Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Multi-Step Embed to Control: A Novel Deep Learning-based Approach for Surrogate Modelling in Reservoir Simulation
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2409.09920.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:01:25.901090Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T17:01:26.066105Z
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 5cff4adf-53c1-4cc0-bbca-ccaf967e0b8d · inbound
Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics cites this paper.
Improving Long-term Autoregressive Spatiotemporal Predictions: A Proof of Concept with Fluid Dynamics Multi-Step Embed to Control: A Novel Deep Learning-based Approach for Surrogate Modelling in Reservoir Simulation
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T17:01:26.070133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.