Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning | Paper Citation Record

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This paper cites Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising

Reference 1

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This paper cites McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth

Reference 2

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This paper cites Secureboost: A lossless federated learning framework, 2021.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Secureboost: A lossless federated learning framework, 2021

Reference 3

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale, 2021.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning An image is worth 16x16 words: Transformers for image recognition at scale, 2021

Reference 4

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Observation 282b5179-779e-4ea3-b50a-0f1cdc4f1996 · outbound

This paper cites Local model reconstruction attacks in federated learning and their uses, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Local model reconstruction attacks in federated learning and their uses, 2023

Reference 5

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Observation fe441d1b-e89b-4863-81ff-9cbb58b7b486 · outbound

This paper cites The algorithmic foundations of differential privacy.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning The algorithmic foundations of differential privacy

Reference 6

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Observation 7bc78367-e2d1-4290-baaf-8497f73fba07 · outbound

This paper cites Calibrating noise to sensitivity in private data analysis.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Calibrating noise to sensitivity in private data analysis

Reference 7

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This paper cites A simple convergence proof of adam and adagrad, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning A simple convergence proof of adam and adagrad, 2022

Reference 8

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Observation 5ece9260-915a-4417-9a52-65ce8c2dbddc · outbound

This paper cites Splitguard: Detecting and mitigating training-hijacking attacks in split learning.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Splitguard: Detecting and mitigating training-hijacking attacks in split learning

Reference 9

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This paper cites Ercument Ci- cek.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Ercument Ci- cek

Reference 10

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Observation 6f204e3c-4b09-44e6-bef6-4c51b66786b7 · outbound

This paper cites Ercüment Çiçek.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Ercüment Çiçek

Reference 11

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Observation dd0b9b13-deeb-412d-9a8a-3d5d62a2c749 · outbound

This paper cites Model inversion attacks that ex- ploit confidence information and basic countermeasures.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Model inversion attacks that ex- ploit confidence information and basic countermeasures

Reference 12

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Observation 614b50d9-2f80-48e1-b75d-bc91803df322 · outbound

This paper cites Zhu, Pingyi Hu, Ruixin Zhao, Yaru Jia, Peng Xu, Hai Jin, and Dongmei Zhang.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Zhu, Pingyi Hu, Ruixin Zhao, Yaru Jia, Peng Xu, Hai Jin, and Dongmei Zhang

Reference 13

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Observation f5ea251c-1e1c-4ab7-bd51-24f9d8b4529a · outbound

This paper cites Gunter, and Nikita Borisov.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Gunter, and Nikita Borisov

Reference 14

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Observation b6de116b-1e0c-42f5-9a40-4e996008e8c7 · outbound

This paper cites PCAT: Functionality and data stealing from split learning by Pseudo-Client attack.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning PCAT: Functionality and data stealing from split learning by Pseudo-Client attack

Reference 15

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Observation 177a3cfc-b5c7-49f3-a4e3-172219cc0e86 · outbound

This paper cites Inverting gradients – how easy is it to break privacy in federated learning?, 2020.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Inverting gradients – how easy is it to break privacy in federated learning?, 2020

Reference 16

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Observation a3865153-943b-4ae4-b27f-b058df2d5c63 · outbound

This paper cites Deep learning with label differential privacy, 2021.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Deep learning with label differential privacy, 2021

Reference 17

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This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio

Reference 18

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Observation b12fca69-0d46-4cf0-8ef0-b764c8ea4ef5 · outbound

This paper cites Generating sequences with recurrent neural networks, 2014.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Generating sequences with recurrent neural networks, 2014

Reference 19

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Observation fb4333b4-9bb1-4c49-bd5c-dcb7fe3b3dab · outbound

This paper cites Federated doubly stochastic kernel learning for vertically partitioned data, 2020.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Federated doubly stochastic kernel learning for vertically partitioned data, 2020

Reference 20

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Observation ed160e87-1d91-46e0-8d3b-a4cd96a64521 · outbound

