Pith. sign in

Paper Citation Record · LEDGER

Multi-Agent MDP Homomorphic Networks

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.04495.

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

pith.paper-citation-record.v1
2110.04495 v2

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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:47:01.055688Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T03:08:59.645785Z

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 a785f71c-2e34-4d5e-90e5-ca2b1d84c0dc · inbound

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

Symmetries-enhanced Multi-Agent Reinforcement Learning Multi-Agent MDP Homomorphic Networks

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T22:47:01.055688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:47:01.055688Z digest=sha256:d7c661be0e24bd30d93f2771bfd78ecea241d96852f7204c68a1a863c7cf6a3b

Observation 60da162c-2b8c-41a3-be6b-048e634ada1e · inbound

Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling cites this paper.

Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling Multi-Agent MDP Homomorphic Networks

Reference 149

Resolution
verified exact
arxiv_id, observed 2026-05-15T03:08:59.649409Z

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=arxiv_source observed=2026-05-15T03:05:36.871497Z digest=sha256:ae9a4671e06c536bd7a32fad0b6c006ac84d040759a724b909046e14b52a0b75