Pith. sign in

Paper Citation Record · LEDGER

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication

As of 15 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2502.00140.

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

pith.paper-citation-record.v1
2502.00140 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:07:23.669718Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:01:01.429423Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

  • verified exact3
  • verified fuzzy8
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d6bccd32-873b-4b0e-b020-08c691e9f6ee · outbound

This paper cites Graph Neural Networks Use Graphs When They Shouldn 't.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Graph Neural Networks Use Graphs When They Shouldn 't

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:07:24.017052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.576472Z digest=sha256:3985a7a4af059c82e94e6f7a58f9a2c24eb7cb185b316e3801ac8dc713b8fbf6

Observation de071e0c-167c-46ad-b4c4-f1c483bafd04 · outbound

This paper cites I., Bronstein, M., Webb, S., and Rossi, E.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication I., Bronstein, M., Webb, S., and Rossi, E

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:07:24.006326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.581374Z digest=sha256:6b766e36defe1655bc1abf0ccdfe5a081b1d9eb380a08f204166e74e934c3faa

Observation 856e5cdc-5d89-45bb-a229-f8da8f412065 · outbound

This paper cites Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:07:23.994953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.585583Z digest=sha256:faf2e7d0736645333ed522a4a2951b2e527a0d898c5cf4c8b07b81e15df7507b

Observation 94a26355-7fd6-4a38-8025-9dd7fc0341b3 · outbound

This paper cites S., Riley, P.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication S., Riley, P

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:07:23.984621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.590058Z digest=sha256:b30d59ac91a564362430c9e297b062ce8de579f2efec20ba15e2203eab89927e

Observation 913d6573-49f1-4a62-8cbb-5e34fd21ed28 · outbound

This paper cites Inductive representation learning on large graphs.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Inductive representation learning on large graphs

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.594243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.594243Z digest=sha256:079d14b82d88327bf2c5b59e716bbf72beec37dca8b0186fac25f7e2b76ffdf2

Observation 23e27325-42a6-4432-81fa-37b847add8b4 · outbound

This paper cites Approximation Capabilities of Muitilayer Feedforward Networks.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Approximation Capabilities of Muitilayer Feedforward Networks

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:07:23.967420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.598154Z digest=sha256:a55b564f79117739f5e59a9b0369f25136b3dc967aaec806bc22ff1dd6b2976e

Observation d1c4e49e-211a-4551-b4b5-5da492385506 · outbound

This paper cites Multilayer feedforward networks are universal approximators.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Multilayer feedforward networks are universal approximators

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:07:23.957125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.601941Z digest=sha256:85eafa0814797df2f3e1908aed12572e6b8b32f7bec671385ec7e0686199c70c

Observation cc2304c1-d04b-4b25-a611-c6382171f0bd · outbound

This paper cites Scale-aware Message Passing For Graph Node Classification.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Scale-aware Message Passing For Graph Node Classification

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-09T20:07:23.888888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.606367Z digest=sha256:5fe28debf0bede8f7adb9a5d0cefb71909c224c8722d6c13314f3d66421d52ad

Observation 039be6ef-1c41-4e5d-87df-59f858ea7cf4 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Semi-Supervised Classification with Graph Convolutional Networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.610872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.610872Z digest=sha256:99e146e60f578d84b58022b414c94c28b471cdfe3df2c2ba96d6967e642453f9

Observation ac00e88a-e856-4eec-bd03-c2f5b313e7f4 · outbound

This paper cites Deeper Insights Into Graph Convolutional Networks for Semi - Supervised Learning.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Deeper Insights Into Graph Convolutional Networks for Semi - Supervised Learning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.615196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.615196Z digest=sha256:b1819d3c67154fa70d3fe86f40a218d63aae0b2a91749adad5361ebac13a5a90

Observation 7e2b5df9-cf95-46bf-865b-f9b54d5e5779 · outbound

This paper cites Gated Graph Sequence Neural Networks.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Gated Graph Sequence Neural Networks

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.619544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.619544Z digest=sha256:7dd6475c35879a62cb7eea182514e9609c318976255e5aec0ab963066838c27c

Observation 64ea5558-7d20-4909-8b52-e7f6b58d77ae · outbound

This paper cites K., Liu, X., and Murata, T.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication K., Liu, X., and Murata, T

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.623846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.623846Z digest=sha256:08ee79318e52a8d6c1c3a0799db44fc0bd45b586e6f84851d35cbc3425d19e02

Observation 9d18bfee-576e-48d1-b501-158d90e5e2e6 · outbound

This paper cites Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:07:23.945900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.627502Z digest=sha256:94b21bf132477cdbb201d61dbb9e6294f406a149b417f3e367c3fe6b38f1e607

