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Paper Citation Record · LEDGER

Goal-Conditioned Reinforcement Learning with Disentanglement-based Reachability Planning

As of 15 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.

pith.paper-citation-record.v1
2307.10846 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-30T17:53:37.012368Z

measured 0 of 1 external citation measurements

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-22T07:56:49.042239Z digest=sha256:edc74a4dee4a10c77f70288ab15ca19ea0d8396b820be0bdf715732fae16d220

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.

source=pdf_text observed=2026-07-30T17:53:37.012368Z digest=sha256:86c63cc1ad0f28aa150b5f7eee3f0f7d0f5297dc2d09a530753649b37405610b