CrediBench: Building Web-Scale Network Datasets for Information Integrity | Paper Citation Record

Observation 2c2c4d93-2ef4-4357-b55a-fd7aa97666b3 · outbound

This paper cites Digital format description, Library of Congress,.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Digital format description, Library of Congress,

Reference 1

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This paper cites an unresolved cited work.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Unresolved cited work

Reference 2

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Observation 443e46b3-e981-4081-a4b6-4d8136ed0a92 · outbound

This paper cites The Surprising Power of Graph Neural Networks with Random Node Initialization.

CrediBench: Building Web-Scale Network Datasets for Information Integrity The Surprising Power of Graph Neural Networks with Random Node Initialization

Reference 3

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Observation 7f8953da-d2b0-49a0-88ae-bb89b9a64d1f · outbound

This paper cites GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data.

CrediBench: Building Web-Scale Network Datasets for Information Integrity GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data

Reference 4

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Observation 5ebb885d-d58d-4971-b4e8-2987d807c34d · outbound

This paper cites Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks

Reference 5

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Observation cc036e29-8d55-497c-bba6-b90ee01d3dcf · outbound

This paper cites The CRAAP Test.LOEX Quarterly, 2004.

CrediBench: Building Web-Scale Network Datasets for Information Integrity The CRAAP Test.LOEX Quarterly, 2004

Reference 6

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Observation c52f9b6f-3a36-4c46-a15e-88aa28e25eb5 · outbound

This paper cites DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts.

CrediBench: Building Web-Scale Network Datasets for Information Integrity DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts

Reference 7

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Observation e1b8978a-f8f7-4756-bbc6-07e290f7302f · outbound

This paper cites The Anatomy of a Large-Scale Hypertextual Web Search Engine.Comput.

CrediBench: Building Web-Scale Network Datasets for Information Integrity The Anatomy of a Large-Scale Hypertextual Web Search Engine.Comput

Reference 8

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Observation 80c65396-19bf-41b7-9a88-898c7a57d5c6 · outbound

This paper cites How Attentive are Graph Attention Networks? In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022.

CrediBench: Building Web-Scale Network Datasets for Information Integrity How Attentive are Graph Attention Networks? In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022

Reference 9

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Observation 1f1e2e33-7693-45fb-af8c-da1365d334a9 · outbound

This paper cites Information credibility on twitter.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Information credibility on twitter

Reference 10

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Observation 090da498-5e3e-4273-b01a-904cc4fe3e99 · outbound

This paper cites SIFT (The Four Moves).Hapgood, 2019.

CrediBench: Building Web-Scale Network Datasets for Information Integrity SIFT (The Four Moves).Hapgood, 2019

Reference 11

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Observation 13b18dbe-18b2-4012-894c-e2bd17625752 · outbound

This paper cites Can LLM-Generated Misinformation Be Detected? InThe Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11,.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Can LLM-Generated Misinformation Be Detected? InThe Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:06.466833Z

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Observation 5edc33b9-bb26-4c9a-bd1f-43325d8fc288 · outbound

This paper cites Combating misinformation in the age of LLMs: Opportunities and challenges.AI Mag., 45(3):354–368, 2024.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Combating misinformation in the age of LLMs: Opportunities and challenges.AI Mag., 45(3):354–368, 2024

Reference 13

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Observation 0e598735-5683-41d0-968c-f4e572d8f704 · outbound

This paper cites URLhttps://openreview.net/forum?id=ccxD4mtkTU.

CrediBench: Building Web-Scale Network Datasets for Information Integrity URLhttps://openreview.net/forum?id=ccxD4mtkTU

Reference 14

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Observation 427c52ea-db79-4403-8957-61744aaad16a · outbound

This paper cites Common Crawl PySpark Repository.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Common Crawl PySpark Repository

Reference 15

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Observation a5cdeef9-5c6b-472a-8829-89e3fd653659 · outbound

This paper cites Linguistic feature based learning model for fake news detection and classification.Expert Syst.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Linguistic feature based learning model for fake news detection and classification.Expert Syst

Reference 16

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Observation 07be78f4-4027-4b38-976e-9b2f0002a8c3 · outbound

This paper cites December 2024 Crawl Archive Now Available, 2025.

