Paper Citation Record · LEDGER

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks

As of 13 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 2026-08-12T06:34:41.77262+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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Source-reported events for the cited work

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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 2026-08-12T06:34:41.77262+00:00.

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

Resolution: 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 2026-08-12T06:34:41.77262+00:00.

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

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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

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

Source-reported events for the cited work

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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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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Source-reported events for the cited work

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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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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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

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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

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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 2026-08-12T06:34:41.77262+00:00.

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

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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 2026-08-12T06:34:41.77262+00:00.

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

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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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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Source-reported events for the cited work

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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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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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

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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.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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

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Source-reported events for the cited work

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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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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; raw_fallback, observed 2026-08-11T20:00:34.688233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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; raw_fallback, observed 2026-08-11T20:00:34.676789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

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Source-reported events for the cited work

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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

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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 2026-08-12T06:34:41.77262+00:00.

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

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

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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

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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.

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.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.

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.

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 2026-08-12T06:34:41.77262+00:00.

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 2026-08-12T06:34:41.77262+00:00.