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Paper Citation Record · LEDGER

View Space: Learning Representation across Arbitrary Graphs

As of 8 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 1 inbound Pith citation observation for arXiv:2512.11561.

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

pith.paper-citation-record.v1
2512.11561 v2

Coverage vector

measured 6 of 6 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T16:58:48.124742Z

measured 7 of 7 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T18:33:47.278805Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

6 of 6 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved5
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f0bf9661-156f-4057-9c27-27f79609d35e · outbound

This paper cites ν(P AP⊤) =P AP⊤ +I=P(A+I)P ⊤ =Pν(A)P ⊤.

View Space: Learning Representation across Arbitrary Graphs ν(P AP⊤) =P AP⊤ +I=P(A+I)P ⊤ =Pν(A)P ⊤

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T16:58:47.573886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:58:47.573886Z digest=sha256:7e9bee430818e6992b07657ae9686a7b698768b43ca8c024debf0d5be9e41e30

Observation 457835d8-563d-4419-88a6-c685bf0ecd66 · outbound

This paper cites 19 Preprint ν(P AP⊤) = (P DP⊤)−p (P AP⊤) (P DP⊤)−q =P D−p A D−q P ⊤ =Pν(A)P ⊤.

View Space: Learning Representation across Arbitrary Graphs 19 Preprint ν(P AP⊤) = (P DP⊤)−p (P AP⊤) (P DP⊤)−q =P D−p A D−q P ⊤ =Pν(A)P ⊤

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-03T16:58:47.763580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:58:47.763580Z digest=sha256:89dd52d4d71ea79eb89d136025bcee5c11e91ecfdaa4a4af92df8e06b69ee99e

Observation b924d07b-38fd-4970-bfde-87b463fbdafd · outbound

This paper cites P LP⊤ =P DP⊤ −P AP⊤ =D ′ −A ′ =L ′, and forf(z) = P k≥0 akzk, f(P LP⊤) = X k≥0 ak(P LP⊤)k =P X k≥0 akLk P ⊤ =Pf(L)P ⊤.

View Space: Learning Representation across Arbitrary Graphs P LP⊤ =P DP⊤ −P AP⊤ =D ′ −A ′ =L ′, and forf(z) = P k≥0 akzk, f(P LP⊤) = X k≥0 ak(P LP⊤)k =P X k≥0 akLk P ⊤ =Pf(L)P ⊤

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T16:58:47.839838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:58:47.839838Z digest=sha256:7314e183479dd49749b0d6f6a5d093caa756899c69cf6305059c0eafa55bf0e8

Observation 4b66076c-3b1c-4503-bdff-1e1f2491975d · outbound

This paper cites Then ν(P AP⊤) =α(I−(1−α)B ′)−1 =αP(I−(1−α)B) −1P ⊤ =Pν(A)P ⊤.

View Space: Learning Representation across Arbitrary Graphs Then ν(P AP⊤) =α(I−(1−α)B ′)−1 =αP(I−(1−α)B) −1P ⊤ =Pν(A)P ⊤

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-03T16:58:47.969191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:58:47.969191Z digest=sha256:c7114e049ec9f7264e6433d61e90232ea1609faa2b52504b1ecd386bf5c49295

Observation 4d7fc0ef-fb08-46a5-9efc-195f8f8eebb6 · outbound

This paper cites Thus, all listed preprocessing operators satisfyν(P AP ⊤) =Pν(A)P ⊤ and are permutation equivariant.

View Space: Learning Representation across Arbitrary Graphs Thus, all listed preprocessing operators satisfyν(P AP ⊤) =Pν(A)P ⊤ and are permutation equivariant

Reference 5

Resolution
malformed identifier
no resolver link, observed 2026-08-03T16:58:48.124742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:58:48.124742Z digest=sha256:c48eff401509963bde87841ac8432943d06f2d1ae02c1a0bc0b44ecf2da5af5a

Observation 94a587c2-a48b-4949-a736-2ed0e87a30fc · outbound

This paper cites Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks.

View Space: Learning Representation across Arbitrary Graphs Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-03T16:58:47.486302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:58:47.486302Z digest=sha256:85587a3c1a345f360d7d6fc352fe2b916bf54d46d17777996fb878d24c18a353

Pith citing papers

Observation 50ae4653-469e-47ec-81af-7fa4a387538d · inbound

Node4All: Learning Node Representation Beyond Datasets cites this paper.

Node4All: Learning Node Representation Beyond Datasets View Space: Learning Representation across Arbitrary Graphs

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-01T18:33:47.278805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:33:47.278805Z digest=sha256:a636474a7835e15bfe4837de9b19450fba1103c6b0196c93bb610464bbfe00d6