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Paper Citation Record · LEDGER

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation

As of 22 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2603.17717.

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pith.paper-citation-record.v1
2603.17717 v4

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measured 33 of 33 reference resolution

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Outbound references

Reference 1

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This paper cites M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models.

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models

Reference 2

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This paper cites In: Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summa- rization.

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summa- rization

Reference 3

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Generating Radiology Reports via Memory-driven Transformer

Reference 4

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This paper cites IEEE Transactions on Medical Imaging (2025).

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation IEEE Transactions on Medical Imaging (2025)

Reference 5

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: International Conference on Medical Image Com- puting and Computer-Assisted Intervention

Reference 6

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This paper cites IEEE Journal of Biomedical and Health Informatics (2025).

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation IEEE Journal of Biomedical and Health Informatics (2025)

Reference 7

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This paper cites CoRR (2024).

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation CoRR (2024)

Reference 8

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This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 9

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation ICLR1(2), 3 (2022)

Reference 10

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: Findings of the Association for Computational Linguistics: ACL 2023

Reference 11

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This paper cites Radiology116(3), 527–532 (1975).

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Radiology116(3), 527–532 (1975)

Reference 12

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Unresolved cited work

Reference 13

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: Text sum- marization branches out

Reference 14

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: Findings of the Association for Computational Linguistics: ACL 2025

Reference 15

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Knowledge-Based Systems305, 112630 (2024)

Reference 16

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering

Reference 17

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Journal of Imag- ing Informatics in Medicine37(5), 2669–2687 (2024)

Reference 18

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics

Reference 19

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop

Reference 20

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation DDaTR: Dynamic Difference-aware Temporal Residual Network for Longitudinal Radiology Report Generation

Reference 21

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Expert Systems with Applications237, 121442 (2024)

Reference 22

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 23

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Meta-Radiology1(3), 100033 (2023)

Reference 24

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: International Conference on Medi- cal Image Computing and Computer-Assisted Intervention

Reference 25

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 26

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Nature Communications16(1), 7866 (2025)

Reference 27

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Radiology: Artificial Intelligence4(4), e210258 (2022)

Reference 28

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Enhancing Retrieval and Managing Retrieval: A Four-Module Synergy for Improved Quality and Efficiency in RAG Systems

Reference 29

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 30

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT Analysis

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation In: Findings of the Association for Computational Linguistics: EMNLP 2023

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Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation Large-Vocabulary Segmentation for Medical Images with Text Prompts

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