This paper cites Fedpass: Privacy-preserving vertical federated deep learning with adaptive obfuscation, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Fedpass: Privacy-preserving vertical federated deep learning with adaptive obfuscation, 2023

Reference 21

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Observation b6536f9c-3396-4520-8381-7ab8e0c46ce4 · outbound

This paper cites Distributed learning of deep neural network over multiple agents, 2018.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Distributed learning of deep neural network over multiple agents, 2018

Reference 22

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Observation 4f7e2c6f-9e72-4c44-93c8-8fe502b271cb · outbound

This paper cites Recov- ering private text in federated learning of language models, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Recov- ering private text in federated learning of language models, 2022

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.270050Z

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Observation e46341c6-dc53-40ef-8688-d67944c48c6c · outbound

This paper cites Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption, 2017.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption, 2017

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.257341Z

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Observation 939be27e-782e-4986-8561-e6ee87e2dd8d · outbound

This paper cites Deep residual learning for image recognition, 2015.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Deep residual learning for image recognition, 2015

Reference 25

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Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 26

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This paper cites an unresolved cited work.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 27

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Observation ac8445cf-28ac-4ad6-9153-72c42a26b5ec · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.199174Z

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Observation 5fc276be-0d16-4405-a8b5-9478e9927bcc · outbound

This paper cites Is vertical logistic regression privacy-preserving? a comprehensive privacy analysis and beyond, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Is vertical logistic regression privacy-preserving? a comprehensive privacy analysis and beyond, 2022

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.187514Z

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Observation 751b4b41-4321-4c97-b00f-1c40d8a6610a · outbound

This paper cites Scope of validity of psnr in image/video quality assessment.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Scope of validity of psnr in image/video quality assessment

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.175899Z

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Observation 1a69c95f-1334-4986-bbfa-ff1f5a1c2209 · outbound

This paper cites Rethinking fid: Towards a better evaluation metric for image generation,.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Rethinking fid: Towards a better evaluation metric for image generation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.164453Z

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This paper cites Cafe: Catastrophic data leakage in vertical federated learning, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Cafe: Catastrophic data leakage in vertical federated learning, 2022

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.153124Z

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This paper cites Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Ar- jun Nitin Bhagoji, Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Ar- jun Nitin Bhagoji, Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.142099Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1647b9af-c4cf-40e0-abad-69d7d15fef49 · outbound

This paper cites Exploit: Extracting private labels in split learning, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Exploit: Extracting private labels in split learning, 2022

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.131318Z

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Observation a186433e-bf72-4439-a00d-4ae8edad85e6 · outbound

This paper cites Vertical federated learning: A structured literature review, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Vertical federated learning: A structured literature review, 2023

Reference 35

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Observation 57dabae2-4af1-4ad4-a2f2-72c233684bf5 · outbound

This paper cites Kingma and Jimmy Ba.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Kingma and Jimmy Ba

Reference 36

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This paper cites Brendan McMahan, Felix X.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Brendan McMahan, Felix X

Reference 37

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ffbbe82e-449a-4ed3-b3dd-4323edaaea55 · outbound

This paper cites Learning multiple layers of features from tiny images.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Learning multiple layers of features from tiny images

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.091444Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cb87fae0-106f-443d-9fbb-d2485046f13d · outbound

This paper cites Lecun, L.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Lecun, L

Reference 39

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Observation 0fd377dd-0acb-49c3-a433-f255a1f5193c · outbound

This paper cites Ressfl: A resistance transfer framework for defending model inversion attack in split federated learning.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Ressfl: A resistance transfer framework for defending model inversion attack in split federated learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.080231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5f5cfd7b-9d92-4c59-bc8a-43b49f44ea03 · outbound

This paper cites Model extraction attacks on split federated learning, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Model extraction attacks on split federated learning, 2023

Reference 41

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 03f0c9d6-be59-4a8c-8762-ef33c16c8e23 · outbound

This paper cites Label leakage and protection in two-party split learning, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Label leakage and protection in two-party split learning, 2022

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.058053Z

Source-reported events for the cited work

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Observation eb52511d-a779-4bda-9364-f8802bd365ae · outbound

