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Paper Citation Record · LEDGER

BeBold: Exploration Beyond the Boundary of Explored Regions

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2012.08621.

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

pith.paper-citation-record.v1
2012.08621 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:44:15.267730Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T11:05:08.952803Z

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 76405fa5-0000-4990-93c4-51b2eff046fd · inbound

Is Exploration or Optimization the Problem for Deep Reinforcement Learning? cites this paper.

Is Exploration or Optimization the Problem for Deep Reinforcement Learning? BeBold: Exploration Beyond the Boundary of Explored Regions

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T05:44:15.267730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:15.267730Z digest=sha256:82d37a82e1e4e70083a39cf288e91af3feb05fb54528fe1bac928a8bf3df1221

Observation d0336585-4869-4e95-bb4d-bb37e24e9574 · inbound

Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning cites this paper.

Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning BeBold: Exploration Beyond the Boundary of Explored Regions

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:05:08.954436Z

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.

source=pdf_text observed=2026-05-10T11:01:17.325738Z digest=sha256:725f524a32614e0cb24774f2af6d3386087d1e0444e3f223f7aaee00a31f0fa5

Observation 6a4320ea-eb1f-4cfe-ab1a-000ba0e89714 · inbound

Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning cites this paper.

Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning BeBold: Exploration Beyond the Boundary of Explored Regions

Reference 32

Resolution
unresolved
no resolver link, observed 2026-07-12T19:46:39.624903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T19:46:39.624903Z digest=sha256:65e0186d6d2e80d30676a030fe8c16ef44df8d5be05e4ae5af2337b581335391