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Paper Citation Record · LEDGER

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks

As of 14 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 2 inbound Pith citation observations for arXiv:2412.06173.

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

pith.paper-citation-record.v1
2412.06173 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:00:34.395601Z

measured 52 of 52 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 2026-05-22T00:58:31.100417Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T01:00:51.523686Z

Reference resolution

50 of 50 outbound references displayed

  • verified exact1
  • verified fuzzy29
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 22a11b61-75ed-4c99-ac9a-b56091fe4bf2 · outbound

This paper cites On the bottleneck of graph neural networks and its practical implications.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks On the bottleneck of graph neural networks and its practical implications

Reference 1

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no resolver link, observed 2026-08-11T20:00:34.254511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.254511Z digest=sha256:690852539e48390364f03b1b25834fe7a80463f533c47dec15a16a76fcdad9e8

Observation 1c8ce0d8-c254-49fb-a137-00034e7ce6ff · outbound

This paper cites Diffwire: Inductive graph rewiring via the lovasz bound.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Diffwire: Inductive graph rewiring via the lovasz bound

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.915495Z

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=2026-08-11T20:00:34.257456Z digest=sha256:37ceb4a810da319f365521c5f53e88231ed62ae2f2fecf7db07b99f20544e34d

Observation a91c6f5a-d957-4a2f-bb02-694d7a3a9c37 · outbound

This paper cites Graph neural networks use graphs when they shouldn't, 2024.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Graph neural networks use graphs when they shouldn't, 2024

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.905121Z

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=2026-08-11T20:00:34.260080Z digest=sha256:dcd9d04c8f43e852a7a0973e57471f7d8d6606a97e429a1fe0f4ff2a24a5e9a4

Observation 6affe739-ccd3-4747-946e-7a1180544703 · outbound

This paper cites Understanding oversquashing in gnns through the lens of effective resistance.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Understanding oversquashing in gnns through the lens of effective resistance

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.895609Z

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=2026-08-11T20:00:34.263070Z digest=sha256:5d0965353a6b9c98ea554a614c5ed69944ee48b129c0807fc69af8b2cf317d93

Observation b921d7c0-574e-4182-b5be-c29803e918e4 · outbound

This paper cites Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks

Reference 5

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no resolver link, observed 2026-08-11T20:00:34.265717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.265717Z digest=sha256:7cc89580a0c1d9b78bd1fa16fbc986f3b45f06aa29884714c01e5119fb84af22

Observation c8f481c2-b2ce-491e-8722-a6dc30734ef2 · outbound

This paper cites Bronstein, Joan Bruna, Y.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Bronstein, Joan Bruna, Y

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.885756Z

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=2026-08-11T20:00:34.268855Z digest=sha256:5b972566d9e5b105a6bd2421d65ab3c55a6a597b8b1fcb84d036d631d247af6d

Observation b4228aa7-b75e-430e-9029-161f6e4a7d57 · outbound

This paper cites Hyperbolic graph convolutional neural networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Hyperbolic graph convolutional neural networks

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.877666Z

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=2026-08-11T20:00:34.271710Z digest=sha256:4b505202fd02ef24183b257531828554d447a11ba4ab927ff15141ab0e9de2da

Observation a1c3a042-cced-48e8-bee2-e4525bbc1fea · outbound

This paper cites Fully Hyperbolic Neural Networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Fully Hyperbolic Neural Networks

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.274020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.274020Z digest=sha256:6bdfb8ffbdcbae15de6d4af3d979cb9f4154f389e28c63c8b83db6413901daf0

Observation cb711827-c919-44e8-bad2-9abd9f53798e · outbound

This paper cites Convolutional neural networks on graphs with fast localized spectral filtering.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Convolutional neural networks on graphs with fast localized spectral filtering

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.869699Z

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=2026-08-11T20:00:34.277380Z digest=sha256:3ba4c65567238ad74087a455e25bdef14de055d7621651d748fa71de1ea739ac

Observation 42e82e29-1c38-46df-b61f-c93c0517d5c7 · outbound

This paper cites Bronstein.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Bronstein

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.860493Z

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=2026-08-11T20:00:34.280243Z digest=sha256:ae1bb00035b152297d72a774ece17b0dd1ec5094419e33be4d6a0740d0cc396f

Observation 1052fd9d-50e6-4e88-925f-c17d4d36b9d8 · outbound

This paper cites Hyperbolic neural networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Hyperbolic neural networks

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.850791Z

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=2026-08-11T20:00:34.283253Z digest=sha256:6399f4a13838c58bfd030b33c69811c229f62c29ab7261ec556f3109d23bd0c5

Observation 22043c32-0f1c-4fea-82d9-4cc2c2223756 · outbound

This paper cites Diffusion improves graph learning.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Diffusion improves graph learning

