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Paper Citation Record · LEDGER

Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.08226.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2307.08226 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:28:18.559511Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-11T14:26:11.981082Z

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 166b5969-b28e-4850-be21-c88d03121327 · inbound

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps cites this paper.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-11T14:26:11.992130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-11T14:26:11.768143Z digest=sha256:6b8e9e3daa9348ea1f5b01cd4f7156b018706080213f24487a4fad1a83da7181

Observation a15ff766-6df8-4554-9eef-695b1b638ce1 · inbound

Equivariant Action Sampling for Reinforcement Learning and Planning cites this paper.

Equivariant Action Sampling for Reinforcement Learning and Planning Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T14:28:18.559511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:28:18.559511Z digest=sha256:84bbd5cb081eb1c12468f41f55a9906c834299f3667ac2e0ad59e1b36578e805