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Paper Citation Record · LEDGER

Jelly Bean World: A Testbed for Never-Ending Learning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2002.06306.

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

pith.paper-citation-record.v1
2002.06306 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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:56:51.094911Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T21:27:28.085670Z

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 9822b3bd-4d1c-4ac9-84f5-6723d589abaa · inbound

An Empirical Study of Deep Reinforcement Learning in Continuing Tasks cites this paper.

An Empirical Study of Deep Reinforcement Learning in Continuing Tasks Jelly Bean World: A Testbed for Never-Ending Learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T20:56:51.094911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:56:51.094911Z digest=sha256:ca79cd7e665b40e21ff631701977b8d5ec229cf62440558818db1a00f3b2e2a8

Observation 8491a849-a41e-4de7-ace8-f2ca305d95be · inbound

Humans Coexist, So Must Embodied Artificial Agents cites this paper.

Humans Coexist, So Must Embodied Artificial Agents Jelly Bean World: A Testbed for Never-Ending Learning

Reference 113

Resolution
metadata mismatch
local_arxiv, observed 2026-08-08T21:27:28.093427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-08T21:27:27.763181Z digest=sha256:5eed370ec7a8c67d14fe262752ffe5f39a7c26dd9ce20c1b77f1a4ec459c4c91