Observation c49833a4-cc0a-4633-a850-c5c24fd026d5 · outbound

This paper cites Geom-GCN: Geometric Graph Convolutional Networks.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Geom-GCN: Geometric Graph Convolutional Networks

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.631145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.631145Z digest=sha256:de485518d456372ca71cceb4dd717ec24822f8c68e9914a3d7ac884474a52592

Observation b1c761d3-9420-43f4-b2c5-edb0638d3315 · outbound

This paper cites an unresolved cited work.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-09T20:07:23.934192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.635065Z digest=sha256:27d61743c797bad3ffe57d7837c4684e86cfc7b22c9ecab01fb8fc4027e91430

Observation cd4bfc36-8d10-4ec0-bb0f-458403e2144a · outbound

This paper cites Multi-scale attributed node embedding.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Multi-scale attributed node embedding

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.638373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.638373Z digest=sha256:c845028948e4f1425c2add7109df612e64942647c68b966225c222a872170f4a

Observation 3357e830-d1bd-43a5-960b-f261893c9245 · outbound

This paper cites A Survey on Oversmoothing in Graph Neural Networks.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication A Survey on Oversmoothing in Graph Neural Networks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.641929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.641929Z digest=sha256:d6079b17b33ab8c32430b16faba142de33fd6d6431ebf5139c514cc814656923

Observation 3759fd38-87d9-4cd8-a902-8a01533151a5 · outbound

This paper cites Graph Neural Networks with maximal independent set-based pooling: Mitigating over-smoothing and over-squashing.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Graph Neural Networks with maximal independent set-based pooling: Mitigating over-smoothing and over-squashing

Reference 18

Resolution
verified exact
doi, observed 2026-08-09T20:07:23.715150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.645906Z digest=sha256:c6b3e5a25ffd1883486ce459988e2d0afd71342cbcdce7d440f822c1b68ac2e8

Observation 9173a79e-525f-404a-8be3-da3702b09c1b · outbound

This paper cites Directed Graph Convolutional Network.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Directed Graph Convolutional Network

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.649467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.649467Z digest=sha256:b569f12eefaeb467a3c74154c208429231c883ae41b0c67788a459cdc7dbf088

Observation 9ff3dc34-905e-4142-981a-b3daae6d7ce9 · outbound

This paper cites C.-W., and Han, J.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication C.-W., and Han, J

Reference 20

Resolution
verified exact
doi, observed 2026-08-09T20:07:23.701428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.653760Z digest=sha256:b3d3057c2d20052bb5c79088136dcd711a24ec41f144740ceec59db49cc878f4

Observation fbf695ce-a132-47e2-8d2b-c7b06dd08501 · outbound

This paper cites How Powerful are Graph Neural Networks?.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication How Powerful are Graph Neural Networks?

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.657083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.657083Z digest=sha256:c0422c2e6d55c579fc8446c723e80f5864fe46c3ea50c43330321ed8a38e06d0

Observation 419e74b6-a15a-4684-b361-3c0aeb87704e · outbound

This paper cites Magnet: A neural network for directed graphs.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Magnet: A neural network for directed graphs

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:07:23.915219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T20:07:23.660523Z digest=sha256:0128642e2e7154abc08d3ba9fd9b5012b13c9d0411042a5fc928f83a317f0cbc

Observation 7b2c4621-8934-442d-954e-3fe732dee8de · outbound

This paper cites Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.663764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.663764Z digest=sha256:fefa29d4747ed9c1d5bd13cf677cce70e33176988d220b13ad5e80c21064e837

Observation fafa0de1-8f2e-4e71-a4b9-ec25541d2412 · outbound

This paper cites Beyond homophily in graph neural networks: Current limitations and effective designs.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication Beyond homophily in graph neural networks: Current limitations and effective designs

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.666795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.666795Z digest=sha256:3d1b101eee2e953088e79db765b30315f0f6b01423b7590a94cb192d5dc6f200

Observation f3aae9df-0b42-44da-a59e-7ade4aa44987 · outbound

This paper cites write newline.

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication write newline

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-09T20:07:23.669718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:07:23.669718Z digest=sha256:049761281a43c1da050b784057d455279ce7d86602e91a1fe689737b5e21b2a8

Pith citing papers

Observation 2ba4e3be-0b0e-42fa-bbe7-db9b565ed19b · inbound

Machine learning of electronic structure and atomistic properties from the external potential cites this paper.

Machine learning of electronic structure and atomistic properties from the external potential Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-02T23:01:01.429423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:01:01.429423Z digest=sha256:91ce269f37a52dfa515d968ff749c41a66af7f56b70faa2addf2f527107c13ba