Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2303.02073.
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 2026-08-16T10:14:54.369813Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T23:50:35.466801Z
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 223a9ce2-b5a4-4816-8446-28cee70bb27f · inbound
Dynamic Action Interpolation: A Universal Approach for Accelerating Reinforcement Learning with Expert Guidance cites this paper.
Dynamic Action Interpolation: A Universal Approach for Accelerating Reinforcement Learning with Expert Guidance How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:14:54.369813Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53c5a307-81dc-4958-afdc-e3e4110fcf36 · inbound
RoboOS: A Hierarchical Embodied Framework for Cross-Embodiment and Multi-Agent Collaboration cites this paper.
RoboOS: A Hierarchical Embodied Framework for Cross-Embodiment and Multi-Agent Collaboration How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T23:50:35.471903Z
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.
Observation 3a52b37a-f638-4063-b51a-064ffd8e0984 · inbound
AutoPath: Learning Transferable Goal-Conditioned Stochastic Path Prior for Safe Navigation Without Human Demonstrations cites this paper.
AutoPath: Learning Transferable Goal-Conditioned Stochastic Path Prior for Safe Navigation Without Human Demonstrations How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T03:31:04.614079Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.