Pith. sign in

Paper Citation Record · LEDGER

Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2010.04740.

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

pith.paper-citation-record.v1
2010.04740 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:04:02.191960Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T03:28:50.279855Z

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 05b20a7e-53c4-4ce0-a559-d5f20bfea7a0 · inbound

Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning cites this paper.

Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:28:50.283141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-24T03:26:12.175794Z digest=sha256:f205c518c151872c7203c2f3a1992606dcaad0ba890f9bc5a19a1f3a765ffb6a

Observation 0c82be9f-b531-4a46-9f6e-c64e09b90afc · inbound

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

Dynamic Graph Communication for Decentralised Multi-Agent Reinforcement Learning Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T23:04:02.191960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:04:02.191960Z digest=sha256:b9f01cf8e89c42dd432a32592df8bd5957d98e242bd09c1130d49bd8f245f311

Observation f3fd1ea1-0396-4a11-aa80-ce8eeaa8fc7a · inbound

Heterogeneous Value Decomposition Policy Fusion for Multi-Agent Cooperation cites this paper.

Heterogeneous Value Decomposition Policy Fusion for Multi-Agent Cooperation Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-09T10:52:39.141965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:52:39.141965Z digest=sha256:e43e650a7fed20856963c7c84fabbceee7918d3b6aac826417cefd6e4cf0ec59

Observation ee481667-cc6f-492c-95f2-e1d92a6b28db · inbound

Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning cites this paper.

Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T10:40:38.829339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:40:38.829339Z digest=sha256:ab1fe2c9fe07b0e1adad127f338f4d645ec37f8d31aa1ecc9fd9f515f15c2680

Observation e34d698f-cd12-41ac-930b-58121c360242 · inbound

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning cites this paper.

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:56:27.351332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-12T01:31:19.576223Z digest=sha256:ea2a1829f86e138ea505ab500406183041050bdccb5b3a693474100e3f972d46

Observation 32b898a1-739d-4b66-9e1c-404ec7b42833 · inbound

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning cites this paper.

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:39:10.742765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-20T22:34:46.440511Z digest=sha256:802216763270876b3f83f235b734dea1ac1cc5a173cc749d8ae8db55b63ddad7