Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Goal-Conditioned Reinforcement Learning with Disentanglement-based Reachability Planning
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.10846.
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 2026-07-30T17:53:37.012368Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T08:01:15.974036Z
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 271399cd-0bae-4f54-9c9b-432f1d35b48d · inbound
Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics cites this paper.
Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics Goal-Conditioned Reinforcement Learning with Disentanglement-based Reachability Planning
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T08:01:15.976144Z
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 d2c29f64-e791-4a0a-a998-6939adb1345b · inbound
Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models cites this paper.
Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Goal-Conditioned Reinforcement Learning with Disentanglement-based Reachability Planning
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-07-30T17:53:37.012368Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.