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Paper Citation Record · LEDGER

Efficient Multi-agent Reinforcement Learning by Planning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.11778.

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

pith.paper-citation-record.v1
2405.11778 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:27:42.351828Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T15:51:42.901845Z

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 f9e674f8-ae03-4629-b107-98b46ec008ec · inbound

Ego-centric Learning of Communicative World Models for Autonomous Driving cites this paper.

Ego-centric Learning of Communicative World Models for Autonomous Driving Efficient Multi-agent Reinforcement Learning by Planning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T05:27:42.351828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:27:42.351828Z digest=sha256:96d68a67f36b24535e4f7dc5c574697f567f749f7c2b27951d883acd82b8395d

Observation 821ed9ee-38ea-40b9-9624-bc946f279322 · inbound

NonZero: Interaction-Guided Exploration for Multi-Agent Monte Carlo Tree Search cites this paper.

NonZero: Interaction-Guided Exploration for Multi-Agent Monte Carlo Tree Search Efficient Multi-agent Reinforcement Learning by Planning

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:51:42.908349Z

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=arxiv_source observed=2026-05-09T19:08:50.518219Z digest=sha256:59354efdea37b29ccbbcde5240d44210eeeff355430afb888c6a9a730ca4c094