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Paper Citation Record · LEDGER

Graph Convolutional Reinforcement Learning

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:1810.09202.

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

pith.paper-citation-record.v1
1810.09202 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 2026-08-14T06:32:32.682623+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:04:02.093258Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T16:35:50.563577Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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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 a0f051ea-6c39-4a3b-9071-0635dd4eda75 · inbound

Dynamic Graph Communication for Decentralised Multi-Agent Reinforcement Learning cites this paper.

Dynamic Graph Communication for Decentralised Multi-Agent Reinforcement Learning Graph Convolutional Reinforcement Learning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T23:04:02.093258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:04:02.093258Z digest=sha256:87e3287443ecd3387e44cba29d9c4732308ff0ea560b2d316d3fbdc7c8209bf4

Observation 14f454fc-d024-4e1a-b4bd-08a4ee81b6ea · inbound

Symmetries-enhanced Multi-Agent Reinforcement Learning cites this paper.

Symmetries-enhanced Multi-Agent Reinforcement Learning Graph Convolutional Reinforcement Learning

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T22:47:00.875907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:47:00.875907Z digest=sha256:bf7ee572712e9b50638d3a18eeb0b73b93bdd24165ae136aef35b6bac8130235

Observation 861a0bd6-15b4-4a98-975a-94934d41310c · inbound

PAGNet: Pluggable Adaptive Generative Networks for Information Completion in Multi-Agent Communication cites this paper.

PAGNet: Pluggable Adaptive Generative Networks for Information Completion in Multi-Agent Communication Graph Convolutional Reinforcement Learning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-09T00:36:02.732968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:36:02.732968Z digest=sha256:a44fecd255aa10ce7ed829fbd279d70843a036feffa5a84809c026df7b7b310c

Observation d00dd392-b865-465f-8bed-cb6fda893b1f · inbound

General Autonomous Cybersecurity Defense: Learning Robust Policies for Dynamic Topologies and Diverse Attackers cites this paper.

General Autonomous Cybersecurity Defense: Learning Robust Policies for Dynamic Topologies and Diverse Attackers Graph Convolutional Reinforcement Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:09.547643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:05:09.547643Z digest=sha256:cbba8a0f6bf5377525d43b488a0c0fda595bcce49a88e009b25e82b8a38c5053

Observation 12ae6d12-1e4c-4320-b61e-8df57f7649a4 · inbound

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review cites this paper.

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review Graph Convolutional Reinforcement Learning

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T17:42:51.769161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:42:51.769161Z digest=sha256:dda2a00b6559f675799e426f9ccaccd386bd0d8c3d4ed2a5c78bfb593bcdd36f

Observation 77e5204f-182a-4342-b8a1-b0c335c8ae20 · inbound

Graph World Model cites this paper.

Graph World Model Graph Convolutional Reinforcement Learning

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-06T17:37:11.682878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:37:11.682878Z digest=sha256:40923e17bf26600146ce84058a9f5f0438d5395c6602568b4bace09068a3bc5a

Observation b92bd11e-7945-4a23-8825-7a38c4ffa673 · inbound

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations cites this paper.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Graph Convolutional Reinforcement Learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T23:23:13.352117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:23:13.352117Z digest=sha256:11568d28e5b4acda63fdfcb23d710bcc755315efc4fd6024def7931ef4bff7c5

Observation 56a53bd8-749d-4a5e-8064-f920dbb2b455 · inbound

Micro-Swarm Locomotion Optimization in Dynamic Flow using Multi-Objective Multi-Agent Reinforcement Learning cites this paper.

Micro-Swarm Locomotion Optimization in Dynamic Flow using Multi-Objective Multi-Agent Reinforcement Learning Graph Convolutional Reinforcement Learning

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-01T16:35:50.564978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-30T00:30:56.136600Z digest=sha256:c4af717cc2f4b9f88d8d05b5b31b1d7b9378fd477849f4d533b7a11330874e4c

Observation d20c24f3-d20e-4b6b-9ca1-69e3b077a663 · inbound

Federated Physics-Grounded Reinforcement Learning for Distributed Stability Control in Smart Grids cites this paper.

Federated Physics-Grounded Reinforcement Learning for Distributed Stability Control in Smart Grids Graph Convolutional Reinforcement Learning

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-11T05:54:35.189048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T05:54:35.189048Z digest=sha256:ba0c9978374d961e0aab4de4db0dfa0c2a8b724fae2cda495daeeef54c511599

Observation e793fb3b-3e2f-48e0-a736-fb0c57d42a05 · inbound

Feedback Attribution and Representation Geometry: Metrics for Comparing Individual and Shared Rewards in MARL cites this paper.

Feedback Attribution and Representation Geometry: Metrics for Comparing Individual and Shared Rewards in MARL Graph Convolutional Reinforcement Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-01T20:47:24.264585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T20:47:24.264585Z digest=sha256:132ab8d89bcb0164e47a59aeea10000ea7ecfec81eba9f5995973ad10b207a55