This paper cites Federated optimization in heterogeneous networks, 2020.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Federated optimization in heterogeneous networks, 2020

Reference 43

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Observation b77c9244-f92b-4f0c-90f9-c1d52896d905 · outbound

This paper cites PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-11T14:46:12.394225Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a3bc3c99-71be-4c12-b55e-b3270936e6e5 · outbound

This paper cites Differentially private vertical federated clustering.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Differentially private vertical federated clustering

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.039681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0d916ece-e529-467b-b7dd-aada77c340d9 · outbound

This paper cites Loss landscapes and optimization in over-parameterized non-linear systems and neural networks.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Loss landscapes and optimization in over-parameterized non-linear systems and neural networks

Reference 46

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Observation 7ccdc5dd-8ac8-47d9-b353-e99e00d47594 · outbound

This paper cites Similarity-based label inference attack against training and inference of split learning.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Similarity-based label inference attack against training and inference of split learning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.685849Z

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Observation c3c79d82-afdb-42b2-b6d7-7d15abfb6a69 · outbound

This paper cites Batch label inference and replacement attacks in black-boxed vertical federated learning, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Batch label inference and replacement attacks in black-boxed vertical federated learning, 2022

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.027711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 236d1314-e6db-4aa8-b2e7-143308cbef2e · outbound

This paper cites Vertical federated learning: Concepts, advances, and challenges.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Vertical federated learning: Concepts, advances, and challenges

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.692727Z

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Observation 5ef919bf-3d2b-43a8-9c58-b790a1f86712 · outbound

This paper cites Feature inference attack on model predictions in vertical federated learning.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Feature inference attack on model predictions in vertical federated learning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.696397Z

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Observation ed939b6d-98e7-42f6-ae78-eda7c8980f55 · outbound

This paper cites Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Agüera y Arcas.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Agüera y Arcas

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.700330Z

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Observation b9e9c42d-9bb9-45cb-80b6-16b2e9eec0d1 · outbound

This paper cites Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-11T14:46:12.126543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e936be91-63c2-4199-adf3-a38a8ba643d2 · outbound

This paper cites Label-only model inversion attacks via knowledge transfer, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Label-only model inversion attacks via knowledge transfer, 2023

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:13.009241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f3ca3b91-c74c-4dfa-8bb8-96ed5f85b18c · outbound

This paper cites Re-thinking model inversion attacks against deep neural networks, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Re-thinking model inversion attacks against deep neural networks, 2023

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.997860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 43a21a28-446c-4f65-8cf6-16da8e105eff · outbound

This paper cites Pham, Khoa Doan, and Kok-Seng Wong.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Pham, Khoa Doan, and Kok-Seng Wong

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.985710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 65973798-9507-48ab-9e1b-eef196c849a0 · outbound

This paper cites Unleashing the tiger: Inference attacks on split learning, 2021.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unleashing the tiger: Inference attacks on split learning, 2021

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.974113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 380d68b5-2acd-48b1-80af-3d68f7b4152b · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.722867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e541ef9d-8ac6-4465-9448-4191e184e9f7 · outbound

This paper cites Full-Reference Image Quality Metrics.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Full-Reference Image Quality Metrics

Reference 58

Resolution: verified exact; doi, observed 2026-08-11T14:46:11.955687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3c00c01c-78d3-408c-8f7a-7a6c95acb256 · outbound

This paper cites Evaluating privacy leakage in split learning, 2024.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Evaluating privacy leakage in split learning, 2024

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.962670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 185add0c-b07d-4144-bdbd-ac4aac4d2e87 · outbound

This paper cites an unresolved cited work.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:46:12.951279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 84faf164-ff9f-49ef-813f-f4151056931d · outbound

This paper cites Victoria Luzón, Francisco Herrera, and Eugenio Martínez-Cámara.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Victoria Luzón, Francisco Herrera, and Eugenio Martínez-Cámara

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.736906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c733b35-4f82-4312-992f-c937d98aa46c · outbound

This paper cites Rudin, Stanley Osher, and Emad Fatemi.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Rudin, Stanley Osher, and Emad Fatemi

