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Paper Citation Record · LEDGER

Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 50 inbound Pith citation observations for arXiv:2007.02901.

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

pith.paper-citation-record.v1
2007.02901 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 50 of 50 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:19:35.762953Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:19:56.407223Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 97535510-0e0d-495b-a54d-40c8d4c99180 · inbound

Rethinking Link Prediction for Directed Graphs cites this paper.

Rethinking Link Prediction for Directed Graphs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 2000

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:19:35.762953Z digest=sha256:c973371457e1c722f84f8d09c73ec7459f67a47a56f7d6ce04292ba77fb0112a

Observation df81117f-8e8f-468a-a2f2-a270cf1211dc · inbound

Effects of Dropout on Performance in Long-range Graph Learning Tasks cites this paper.

Effects of Dropout on Performance in Long-range Graph Learning Tasks Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 58

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source=pdf_text observed=2026-08-08T13:03:13.930965Z digest=sha256:868d962d2b3c7fe14a9c5eba473852bc244c1d203faf8fade972ddcbe2a4f8e9

Observation 0821edb3-541e-46df-9aeb-4b09348b9dcf · inbound

Learn Beneficial Noise as Graph Augmentation cites this paper.

Learn Beneficial Noise as Graph Augmentation Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 2023

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source=pdf_text observed=2026-08-07T14:28:34.567236Z digest=sha256:078f871ff07ed4c188b22b2056a6810de436f4763cc3bd66e4777b54021cf981

Observation 8c87cb08-bf5d-4588-924d-202772e2c58d · inbound

Graph Positional Autoencoders as Self-supervised Learners cites this paper.

Graph Positional Autoencoders as Self-supervised Learners Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:54:21.034872Z digest=sha256:41568a671056453642b6e206c278016c42b0ceb5935fc3cbe392ce6cd1eabbca

Observation 3886432c-2490-4fcc-877b-2f31a5b29601 · inbound

iN2V: Bringing Transductive Node Embeddings to Inductive Graphs cites this paper.

iN2V: Bringing Transductive Node Embeddings to Inductive Graphs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:36:54.534673Z digest=sha256:0d45797f74ae81674ad7d9967a31ee5cbdac26c5b23126158779fc0c72f3ee70

Observation e40c20d7-d3b8-4b14-97c7-de3e6cddd1b8 · inbound

Mitigating Degree Bias Adaptively with Hard-to-Learn Nodes in Graph Contrastive Learning cites this paper.

Mitigating Degree Bias Adaptively with Hard-to-Learn Nodes in Graph Contrastive Learning Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.609891Z digest=sha256:5227866a098ba2f9dd6f02d1136154aaa2a06da55ab1bee56ddb4300bf1c7ec7

Observation b9da3af4-5fde-4657-9b33-037fc8c269e3 · inbound

EVINET: Towards Open-World Graph Learning via Evidential Reasoning Network cites this paper.

EVINET: Towards Open-World Graph Learning via Evidential Reasoning Network Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 22

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source=pdf_text observed=2026-08-07T05:42:42.158643Z digest=sha256:e8f3c9dc604c9e79bf2fdff7143d0f0c60f47ef6e79b45d2e36b8b5d9cc5df1c

Observation b7a826a9-fff9-4dde-b1a9-f832eb6c0152 · inbound

Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark cites this paper.

Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 42

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source=pdf_text observed=2026-08-07T00:55:54.787135Z digest=sha256:3dbaedcf2cfbc281f6ef2642c0a96c0219a5930d97beb0020af38624131a1561

Observation c04b7827-1c74-4765-baa3-85e4e0f1bf79 · inbound

When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label cites this paper.

When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 20

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source=arxiv_source observed=2026-08-06T14:45:06.870257Z digest=sha256:d388dc1a2e15c720e3fa75ab190c30e0af386e4122c9f2b968265504994ae719

Observation 57f5205c-0a85-4baf-ab52-fb09cf8a4643 · inbound

Quantizing Text-attributed Graphs for Semantic-Structural Integration cites this paper.

Quantizing Text-attributed Graphs for Semantic-Structural Integration Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 40

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source=pdf_text observed=2026-08-06T15:51:12.824411Z digest=sha256:861c2a1099db79b09f7692f2cb1cf825a6b01bb9cbc44f540f8ddd13933203ef

Observation f52bc730-4656-4f8a-8303-83b748e464a2 · inbound

From Nodes to Narratives: Explaining Graph Neural Networks with LLMs and Graph Context cites this paper.

