Paper Citation Record · LEDGER

FACMAC: Factored Multi-Agent Centralised Policy Gradients

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2003.06709.

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

pith.paper-citation-record.v1
2003.06709 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:23:07.846834Z

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

106
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 ba6cdf49-57b7-4178-9cc2-847b9bc158a0 · inbound

Light Aircraft Game : Basic Implementation and training results analysis cites this paper.

Light Aircraft Game : Basic Implementation and training results analysis FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.846834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe70f2eb-5cf6-4f38-8a19-45d2b2c4af17 · inbound

Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration cites this paper.

Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T17:49:14.548948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e701f065-98fe-454b-8049-3ee0485ec490 · inbound

Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensus cites this paper.

Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensus FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:45:28.397064Z

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.

Observation a3370656-0e27-4c4a-8513-0cbec2b39286 · inbound

Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensus cites this paper.

Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensus FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T16:21:02.367590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df2bebd4-47cb-4b8f-82b9-07ce68af3061 · inbound

Robust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learning cites this paper.

Robust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learning FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 69

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T22:15:06.188649Z

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.

Observation aa453969-d613-4080-9a91-bd4beb2c1b38 · inbound

Decoupled Delay Compensation: Enhancing Pre-trained MARL Policies via Learned Dynamics Filtering cites this paper.

Decoupled Delay Compensation: Enhancing Pre-trained MARL Policies via Learned Dynamics Filtering FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:03:51.170060Z

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.

Observation 3fdf59f5-5d5f-4c84-ae03-3b28cc7a7343 · inbound

Sim2O: Efficient Offline-to-Online MARL via Joint Action Composition cites this paper.

Sim2O: Efficient Offline-to-Online MARL via Joint Action Composition FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:09:36.633975Z

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.

Observation c0b0c554-dee5-4b5d-9566-b958c3a26a3b · inbound

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning cites this paper.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T19:30:07.599725Z

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.

Observation d64e32cc-5e5a-4705-90a0-2afb2f7ad6db · inbound

Action-Factored Multi-Agent Reinforcement Learning for Scalable Quantum Device Tuning cites this paper.

Action-Factored Multi-Agent Reinforcement Learning for Scalable Quantum Device Tuning FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-13T03:08:01.590659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be7b171f-eada-46e8-b569-e7c128d34c4f · inbound

A Self-Evolving Default Action for Cooperative Tasks with Continuous Action Space cites this paper.

A Self-Evolving Default Action for Cooperative Tasks with Continuous Action Space FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T15:04:33.059883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.