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.842031Z

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=2026-08-11T20:00:34.286101Z digest=sha256:f7abc99640a50f0ec99695409c9fb2dafdaf9fbd79d4ec9890b73cc19a21fff3

Observation 2ca3eaed-cb21-4ab4-ba6d-acf86d45b12e · outbound

This paper cites Hamilton, Zhitao Ying, and Jure Leskovec.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Hamilton, Zhitao Ying, and Jure Leskovec

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.832881Z

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=2026-08-11T20:00:34.289147Z digest=sha256:85b25f0d8c85786b3c93cc96d5d2d2e20686cb58e3ddf8f7a20e523293df86bc

Observation b44914ae-2f9a-4878-a9f7-536ef69f7f0d · outbound

This paper cites Harris, K.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Harris, K

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.823989Z

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=2026-08-11T20:00:34.291877Z digest=sha256:e1f6bee9ea1b4deaebb3b015d64d985b0773cc69264e9939191c7d512859ba1e

Observation 00b1bb22-49b0-45c2-af3e-04654e723a20 · outbound

This paper cites Mitigating Degree Biases in Message Passing Mechanism by Utilizing Community Structures.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Mitigating Degree Biases in Message Passing Mechanism by Utilizing Community Structures

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.294777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.294777Z digest=sha256:bdd4916eb4fc75e5b99d4e575a1523b04944e59ff4ddceb8d636a8cfcb858323

Observation ee54581c-8003-4128-864b-11d3242f6c4e · outbound

This paper cites Open Graph Benchmark: Datasets for Machine Learning on Graphs.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.298186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.298186Z digest=sha256:627de8c8591236b1da679afb983d19e44522ad5561e5826ce2cd5200dde08d72

Observation 5a04ce65-9eda-4281-999b-5569a4d5b1a2 · outbound

This paper cites Combining Label Propagation and Simple Models Out-performs Graph Neural Networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Combining Label Propagation and Simple Models Out-performs Graph Neural Networks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.301665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.301665Z digest=sha256:acacd9ebb5dcf3ccd50ff2e846bb7ec4e40abfdbba0ba0fa8df56820c4647466

Observation bbde50c4-b664-4f94-8b61-aa6fdfefde13 · outbound

This paper cites Stevenson, and Lizhen Lin.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Stevenson, and Lizhen Lin

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.815139Z

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=2026-08-11T20:00:34.305023Z digest=sha256:6e236d80d2a80ba37b9334249046764bd71308e3ddaeb639c9edeb205528cdf3

Observation 221673f8-d877-40bf-a221-5fb4153188c7 · outbound

This paper cites Banerjee, and Guido Montufar.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Banerjee, and Guido Montufar

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.308020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.308020Z digest=sha256:fd31e2620e71e511afa2ce8265e67efc28bc836709bca4f78fec882cc8cc1316

Observation 16ea4704-145e-4da5-bcc1-f6a171e2f412 · outbound

This paper cites Shedding light on problems with hyperbolic graph learning.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Shedding light on problems with hyperbolic graph learning

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.800124Z

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=2026-08-11T20:00:34.311188Z digest=sha256:e98d06b38fd00c9ffb509168b5bdf4a5181a13edef12e245be58e23ffb8f2bf3

Observation 23c7c7a3-898e-4dfe-a51d-a215c4d9869c · outbound

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

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Semi-Supervised Classification with Graph Convolutional Networks

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.313818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.313818Z digest=sha256:c8b95aa99c3ac2f3f5ba8a532ed8d378cb516cd767cfc204a1c9b74dd61e09af

Observation 1ce9958b-f130-4330-b699-7aca85a3b7e6 · outbound

This paper cites Kleinberg.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Kleinberg

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.791123Z

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=2026-08-11T20:00:34.316948Z digest=sha256:f95ab4f15f209b9670e48f073170f054c4d579b711b5b9a6fdc42433af564462

Observation ef74f5a8-4b7f-4338-aae8-7a2cf030f8ad · outbound

This paper cites Predict then propagate: Graph neural networks meet personalized pagerank.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Predict then propagate: Graph neural networks meet personalized pagerank

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.781942Z

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=2026-08-11T20:00:34.320046Z digest=sha256:28bd21e7f29e0367f781b98de648e6777cec515b516ad660b3397d85bba032b9

Observation cf6effd8-d329-4b02-bba9-fa6b6c6f11b3 · outbound

This paper cites Towards deeper graph neural networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Towards deeper graph neural networks

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.772434Z

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=2026-08-11T20:00:34.322834Z digest=sha256:b3b7db5c05589f12ade846b9c8d9afb28b84a8484abd9f4d754d1e26ab6bff11

Observation bff719e0-66ff-4b7b-a4b3-0c28ab1676e3 · outbound

This paper cites Differentiating through the fr\'echet mean.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Differentiating through the fr\'echet mean

