Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Discovering Latent Causal Graphs from Spatiotemporal Data
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2411.05331.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T21:50:48.172991Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T18:16:11.994884Z
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 473ddb50-3191-4a8f-b95f-fd45c86990b8 · inbound
Neural Spatiotemporal Point Processes: Trends and Challenges cites this paper.
Neural Spatiotemporal Point Processes: Trends and Challenges Discovering Latent Causal Graphs from Spatiotemporal Data
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T21:50:48.172991Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ad0221b-7071-4b43-9ecc-ad3700104e0e · inbound
Towards explainable decision support using hybrid neural models for logistic terminal automation cites this paper.
Towards explainable decision support using hybrid neural models for logistic terminal automation Discovering Latent Causal Graphs from Spatiotemporal Data
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T21:58:29.424838Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b88f3f02-fbaa-4e2e-92c9-3ae8dbea7de3 · inbound
MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series cites this paper.
MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series Discovering Latent Causal Graphs from Spatiotemporal Data
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:16:11.997467Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.