From Nodes to Narratives: Explaining Graph Neural Networks with LLMs and Graph Context Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 3

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arxiv_id, observed 2026-05-18T23:31:54.457662Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T23:30:11.590032Z digest=sha256:f4256861a050f4a5eea39de4f2e7e26b844d3390924c08202dfc9d04315e6943

Observation 7d13d513-5a3b-4a29-a10f-5bc804660b9b · inbound

Intellectual Property in Graph-Based Machine Learning as a Service: Attacks and Defenses cites this paper.

Intellectual Property in Graph-Based Machine Learning as a Service: Attacks and Defenses Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 197

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source=pdf_text observed=2026-08-05T15:39:56.216787Z digest=sha256:74f9841baa9fba76ddf59f64e7a508472ba9b47039f59a8c760c51cd7a233203

Observation bf7c9955-b711-45c5-96f0-6a2084db6f42 · inbound

Turning Tabular Foundation Models into Graph Foundation Models cites this paper.

Turning Tabular Foundation Models into Graph Foundation Models Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 2024

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:47:53.885634Z digest=sha256:1921a054c2a4db66c453d467c2cfcb1cdbef2a943dafa387e00affda8e779777

Observation 251860ae-6cbe-46c7-ba94-81958a84b818 · inbound

GILT: An LLM-Free, Tuning-Free Graph Foundational Model for In-Context Learning cites this paper.

GILT: An LLM-Free, Tuning-Free Graph Foundational Model for In-Context Learning Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 30

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source=arxiv_source observed=2026-08-04T11:30:51.047069Z digest=sha256:71bc306f6eea7818ef68011c992e5d51208c3bce57ae9b846d518b97657a746f

Observation 3f7aaf59-4c08-4e82-937a-cd29482e9cdf · inbound

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach cites this paper.

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 32

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arxiv_id, observed 2026-05-18T08:46:07.705383Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T08:45:51.992431Z digest=sha256:59b6296b0f841feaeb96dfe571a19c37e53baa7ae1dfbf4dc1e54343fdfdf967

Observation 06f4439a-3834-4523-85e0-f620260c0f12 · inbound

Toward General Digraph Contrastive Learning: A Dual Spatial Perspective cites this paper.

Toward General Digraph Contrastive Learning: A Dual Spatial Perspective Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 39

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:18:32.201014Z digest=sha256:efa71151a10791225cd8a74775cd5fa3a446d495eb7356b238e5a8e43e69eb1a

Observation 78aa819f-569c-4731-ba0a-d29c8de01f79 · inbound

Energy-Balanced Hyperspherical Graph Representation Learning via Structural Binding and Entropic Dispersion cites this paper.

Energy-Balanced Hyperspherical Graph Representation Learning via Structural Binding and Entropic Dispersion Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 29

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arxiv_id, observed 2026-05-16T19:21:12.135441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T19:20:32.868784Z digest=sha256:076587684786523c72330ccaba6718734035f5d9cadce4848096e09654c3fb77

Observation 1282ec0f-3e10-4d2c-b3bd-b3177002e708 · inbound

Fixed Aggregation Features Can Rival GNNs cites this paper.

Fixed Aggregation Features Can Rival GNNs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 2000

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T07:43:53.861189Z digest=sha256:f08d58619037e43f1ec740a7781050559e451465842f26aa43dfdaf478beaaee

Observation 9e65ecd7-eaf7-46d7-ae16-2066456f4b4d · inbound

Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach cites this paper.

Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 2017

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source=pdf_text observed=2026-08-04T06:16:57.728507Z digest=sha256:7338e76da1a24bb5148a59da6713e8904afeb3dee388f2c5a1703baf63eaff42

Observation d09b3b8b-84c2-4d1d-85c0-65878dbc3a8d · inbound

GP2F: Cross-Domain Graph Prompting with Adaptive Fusion of Pre-trained Graph Neural Networks cites this paper.