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.763358Z

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=2026-08-11T20:00:34.325658Z digest=sha256:53226e71e9b9d0bd3b0c229b1321fd1d8e9e50238c082fdbce7cd7cb4c6338b7

Observation 46d55731-2115-47d2-bcd0-63e3b30e0d6b · outbound

This paper cites Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.328301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.328301Z digest=sha256:21bfbd12e04769203dfb09982a682d0bc8ef412af655f2d89fa02b006a470442

Observation 82946a4a-ae0b-42ca-aa11-07efeab1ba73 · outbound

This paper cites Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-11T20:00:34.564193Z

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=2026-08-11T20:00:34.331434Z digest=sha256:b9874ba4909764af9469bec65db301b5d0a48053d0bb8129c10cb34ae16222ba

Observation 23fbdfc1-8f49-438b-8498-f095da3ae1ea · outbound

This paper cites Boscaini, Jonathan Masci, Emanuele Rodol \`a , Jan Svoboda, and Michael M.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Boscaini, Jonathan Masci, Emanuele Rodol \`a , Jan Svoboda, and Michael M

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.754402Z

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=2026-08-11T20:00:34.334845Z digest=sha256:6f07be5d804aea8085035033581f2b953b5d2f4c69110518b1319580858b372e

Observation c5fedc2f-b5b3-465c-a36f-e0a05746ddad · outbound

This paper cites Revisiting over-smoothing and over-squashing using ollivier-ricci curvature.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Revisiting over-smoothing and over-squashing using ollivier-ricci curvature

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.745945Z

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=2026-08-11T20:00:34.337511Z digest=sha256:42d4b3984ebcb4aaf5fd0cac880c734bd55e5ed13cf0af48abc8ac0972582518

Observation 8b7e881b-cb52-49bd-86ac-be8a660ea27f · outbound

This paper cites Poincar \'e embeddings for learning hierarchical representations.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Poincar \'e embeddings for learning hierarchical representations

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.737702Z

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=2026-08-11T20:00:34.339842Z digest=sha256:c62302aa64d36ab357f852c812fdf33110314a57e9ba52a4f9641f1957259e11

Observation 3a8919c9-3c94-49b6-bc27-03145fe3ce29 · outbound

This paper cites Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Graph Neural Networks Exponentially Lose Expressive Power for Node Classification

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.342079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.342079Z digest=sha256:42175455bbcc7a2097fa1b743453d2ee421ced9552533237c3bf67352b936589

Observation a56c2dcd-b714-43e9-ae2f-fbce03b5dd8e · outbound

This paper cites Multi-scale Attributed Node Embedding.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Multi-scale Attributed Node Embedding

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.344533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.344533Z digest=sha256:ad9828bca888fa83d9e00b74e79be9e295cd6a308f02242af3d6c5e427fdffc4

Observation c01acd07-7e8e-47f4-a5db-c08ffc6cfa91 · outbound

This paper cites Konstantin Rusch, Michael M.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Konstantin Rusch, Michael M

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.347509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.347509Z digest=sha256:17d3e8ab4bcc19fd0c4c4f47008757354533198842f8f51271a238f1e4b1a55d

Observation b917894b-515d-4c7d-9bd1-308588e7bdbb · outbound

This paper cites Low distortion delaunay embedding of trees in hyperbolic plane.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Low distortion delaunay embedding of trees in hyperbolic plane

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.724105Z

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=2026-08-11T20:00:34.349871Z digest=sha256:1862f339aa718e69cad685b6632698d0dcd543127717ad6623c77b3649a7febb

Observation a918c9aa-10ad-40df-886c-59b4feb1e78e · outbound

This paper cites Collective classification in network data.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Collective classification in network data

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.715338Z

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=2026-08-11T20:00:34.352248Z digest=sha256:dd735e2a65e36eae819e43713964bbd769c49043c9c088f300fbac82dd41c391

Observation be80fcb1-0a58-4727-a531-b1c99bebb3ef · outbound

This paper cites Pitfalls of Graph Neural Network Evaluation.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Pitfalls of Graph Neural Network Evaluation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.355102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.355102Z digest=sha256:dbffd27950fd3d770386ef8f1671e9db41cc682213e168db35fcb5735a030000

Observation e7888761-96f3-49f7-af4d-48d3a743a3a6 · outbound

This paper cites Venkatachalam, Danica J.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Venkatachalam, Danica J

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.706364Z

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.