CrediBench: Building Web-Scale Network Datasets for Information Integrity December 2024 Crawl Archive Now Available, 2025

Reference 17

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Observation 2869d074-2b2f-4ad2-9bd8-028b02f8bd4c · outbound

This paper cites Common Crawl Web Graphs, 2025.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Common Crawl Web Graphs, 2025

Reference 18

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Observation e0ac3319-8a0a-4542-bd43-85297dc0ec81 · outbound

This paper cites an unresolved cited work.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Unresolved cited work

Reference 19

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Observation 8d4b96bf-4a55-4828-b843-a71323dd5d4a · outbound

This paper cites Global Risks Report 2025, Jan.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Global Risks Report 2025, Jan

Reference 20

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Observation 410ac227-6479-4abd-bae4-f32af99f8d63 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Fast Graph Representation Learning with PyTorch Geometric

Reference 21

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Observation a4a0b305-23d7-45ee-82be-342173bc4ce9 · outbound

This paper cites Infodemiology: the epidemiology of (mis)information.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Infodemiology: the epidemiology of (mis)information

Reference 22

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Observation cb0f6e6b-fdf6-499f-abdd-040ce686ba92 · outbound

This paper cites TweetCred: Real- Time Credibility Assessment of Content on Twitter.

CrediBench: Building Web-Scale Network Datasets for Information Integrity TweetCred: Real- Time Credibility Assessment of Content on Twitter

Reference 23

Resolution: verified exact; doi, observed 2026-08-04T14:53:30.542866Z

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Observation d6988b90-b44a-4bc0-8b5c-bdad909a962e · outbound

This paper cites PyG 2.0: Scalable Learning on Real World Graphs.

CrediBench: Building Web-Scale Network Datasets for Information Integrity PyG 2.0: Scalable Learning on Real World Graphs

Reference 24

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Observation e3298cf3-d359-4e14-964b-a2efb7a40d65 · outbound

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

CrediBench: Building Web-Scale Network Datasets for Information Integrity Hamilton, Zhitao Ying, and Jure Leskovec

Reference 25

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Observation 7aab47bd-4a60-4671-b2fc-0cf1aa171ff5 · outbound

This paper cites Compare to the Knowledge: Graph Neural Fake News Detection with External Knowledge.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Compare to the Knowledge: Graph Neural Fake News Detection with External Knowledge

Reference 26

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Observation 52293cf5-457e-49fe-b7f9-6ab023c5d086 · outbound

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CrediBench: Building Web-Scale Network Datasets for Information Integrity Unresolved cited work

Reference 27

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Observation 1eca7c90-6bfe-4b91-bbc7-1215731c1b71 · outbound

This paper cites FakeBERT: Fake news detection in social media with a BERT-based deep learning approach.Multim.

CrediBench: Building Web-Scale Network Datasets for Information Integrity FakeBERT: Fake news detection in social media with a BERT-based deep learning approach.Multim

Reference 28

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Observation d4c230e9-a298-4366-b414-5b87bbb98f9e · outbound

This paper cites Representation learning for dynamic graphs: A survey.J.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Representation learning for dynamic graphs: A survey.J

Reference 29

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Observation 14e0ae75-5d80-4fc9-abf1-e05ce7d32e05 · outbound

This paper cites Disinformation Detection: An Evolving Challenge in the Age of LLMs.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Disinformation Detection: An Evolving Challenge in the Age of LLMs

Reference 30

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Observation 99ea3470-771e-4683-92ff-2a2c15de0035 · outbound

This paper cites Kipf and Max Welling.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Kipf and Max Welling

Reference 31

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Observation 02639b68-57c2-40e5-ae98-6808a140d298 · outbound

This paper cites AMFB: Attention based multimodal Factorized Bilinear Pooling for multimodal Fake News Detection.Expert Syst.

