Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2006.08718.
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 2026-08-07T04:56:29.447038Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T13:22:00.524610Z
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 ce47f3fb-9001-4d36-8cf6-8eb848d6b65e · inbound
Gradient-Weighted, Data-Driven Normalization for Approximate Border Bases -- Concept and Computation cites this paper.
Gradient-Weighted, Data-Driven Normalization for Approximate Border Bases -- Concept and Computation Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:56:29.447038Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d94f80ca-67a0-4f92-b510-a829032d2c3a · inbound
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces cites this paper.
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T13:22:00.632782Z
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.