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Paper Citation Record · LEDGER

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2303.03376.

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

pith.paper-citation-record.v1
2303.03376 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:30:10.090187Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 059f6064-4ede-451b-8be4-a898f0bfce86 · inbound

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution cites this paper.

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

Reference 282

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:12:31.183925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-16T08:12:30.984870Z digest=sha256:c510a54d0f8ba4662fab1d1f1d8dbfe80cac2df2bf57e8058dfcadd616b34e0a

Observation 85b4695b-842f-4fab-b693-abd86b2ba4a5 · inbound

Evolution and The Knightian Blindspot of Machine Learning cites this paper.

Evolution and The Knightian Blindspot of Machine Learning MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

Reference 169

Resolution
unresolved
no resolver link, observed 2026-08-10T16:30:10.090187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:30:10.090187Z digest=sha256:3fbdd0470da028dc92c001823ab3c8bd64f2775cb23ff8d061923f7eae277179

Observation 546c4fe2-a45d-46a9-98ac-0907386ba167 · inbound

PACE: Parameter Change for Unsupervised Environment Design cites this paper.

PACE: Parameter Change for Unsupervised Environment Design MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T17:01:05.843480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-09T14:21:34.002785Z digest=sha256:761532077a2fc016cdf06a9ac9d87ce4707501890fa1fa127c322316b20d1823

Observation aa721785-76f7-4dbf-a538-1f3d66a40403 · inbound

SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning cites this paper.

SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

Reference 67

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T06:21:26.492248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T04:21:44.087943Z digest=sha256:cca848d811d3fe4862dca0423c05c28a9e09fbda522fab75a10cf5342381a75c

Observation cb987667-e0a1-406c-a751-64fab23b5dcd · inbound

SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning cites this paper.

SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

Reference 67

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T21:32:59.516814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T21:30:42.766390Z digest=sha256:32124001a96a11b7c9cae86e2c3196a489e132d9132f91f76e3b16065862da70