Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
BeBold: Exploration Beyond the Boundary of Explored Regions
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2012.08621.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T04:36:16.720368Z
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 6fe2e724-6a0f-4d36-a6b5-08c1ca7f3013 · inbound
Autonomous Embodied Agents: When Robotics Meets Deep Learning Reasoning cites this paper.
Autonomous Embodied Agents: When Robotics Meets Deep Learning Reasoning BeBold: Exploration Beyond the Boundary of Explored Regions
Reference 158
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T04:36:16.720368Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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.
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 2026-08-23T06:30:58.430688+00:00.
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.
Observation 04394cec-c92d-4064-ac4b-0cea4c16a012 · inbound
Explore Beyond the Boundary Using Entropic Information cites this paper.
Explore Beyond the Boundary Using Entropic Information BeBold: Exploration Beyond the Boundary of Explored Regions
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:26:47.637478Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.