Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exact Imposition of Safety Boundary Conditions in Neural Reachable Tubes
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.00814.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:23:10.147541Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T16:23:10.518986Z
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 9784ce8e-0a3c-4e26-88ff-e3c6f5d7040e · inbound
Safe and Performant Controller Synthesis using Gradient-based Model Predictive Control and Control Barrier Functions cites this paper.
Safe and Performant Controller Synthesis using Gradient-based Model Predictive Control and Control Barrier Functions Exact Imposition of Safety Boundary Conditions in Neural Reachable Tubes
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T16:23:10.529972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 122fa0c3-b256-4a21-af11-258632636f82 · inbound
MAD-PINN: A Decentralized Physics-Informed Machine Learning Framework for Safe and Optimal Multi-Agent Control cites this paper.
MAD-PINN: A Decentralized Physics-Informed Machine Learning Framework for Safe and Optimal Multi-Agent Control Exact Imposition of Safety Boundary Conditions in Neural Reachable Tubes
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T14:42:47.811130Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.