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Observation ad051392-bf4d-4ba4-8249-a26010de58cf · outbound

This paper cites Relwire: Metric based graph rewiring.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Relwire: Metric based graph rewiring

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.697425Z

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=2026-08-11T20:00:34.360961Z digest=sha256:0325f5946c93232929981a68f1c1308b1ae1b0c7a85b1ea0014a6dba53d4b551

Observation a52db9d3-605d-4838-8af3-fda337dba70f · outbound

This paper cites Semi-supervised learning (chapelle, o.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Semi-supervised learning (chapelle, o

Reference 39

Resolution
verified fuzzy
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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.

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Observation 729b42e2-d5f1-41d8-9121-39c92270d459 · outbound

This paper cites Is rewiring actually helpful in graph neural networks?, 2023.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Is rewiring actually helpful in graph neural networks?, 2023

Reference 40

Resolution
verified fuzzy
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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=2026-08-11T20:00:34.366598Z digest=sha256:590b061840ed6a730033c9bb12b434dbbec17f6bd50571c1ebbe961edff3d582

Observation ede12201-1e59-4312-843c-25585b150db1 · outbound

This paper cites Graph Attention Networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Graph Attention Networks

Reference 41

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.369345Z digest=sha256:0c8421d584fcabec307d675f1d62de9c17b105399ea5e4de74e453526b2e1d05

Observation 307f6096-c3da-45bc-8ed3-cd39ebb27f47 · outbound

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

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.372348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.372348Z digest=sha256:ee697ae76a370be1437ea9d2af6867ca24b59d06b9f6f717efafef8e6d2e4db3

Observation 7031beac-1523-4608-b59e-951b2de83f1e · outbound

This paper cites Watts and Steven H.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Watts and Steven H

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.666957Z

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=2026-08-11T20:00:34.375255Z digest=sha256:a816bc41396fa421dc5c6b1efd587d4e38228e2581739e118d6a6aa42dc0469c

Observation df5c6d59-aa17-4192-9a3e-560785be102a · outbound

This paper cites Simplifying Graph Convolutional Networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Simplifying Graph Convolutional Networks

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.377872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.377872Z digest=sha256:213ad7014e091703ae6781b27f863dc5dbf0d0ac7ec779cf030fcd21f219f903

Observation 8b87c9f9-ddfa-4bf6-b988-870e937dc379 · outbound

This paper cites an unresolved cited work.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-11T20:00:34.657352Z

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=2026-08-11T20:00:34.380945Z digest=sha256:914feeb7310f96e5e25913b1e98af4336dd5544dbc711b9171331c126dac9e02

Observation 75b9db1f-dea7-4a57-886f-482b6f33264e · outbound

This paper cites How Powerful are Graph Neural Networks?.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks How Powerful are Graph Neural Networks?

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.383685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.383685Z digest=sha256:82dc1d84e227052c2d6b4bb856e0e3d3ccc9b3ae745f24c6bfc78bb0bc26b3c7

Observation e61487ba-1ea3-4ef4-8b03-0df70eaef3a8 · outbound

This paper cites Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.386889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.386889Z digest=sha256:e7950357559841b44cec7feb9582e6f169317a108071a6cac0236c8fe1bc50db

Observation 813daed5-a55c-4607-a0cc-cbd80cf4acfc · outbound

This paper cites Hyperbolic graph attention network.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Hyperbolic graph attention network

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.647190Z

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=2026-08-11T20:00:34.389973Z digest=sha256:54700cbe590590d87720b0672f3e702f6d46636e67403d93300d91eb15f1d791

Observation 8f988105-61ca-4cdd-82cd-689281475ef7 · outbound

This paper cites Lorentzian graph convolutional networks.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Lorentzian graph convolutional networks

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:00:34.637319Z

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=2026-08-11T20:00:34.392658Z digest=sha256:9497ded695476fd1fb095bd555ab8e520434170268a22976d1651622a66516e7

Observation de446992-3c78-4847-ab50-708fd087c4fe · outbound

This paper cites write newline.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks write newline

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-11T20:00:34.395601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:00:34.395601Z digest=sha256:562fccd9c1a5d90b1dd07b8fc789c3da1a0b0ef39b121cf5112baa107ab9f0f1

Pith citing papers

Observation 428d2124-3d0a-43d5-b0ef-585871fee8d9 · inbound

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence cites this paper.

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence Revisiting the Necessity of Graph Learning and Common Graph Benchmarks

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-20T15:18:25.326643Z

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=2026-05-20T15:17:23.832754Z digest=sha256:6e0a0f6a18cf7edf005281bf6bd77e9c0a0a11219a98757a55fd835506d94c1a

Observation b6e429be-f7f6-4ff7-af27-29041629732c · inbound

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence cites this paper.

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence Revisiting the Necessity of Graph Learning and Common Graph Benchmarks

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-22T01:00:51.526727Z

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=2026-05-22T00:58:31.100417Z digest=sha256:6059975d0e2a59df34ca389b41da492eb19a9eeab80888e4ab9e00a7edd6ccd8