Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Accelerating Integrated Task and Motion Planning with Neural Feasibility Checking
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.10568.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:51:05.307956Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T13:19:51.320364Z
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 e778c826-f54d-4349-9b7b-a42639bdaefc · inbound
Learning from Planned Data to Improve Robotic Pick-and-Place Planning Efficiency cites this paper.
Learning from Planned Data to Improve Robotic Pick-and-Place Planning Efficiency Accelerating Integrated Task and Motion Planning with Neural Feasibility Checking
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:51:05.307956Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43c8731a-f865-44bd-af39-13f074477998 · inbound
Learning Bilevel Policies over Symbolic World Models for Long-Horizon Planning cites this paper.
Learning Bilevel Policies over Symbolic World Models for Long-Horizon Planning Accelerating Integrated Task and Motion Planning with Neural Feasibility Checking
Reference 142
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:38:52.810035Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f6bd39f7-b398-4a3a-9f6a-532baf2281e6 · inbound
Learning Motion Feasibility from Point Clouds in Cluttered Environments cites this paper.
Learning Motion Feasibility from Point Clouds in Cluttered Environments Accelerating Integrated Task and Motion Planning with Neural Feasibility Checking
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T13:19:51.321908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.