CrediBench: Building Web-Scale Network Datasets for Information Integrity AMFB: Attention based multimodal Factorized Bilinear Pooling for multimodal Fake News Detection.Expert Syst

Reference 32

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Observation 5f2c3612-f1d7-4684-931a-3e46bdbbeaf7 · outbound

This paper cites Evaluating credibility of social media information: current challenges, research directions and practical criteria.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Evaluating credibility of social media information: current challenges, research directions and practical criteria

Reference 33

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Observation b2ecdbdf-5543-4eba-9254-e6412e1a3a38 · outbound

This paper cites A Decision-Based Heterogenous Graph Attention Network for Multi-Class Fake News Detection.

CrediBench: Building Web-Scale Network Datasets for Information Integrity A Decision-Based Heterogenous Graph Attention Network for Multi-Class Fake News Detection

Reference 34

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Observation 87a60aca-69ce-40c3-a874-8af66b903698 · outbound

This paper cites High level of correspondence across different news domain quality rating sets.PNAS Nexus, 2(9):pgad286, 09 2023.

CrediBench: Building Web-Scale Network Datasets for Information Integrity High level of correspondence across different news domain quality rating sets.PNAS Nexus, 2(9):pgad286, 09 2023

Reference 35

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Observation c539f317-f205-40ba-b80c-001dfaa1c54e · outbound

This paper cites Kakade, Prateek Jain, and Ali Farhadi.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Kakade, Prateek Jain, and Ali Farhadi

Reference 36

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Observation 021dea78-14dc-49a9-9851-4ba38830e0ea · outbound

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CrediBench: Building Web-Scale Network Datasets for Information Integrity Unresolved cited work

Reference 37

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Observation dbb79eed-fba2-4143-b8b8-2b4ea1f0135b · outbound

This paper cites A Decision-Based Heterogenous Graph Attention Network for Multi-Class Fake News Detection.

CrediBench: Building Web-Scale Network Datasets for Information Integrity A Decision-Based Heterogenous Graph Attention Network for Multi-Class Fake News Detection

Reference 38

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Observation 22906d17-695e-4865-a711-68bf43c66a19 · outbound

This paper cites Credibility in Context: An Analysis of Feature Distributions in Twitter.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Credibility in Context: An Analysis of Feature Distributions in Twitter

Reference 39

Resolution: verified exact; doi, observed 2026-08-04T14:53:30.172656Z

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Observation 26ec535a-cbe6-4ff3-8708-fadb02d5dfb5 · outbound

This paper cites Fake news, rumor, information pollution in social media and web: A contemporary survey of state-of-the-arts, challenges and opportunities.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Fake news, rumor, information pollution in social media and web: A contemporary survey of state-of-the-arts, challenges and opportunities

Reference 40

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Observation 6fe8e8fd-37d2-4c1b-990b-795e41af535f · outbound

This paper cites Cross-SEAN: A cross-stitch semi-supervised neural attention model for COVID- 19 fake news detection.Appl.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Cross-SEAN: A cross-stitch semi-supervised neural attention model for COVID- 19 fake news detection.Appl

Reference 41

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Observation 617a1dfd-7861-495e-b4f9-80aec35d15f6 · outbound

This paper cites Fake News Detection with Retrieval Augmented Generative Artificial Intelligence.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Fake News Detection with Retrieval Augmented Generative Artificial Intelligence

Reference 42

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Observation 76a33730-b8c7-4ee4-93dc-93203111d961 · outbound

This paper cites Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection

Reference 43

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Observation fea7b447-df84-4ecf-ac4f-52eb98f531e9 · outbound

This paper cites Web Credibility: Features Exploration and Credibility Prediction.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Web Credibility: Features Exploration and Credibility Prediction

Reference 44

Resolution: verified exact; doi, observed 2026-08-04T14:53:30.088867Z

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Observation c3130f8f-98d5-4066-92ec-9b1b76a060e6 · outbound

This paper cites Exploring Generalizability of Fine-Tuned Models for Fake News Detection.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Exploring Generalizability of Fine-Tuned Models for Fake News Detection

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:07.676924Z

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Observation 7fd4db6b-e00c-47b6-ba62-8fe47ac89e53 · outbound

This paper cites Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:07.665354Z

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Observation 6a64047a-7908-488e-85e5-7d76758fc9c9 · outbound

This paper cites Web Retrieval Agents for Evidence-Based Misinformation Detection.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Web Retrieval Agents for Evidence-Based Misinformation Detection

Reference 47

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Observation 29dd41ad-5a66-4c43-8691-e41f8cff68fe · outbound

This paper cites Graph Attention Networks.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Graph Attention Networks

Reference 48

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Observation 7a845deb-79fb-4414-9730-94af57d54daa · outbound

This paper cites CSI: A Hybrid Deep Model for Fake News Detection.

CrediBench: Building Web-Scale Network Datasets for Information Integrity CSI: A Hybrid Deep Model for Fake News Detection

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:07.673553Z

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Observation 7d805a59-bef4-4d19-8059-1881be72dd01 · outbound

This paper cites Information Credibility on Twitter in Emergency Situation.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Information Credibility on Twitter in Emergency Situation

Reference 50

Resolution: verified exact; doi, observed 2026-08-04T14:53:29.961986Z

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Observation ebfa40f1-fc30-4263-a082-da56967f1657 · outbound

This paper cites Qwen3 Technical Report.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Qwen3 Technical Report

Reference 51

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Observation e0569392-6916-4b9e-af29-16b6df99bcda · outbound

This paper cites Some Like it Hoax: Automated Fake News Detection in Social Networks.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Some Like it Hoax: Automated Fake News Detection in Social Networks

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:07.682394Z

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Observation a80de5ef-5378-48ef-bae5-1ec6f4f721a6 · outbound

This paper cites Fake news detection based on dual-channel graph convolutional attention network.J.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Fake news detection based on dual-channel graph convolutional attention network.J

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Resolution: verified exact; doi, observed 2026-08-04T14:53:29.849700Z

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Observation e9cea37f-99e1-4566-ad52-b734bd20313b · outbound

This paper cites Liar, Liar Pants on Fire.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Liar, Liar Pants on Fire

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This paper cites an unresolved cited work.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Unresolved cited work

Reference 58

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This paper cites doi: 10.1109/ICDM50108.2020.00054.

CrediBench: Building Web-Scale Network Datasets for Information Integrity doi: 10.1109/ICDM50108.2020.00054

Reference 461

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This paper cites URL https://doi.org/10.1109/ICDE48307.

CrediBench: Building Web-Scale Network Datasets for Information Integrity URL https://doi.org/10.1109/ICDE48307

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:07.702909Z

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Observation ac27de3e-a76d-4080-92db-d0daf17fdf1e · outbound

This paper cites URL https://doi.org/10.1109/CIC56439.

CrediBench: Building Web-Scale Network Datasets for Information Integrity URL https://doi.org/10.1109/CIC56439

Reference 2022

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Observation 190c5d2c-9063-49f4-a6de-3637afd75e68 · outbound

This paper cites an unresolved cited work.

CrediBench: Building Web-Scale Network Datasets for Information Integrity Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T14:50:06.328737Z

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Observation b9b27f0b-5b34-4cbd-9834-9b36212e1d7c · outbound

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CrediBench: Building Web-Scale Network Datasets for Information Integrity PyG 2.0: Scalable Learning on Real World Graphs

Reference 2025

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