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.740336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9678cfe-effd-43c1-b18f-48f50826fc6d · outbound

This paper cites Stochastic gradient methods with preconditioned updates.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Stochastic gradient methods with preconditioned updates

Reference 63

Resolution: verified exact; doi, observed 2026-08-11T14:46:11.927175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a243b9f5-58e2-40cb-8560-380a88045865 · outbound

This paper cites Image quality assessment through fsim, ssim, mse and psnr—a comparative study.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Image quality assessment through fsim, ssim, mse and psnr—a comparative study

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.940682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 67261fdd-a9a0-4e5b-99ad-d1e87c61ea1c · outbound

This paper cites Membership inference attacks against machine learning models, 2017.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Membership inference attacks against machine learning models, 2017

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.755106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 062e6e63-3ec3-45b9-aeb5-39ee35c001a9 · outbound

This paper cites Smith, Shuang Song, and Abhradeep Thakurta.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Smith, Shuang Song, and Abhradeep Thakurta

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.910561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 07ab6222-122a-4e3c-9557-3526c6726c6b · outbound

This paper cites Defending against reconstruction attack in vertical federated learning, 2021.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Defending against reconstruction attack in vertical federated learning, 2021

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.898606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5d795486-7aea-4171-b0cf-13dda911dc43 · outbound

This paper cites Label leakage and protection from forward embedding in vertical federated learning, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Label leakage and protection from forward embedding in vertical federated learning, 2022

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.886962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 69f30bf8-f35f-4b18-a2fd-620e6c78e74d · outbound

This paper cites Privacy assessment on reconstructed images: Are existing evaluation metrics faithful to human perception?, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Privacy assessment on reconstructed images: Are existing evaluation metrics faithful to human perception?, 2023

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.875635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 109bb65e-bab6-459a-bf32-6fd81d0c38e9 · outbound

This paper cites an unresolved cited work.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:46:12.863672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8bb9f1b1-cb17-469e-9406-05ec6fceaf0f · outbound

This paper cites Mlp-mixer: An all-mlp architecture for vision, 2021.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Mlp-mixer: An all-mlp architecture for vision, 2021

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.852234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 80c7a9d6-00df-44d8-8341-1c46ee8f677d · outbound

This paper cites Federated or split? a performance and privacy analysis of hybrid split and federated learning architectures.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Federated or split? a performance and privacy analysis of hybrid split and federated learning architectures

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.782327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87e64770-1903-4aef-9cae-c1ea85b35f59 · outbound

This paper cites Nopeek: Informa- tion leakage reduction to share activations in distributed deep learning, 2020.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Nopeek: Informa- tion leakage reduction to share activations in distributed deep learning, 2020

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.841382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e84b88e1-c9f1-4b4b-accb-b408e70467d2 · outbound

This paper cites Feverless: Fast and secure vertical federated learning based on xgboost for decentralized labels.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Feverless: Fast and secure vertical federated learning based on xgboost for decentralized labels

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.789225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dc7be93-c760-4381-aaa5-e572429ce837 · outbound

This paper cites Vincent Poor.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Vincent Poor

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.830287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4fb284ab-e83d-46b6-bdc6-9b02aabc9cfb · outbound

This paper cites A universal image quality index.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning A universal image quality index

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.818246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 87f19723-5695-4b9c-af5d-a05102e57112 · outbound

This paper cites Vertical federated learning: Challenges, methodologies and experiments, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Vertical federated learning: Challenges, methodologies and experiments, 2022

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.805972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fb9001da-3fd3-49a0-8f85-00e2e2a18f11 · outbound

This paper cites an unresolved cited work.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.803678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf145b0b-3f5b-42be-91c1-e81f306f6131 · outbound

This paper cites Naughton.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Naughton

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.787784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 23a1f839-1903-4483-b5dc-12b80a746630 · outbound

This paper cites Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.810851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation baf41625-b4b8-4ce8-a16d-17a431b7b2a5 · outbound

This paper cites A survey on vertical federated learning: From a layered perspective, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning A survey on vertical federated learning: From a layered perspective, 2023

