:54:21.046418Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aec55855-c2d6-4332-9c9a-b5682de50972 · inbound
PyKirigami: An interactive Python simulator for kirigami structures cites this paper.
PyKirigami: An interactive Python simulator for kirigami structures Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:43:28.391483Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93a77bb0-cd4f-4bef-b144-182f888bb3cb · inbound
Risk-Controlled Post-Processing of Decision Policies cites this paper.
Risk-Controlled Post-Processing of Decision Policies Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction
Reference 134
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T21:36:17.110582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 77cd150f-9610-495c-94c0-fa600819de8d · inbound
Concise and Logically Consistent Conformal Sets for Neuro-Symbolic Concept-Based Models cites this paper.
Concise and Logically Consistent Conformal Sets for Neuro-Symbolic Concept-Based Models Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T12:53:17.508036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation e7c8f777-7d92-47df-b1d9-10cba466391e · inbound
Conformal Risk-Averse Decision Making with Action Conditional Guarantee cites this paper.
Conformal Risk-Averse Decision Making with Action Conditional Guarantee Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T15:27:05.495942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.