GP2F: Cross-Domain Graph Prompting with Adaptive Fusion of Pre-trained Graph Neural Networks Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 4

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arxiv_id, observed 2026-05-25T07:35:28.051068Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T07:34:42.234291Z digest=sha256:402b99f2619eb6e91f5870bcadeb1531c36a86cc7be3add90c0ccad067053116

Observation caebab9b-ba05-4752-9146-e647aecee8cc · inbound

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs cites this paper.

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:07:41.193389Z digest=sha256:69f21b09aa002669f9446703e55867cf3fd05b2a323e822dad35b596f92b217d

Observation 588e436c-eb4f-4130-b2cb-c8a504521124 · inbound

AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation cites this paper.

AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 77

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arxiv_id, observed 2026-05-15T21:31:39.404771Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T21:30:43.925179Z digest=sha256:3a10034448ca76e4e559441f450a9a8c994d9602f72843fdabd16fa82f9ad9f7

Observation 8faab4c6-92d2-4b06-b320-6620dff9822b · inbound

Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models cites this paper.

Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 21

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arxiv_id, observed 2026-05-22T10:31:25.509877Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T10:30:01.910920Z digest=sha256:e9ba8ab37708a68c7cb855db36c9bf1536a2e63a01259cbda3aabfc5b0885eea

Observation a217ee93-e637-4c0e-a692-0c6ded0aa527 · inbound

Toward a universal foundation model for graph-structured data cites this paper.

Toward a universal foundation model for graph-structured data Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 34

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arxiv_id, observed 2026-05-11T00:25:51.998524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T18:31:39.746121Z digest=sha256:9adcfbed1708e21ac7f79e9eb7b95a1f7d6bc6f21fd88bccb13c0d91188a6ba7

Observation d2ebbfbf-c0b7-4e2f-a4b7-af30ef829d80 · inbound

Neighbourhood Transformer: Switchable Attention for Monophily-Aware Graph Learning cites this paper.

Neighbourhood Transformer: Switchable Attention for Monophily-Aware Graph Learning Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 18

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arxiv_id, observed 2026-05-11T05:40:58.454333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T18:00:47.753649Z digest=sha256:82207d8bf8685acd15409de30da91d62b725c44241ba3dbd0cdf14bb25eaedac

Observation 94592973-37b5-4daa-a5f0-56689f84a5bc · inbound

Disentangle-then-Refine: LLM-Guided Decoupling and Structure-Aware Refinement for Graph Contrastive Learning cites this paper.

Disentangle-then-Refine: LLM-Guided Decoupling and Structure-Aware Refinement for Graph Contrastive Learning Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 27

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arxiv_id, observed 2026-05-10T11:05:08.487784Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T11:03:28.089449Z digest=sha256:9e044ca9adc5d017cc5d1cb6d1425c1f75a0dbe7014ebb077adbe4e90a3700bb

Observation 75e8afd5-88bd-49b8-bf75-b1b9fee54835 · inbound

DuConTE: Dual-Granularity Text Encoder with Topology-Constrained Attention for Text-attributed Graphs cites this paper.

DuConTE: Dual-Granularity Text Encoder with Topology-Constrained Attention for Text-attributed Graphs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 10

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arxiv_id, observed 2026-05-10T05:51:09.931115Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T05:49:52.864722Z digest=sha256:55ee3f271fdbf8f37c566ad1206b05b5ade7a29834340e84f6715b2a15cd68b9

Observation c00b4cde-db82-4924-ba76-d4e0b08b8cd2 · inbound

Improving Graph Few-shot Learning with Hyperbolic Space and Denoising Diffusion cites this paper.

Improving Graph Few-shot Learning with Hyperbolic Space and Denoising Diffusion Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 2

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verified exact
arxiv_id, observed 2026-05-12T09:41:26.633904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T09:51:38.704274Z digest=sha256:ccddeb4f5f20c6aae8f0a3edce188493a8369eae4e58af71bc827103c49d6cd7

Observation 77faf7f7-c451-4d45-b57f-d29b9f448d0e · inbound

Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding cites this paper.

Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 13

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arxiv_id, observed 2026-05-12T11:01:31.294877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T16:49:54.542437Z digest=sha256:8a79cda5c17f36390913c98ca727e81f701f3b4b649e1d021e6be9d0778705cd

Observation 0cb28157-1ecc-4b6b-8732-fa8c35401a60 · inbound

UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning cites this paper.

UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 41

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arxiv_id, observed 2026-05-12T05:31:25.368340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T05:11:57.184620Z digest=sha256:a0cfac9cbe2dc02267491f64a0546eb4c9e64737b04210c8f00870886f24dab3

Observation fa288478-6c66-402f-a382-e183142c2fe7 · inbound

S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs cites this paper.

S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 22

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metadata mismatch
arxiv_id, observed 2026-05-20T12:53:17.646836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T12:49:18.671971Z digest=sha256:0bf5c95f088a4085bc3467f21f3a901895a893cb11cfb6b217023ae5820c9ce1

Observation 2d92804a-5eeb-4063-b40e-164802ad10f0 · inbound

S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs cites this paper.

S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 22

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metadata mismatch
arxiv_id, observed 2026-05-21T07:59:50.854881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T07:55:11.088587Z digest=sha256:20253d420e6843931899acbadbb95387623786ae49c4d8ce8a6407547034ed88

Observation 1acc81a9-0756-40a5-bf26-38aef5a3e1aa · inbound

Fast and Featureless Node Representation Learning with Partial Pairwise Supervision cites this paper.

Fast and Featureless Node Representation Learning with Partial Pairwise Supervision Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 31

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arxiv_id, observed 2026-05-20T06:43:06.031345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T06:39:02.277629Z digest=sha256:ccad7f23fbf6c3a9f88df8cbf9a864a5cd3bf7e4b3934bb10e6f8a93dfc1040c

Observation ce7c194f-9a4c-43b3-aa89-e0994fcc4940 · inbound

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification cites this paper.

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 29

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metadata mismatch
arxiv_id, observed 2026-05-21T08:34:05.481817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T08:32:32.410473Z digest=sha256:c68b3e7da14e0f7043e9094153cb90a206ab4634b1b07719a26447efd584a4db

Observation 7f47057d-52d7-41e9-b9ef-b07c26943325 · inbound

Where LLM Annotators Fail: Label-Free Learning on Graphs with LLMs cites this paper.

Where LLM Annotators Fail: Label-Free Learning on Graphs with LLMs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:33:30.687530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-29T14:26:07.597446Z digest=sha256:383b5937d74e8b30d2a04ff650acd8cb69e7879c75abcd1c38e8d6e788725130

Observation 9c9a2a2f-e20e-4790-8495-bfcd37ef675f · inbound

GFFMERGE: Efficient Merging of Graph Neural Force Fields and Beyond cites this paper.

GFFMERGE: Efficient Merging of Graph Neural Force Fields and Beyond Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T02:06:26.659158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T11:15:53.211895Z digest=sha256:00be6bf3ebcca91718a999fae96eabb20863b0ba7f0361e06f9eb18360ad1ab3

Observation 6f15d046-b8d8-401f-931b-903c6c519f3b · inbound

Generalizing Graph Foundation Models via Hyperbolic Retrieval-Augmented Generation cites this paper.

Generalizing Graph Foundation Models via Hyperbolic Retrieval-Augmented Generation Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-02T05:16:39.238645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T08:25:09.062736Z digest=sha256:d4b2c3e25a6cd3785300a181ea0313c51a08a347334a9a2b3394877e06c87847

Observation fefefd74-1bb6-494f-bf7f-318e9cf352fd · inbound

ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs cites this paper.

ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T04:27:37.280545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T13:52:15.860919Z digest=sha256:4d206e2ecce5cc168e8f112f1209ce1c10d74dfc95afec96259b9880c9894fe9

Observation 9e25fed0-a343-46d9-85ad-31304c60c26e · inbound

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs cites this paper.

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T08:57:47.513194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T10:41:37.290485Z digest=sha256:a514e144dcc308b029f6a96cd7c32a635323cca663583ca39e966f03ecd2c0ce

Observation e3cb08df-f17e-484d-a671-2b4539fd5924 · inbound

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching cites this paper.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 67

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T09:07:47.674460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T10:33:02.954683Z digest=sha256:e1b12dce19ea261033b6b7806eee0b0ff53c401f9af73424cdb506c13547779c

Observation cdcbca95-8b43-4a9a-8d5e-3067d9131fb2 · inbound

GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs cites this paper.

GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 69

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T11:08:03.238106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T09:41:14.904868Z digest=sha256:2b6c5f7655ff047e5065e73932adb5cba5b07368200a7940b8ef2e360466f4a3

Observation 51287a9c-aba3-4284-85e0-ce2b94db5617 · inbound

Graph Reduction in Multirelational Networks: A Spreading-Oriented Reduction Benchmark cites this paper.

Graph Reduction in Multirelational Networks: A Spreading-Oriented Reduction Benchmark Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T13:58:21.797178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T07:22:49.577516Z digest=sha256:508eb8486c5f6bebe9f6bd793a16e783fceb64bcb3c66ada71b54e854a2a5428

Observation 675733b6-a5ca-400b-b4da-3e6c8db126a6 · inbound

Boundary Embedding Shaping with Adaptive Contrastive Learning for Graph Structural Disentanglement cites this paper.

Boundary Embedding Shaping with Adaptive Contrastive Learning for Graph Structural Disentanglement Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:29:30.968673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T17:59:12.258042Z digest=sha256:af68d5a643c9422515d14c8e8edd8689164ed71eb636bff73d23db3c48b68a8a

Observation 2aa0be4f-659e-44bb-ab61-8727a622508f · inbound

Boundary Embedding Shaping with Adaptive Contrastive Learning for Graph Structural Disentanglement cites this paper.

Boundary Embedding Shaping with Adaptive Contrastive Learning for Graph Structural Disentanglement Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-02T10:54:00.462812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T10:54:00.462812Z digest=sha256:9852c200421620789ec19a70091f4b01ae1e936c2a65a38093fccec4a5fd38b3

Observation 15470418-8bbc-4812-b640-1c2c3063da44 · inbound

TaLK: Text-attributed Graph Dataset Distillation via Coupling Language Model with Graph-Aware Kernel cites this paper.

TaLK: Text-attributed Graph Dataset Distillation via Coupling Language Model with Graph-Aware Kernel Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 39

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T10:29:44.391064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T08:53:13.162764Z digest=sha256:fb10f2c80923ce798a61d6f067128eb69c5e8cb54b06b0400de837861f1fde5a

Observation b4905a43-3ba9-4df1-bd4e-69e69f62f183 · inbound

Convex--Concave Quadratic Spectral Filtering for Graph Neural Networks cites this paper.

Convex--Concave Quadratic Spectral Filtering for Graph Neural Networks Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T16:19:56.409084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T00:49:17.654830Z digest=sha256:fcb5b9a9f8b6dbc80166f375b90387270dbf29848175718bb55d19e92b7f1935

Observation c2d434d7-29ec-4772-9bfd-e3afb0b1ed1f · inbound

PromptGNN-sim: Deep Fusion and Alignment of GNN and LLMs for Text-Attributed Graph Learning cites this paper.

PromptGNN-sim: Deep Fusion and Alignment of GNN and LLMs for Text-Attributed Graph Learning Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T08:24:26.885204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T06:06:46.108334Z digest=sha256:17a337ffdbfe6aa6c5139f898c6e2aac043e402b7c532239a1f8fe10188dc8a7

Observation 2077b1db-091a-4c11-8884-861f1d6001e2 · inbound

X-LogSMask: Expand Transformer for Graph-Structured Data cites this paper.

X-LogSMask: Expand Transformer for Graph-Structured Data Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T01:07:29.732047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-03T01:00:18.263578Z digest=sha256:690aef5d0b6a218bdad809ace454cbaa2ce113337ba12c596dd3ba0dd6c3ae53

Observation 72f0c56e-1aa7-4fd7-a8b2-79ee5de4a263 · inbound

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation cites this paper.

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-01T13:29:57.675045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T13:29:57.675045Z digest=sha256:37fc8e6fdd3a4bfa11683d821debca22eec5bce353682fa00b3deb0dbda8d256

Observation 4a4c427c-fea8-447d-8dba-434c0aae292a · inbound

Train Small, Deploy Large: Zero-Shot GNN Transfer Through Geometric Renormalization cites this paper.

Train Small, Deploy Large: Zero-Shot GNN Transfer Through Geometric Renormalization Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-01T01:52:01.491244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T01:52:01.491244Z digest=sha256:84dae881b2309157fd1d2c725a59f949038d81ec215dc525ff3f04989ffeb6f6