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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 49 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 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 49 of 49 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:03:13.930965Z

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 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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:03:13.930965Z digest=sha256:9b4af81205d6cd31bc3a043b6f93814e01b90537f617d6f4a0768a4783a72078

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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no resolver link, observed 2026-08-07T14:28:34.567236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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no resolver link, observed 2026-08-07T12:54:21.034872Z

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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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no resolver link, observed 2026-08-07T10:36:54.534673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:36:54.534673Z digest=sha256:6f5d6d16755ee51a71cc34a04fad28aa4a4f0968eb0cb40ace0b0c075b94c7a5

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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Source-reported events for the cited work

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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no resolver link, observed 2026-08-07T05:42:42.158643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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no resolver link, observed 2026-08-07T00:55:54.787135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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no resolver link, observed 2026-08-06T14:45:06.870257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:45:06.870257Z digest=sha256:2678d7e9811fc79335156815b1710921b7870923ae1a33bee32af22b08f0fd50

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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no resolver link, observed 2026-08-06T15:51:12.824411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T23:30:11.590032Z digest=sha256:8c795d0096278419f2805ef89eced9ef7a99905094f551dcc58a4f1d18b66c79

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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no resolver link, observed 2026-08-05T15:39:56.216787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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Source-reported events for the cited work

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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no resolver link, observed 2026-08-04T11:30:51.047069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T08:45:51.992431Z digest=sha256:63ced77f57e3fc6d401d1e87337479051430c381d35807f5c68673e7d3b971c4

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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no resolver link, observed 2026-08-04T09:18:32.201014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:18:32.201014Z digest=sha256:c5485ef07c94196904b9f5479f916f74961b526a965d2699e1eca1a1a7e7d941

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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verified exact
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T19:20:32.868784Z digest=sha256:b7bcc7aefe01d47989ebb764e66b663d9964b90f03156bdd6fd99eb01b4d67e8

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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no resolver link, observed 2026-08-03T07:43:53.861189Z

Source-reported events for the cited work

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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no resolver link, observed 2026-08-04T06:16:57.728507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-25T07:34:42.234291Z digest=sha256:0614c3c272b1e7f828c800943d787f8c3d818791c9ea15efdd9ad3302ef7bd61

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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no resolver link, observed 2026-08-03T00:07:41.193389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:07:41.193389Z digest=sha256:f83d0a341edc353c0e2f52016b8dad1cc606c1f87970090a20fbff1c46c3b420

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T21:30:43.925179Z digest=sha256:e1ef755eb2b7f2d60214ec5683ede1d7b89436f9ac02f1de8def8118ef54b57d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T10:30:01.910920Z digest=sha256:e916ea07ed85a3ec24fc6a2e6322157ea269d874faec89adecedb5e546dff458

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:31:39.746121Z digest=sha256:2c48753ed90cea85d295f0fc1329116feaaf83fd621f03bee34caae4e69b2ebc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:00:47.753649Z digest=sha256:1e850b8c435a94a54ff9121c48a5792903e4cc2c200f5cc54cd48fc3cd51ae7a

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T11:03:28.089449Z digest=sha256:3c6f500002cc179d3f9e7d89fa62c9a57325217e1d3eb4969b096d43c4ebf3b3

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T05:49:52.864722Z digest=sha256:44a63179e02c1933183b91a5fe97fadb64832e6cefd5a77d51a53cf9347c65dd

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T09:51:38.704274Z digest=sha256:cb8e646a68a414d6ad771ef5d48fe739a86e344c5ca4cb07c0cbda67207bbde9

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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verified exact
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T16:49:54.542437Z digest=sha256:fedd389f46687b0c6660a3ce8549f1547f537fd1676f415d2fbfef29c85c19c1

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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metadata mismatch
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T05:11:57.184620Z digest=sha256:dc43ce6a9056024d529df9992810650e772ed37b2f0a462347f9e54c7557e042

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T12:49:18.671971Z digest=sha256:a1f53cb5ea21ea59875a0dd75438d4d3c89a7a2de18093077f1ba629024dce2f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T07:55:11.088587Z digest=sha256:cd44346be04d916a2f9b6f9c9e3211f5c78826e9829575831e4a87cb1d41178b

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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metadata mismatch
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T06:39:02.277629Z digest=sha256:4ff19339922d81e78d4d1fb2eef50fcd4801d6b15f8fae922b8f75cadfb572f0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T08:32:32.410473Z digest=sha256:6ac68f7b768a90e9bb13964cd14e9de0515343c3a447db1fad3c985fd2566b6d

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-29T14:26:07.597446Z digest=sha256:1eff932a400e28f586b579badf8338829cbd7d4d7bf2b228110b76799aa82941

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T11:15:53.211895Z digest=sha256:11101f1d9ec532a476b1bd3bc9bbfa16adbcbf26aca899c4234b8f1442526ec7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T08:25:09.062736Z digest=sha256:7a666452268e3b3375e8a0fe87e5ad8390d77ff0c9c9e432ee391c02f39ef9b9

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T13:52:15.860919Z digest=sha256:9108dbfac04d8e5e8406c1170775977b12604a5bd68b34a8e3c88a84a18e98f9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T10:41:37.290485Z digest=sha256:521c8cdaf7636a0006e1fee50c6f981616e7f5b6626fe961a3ae233dbf4c9d4b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T10:33:02.954683Z digest=sha256:a7d25b26eb44bf1a3ed1ec43edc444ecf24b290743298d6fe3afbdd773c92838

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T09:41:14.904868Z digest=sha256:c5a4c5bc43e47e6e367133ff4f9568e6884f75bdef54916ec943f7f82bc64e51

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T07:22:49.577516Z digest=sha256:eb859b56aaa5926bcc60f07d811c59c8979e6f863ab88ec22d43445181ea15b5

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T17:59:12.258042Z digest=sha256:059e2c198de83c8362007bc2bae3637db88617643e6a85cbceff101fc79ba89f

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T08:53:13.162764Z digest=sha256:bb9477604fcdb2fae84a58882e663f944297c90169127107a69d92c84952ff20

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T00:49:17.654830Z digest=sha256:ff0cfd395b468602d4f46e650eefccefc9dbcf34733f0a6783c36af7f94184e5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T06:06:46.108334Z digest=sha256:05fc47b4792c5ab9d5847c95f0e30fc9976c48d09c925dce065bdff0785052fc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-03T01:00:18.263578Z digest=sha256:ea90cbc4958498575bd468d404abee3dca9520009d1400f7d57e880b71276cbe

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