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.770067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 56d1ce18-8ee2-4ad2-8d05-2665592d9997 · outbound

This paper cites Federated machine learning: Concept and applications, 2019.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Federated machine learning: Concept and applications, 2019

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.759099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6669adbb-1808-4a06-a817-ce69d7e04986 · outbound

This paper cites Adversarial neural network inversion via auxiliary knowledge alignment, 2019.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Adversarial neural network inversion via auxiliary knowledge alignment, 2019

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.748366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f113170b-e9e2-464f-9eeb-05f0d70f46e1 · outbound

This paper cites Feature reconstruction attacks and countermeasures of dnn training in vertical federated learning, 2022.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Feature reconstruction attacks and countermeasures of dnn training in vertical federated learning, 2022

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.736593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 511a5c11-608d-498c-9743-eb34afe37e28 · outbound

This paper cites How to backdoor split learning.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning How to backdoor split learning

Reference 85

Resolution: malformed identifier; no resolver link, observed 2026-08-11T14:46:11.828772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7088e68a-08c9-416e-9fca-55660b6d5041 · outbound

This paper cites A survey of privacy threats and defense in vertical federated learning: From model life cycle perspective, 2024.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning A survey of privacy threats and defense in vertical federated learning: From model life cycle perspective, 2024

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.725249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cd388131-170c-4d17-b38d-b9457448764f · outbound

This paper cites Efros, Eli Shechtman, and Oliver Wang.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Efros, Eli Shechtman, and Oliver Wang

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.835747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a54e933-7d97-4bb7-9416-70d1fa6613e3 · outbound

This paper cites idlg: Improved deep leakage from gradients, 2020.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning idlg: Improved deep leakage from gradients, 2020

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.707094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1bb8e85d-745c-4976-b0bd-3e6b42ccadc2 · outbound

This paper cites Deep leakage from gradients, 2019.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Deep leakage from gradients, 2019

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.695143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c3c25539-5eae-4ea6-82b4-bf6a28d69503 · outbound

This paper cites Defending batch-level label inference and replacement attacks in vertical federated learning.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Defending batch-level label inference and replacement attacks in vertical federated learning

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.846464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acb8db78-2a95-45df-9a9f-0bd22b281710 · outbound

This paper cites Mutual information regularization for vertical federated learning, 2023.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Mutual information regularization for vertical federated learning, 2023

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.683423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation df3f9462-345a-4bc8-8a7a-183c7eae4aca · outbound

This paper cites an unresolved cited work.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:46:12.670727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 83e067d6-bc7e-457e-b896-f1101f48da53 · outbound

This paper cites kX i=1 Gfake i # . Hk+1 = XW k+1 = XW 1 − γXX ⊤.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning kX i=1 Gfake i # . Hk+1 = XW k+1 = XW 1 − γXX ⊤

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.657016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 279daee1-0842-404e-b8fa-fd71867b4a95 · outbound

This paper cites an unresolved cited work.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 97

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:46:12.646427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6a856cf1-cb7a-4d99-9a3a-7cb7fd8a8a16 · outbound

This paper cites neighbouring.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning neighbouring

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.634755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7032a6d7-c7e6-4037-bf65-095af2bf2299 · outbound

This paper cites All CNN-based models are listed in the original UnSplit and FSHA papers’ repositories 4 and 5.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning All CNN-based models are listed in the original UnSplit and FSHA papers’ repositories 4 and 5

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:46:12.623234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ec438411-16ac-456e-bd23-309eb8c9d729 · outbound

This paper cites an unresolved cited work.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:46:12.929486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 587ca74c-29f2-403f-b2f7-80e946a23b54 · outbound

This paper cites an unresolved cited work.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Unresolved cited work

Reference 2021

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:46:13.209775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 84c90158-7a76-4bf1-8e66-fe95dfdb117c · outbound

This paper cites Rethinking FID: Towards a Better Evaluation Metric for Image Generation.

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Rethinking FID: Towards a Better Evaluation Metric for Image Generation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T14:46:11.624273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers