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Paper Citation Record · LEDGER

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning

As of 22 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2509.09742.

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

pith.paper-citation-record.v1
2509.09742 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:43:59.961007Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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Outbound references

Observation 21e41083-91be-4f41-8c4e-1b9544da9248 · outbound

This paper cites Deep learning with differential privacy.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Deep learning with differential privacy

Reference 1

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Observation 0f812787-4497-4a94-97cb-7d71284fe795 · outbound

This paper cites Collaborative learning of anomalies with privacy (clap) for unsupervised video anomaly detection: A new baseline.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Collaborative learning of anomalies with privacy (clap) for unsupervised video anomaly detection: A new baseline

Reference 2

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Observation f32f4ca2-d8d4-440c-b995-fa9c8112b6d4 · outbound

This paper cites Bayesian Framework for Gradient Leakage.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Bayesian Framework for Gradient Leakage

Reference 3

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Observation 7e9e9dfb-a7ef-49cb-848a-b88d14b1ce5f · outbound

This paper cites Practical Secure Aggregation for Federated Learning on User-Held Data.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Practical Secure Aggregation for Federated Learning on User-Held Data

Reference 4

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Observation 13c1c3b0-a486-4bf0-b76e-4e1cb10ae888 · outbound

This paper cites Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification

Reference 5

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Observation 4a9fe317-3837-4e10-b88e-4389b0d6412a · outbound

This paper cites Improved gradient leakage attack against compressed gradi- ents in federated learning.Neurocomputing, 608:128349, 2024.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Improved gradient leakage attack against compressed gradi- ents in federated learning.Neurocomputing, 608:128349, 2024

Reference 6

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Observation b381e7a4-907d-4bd5-85d8-a1aa5540d05d · outbound

This paper cites SoK: On Gradient Leakage in Federated Learning.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning SoK: On Gradient Leakage in Federated Learning

Reference 7

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Observation b71818c6-26bd-4ec5-8525-0301293a367c · outbound

This paper cites What is a good psnr value for image? https: //poletoparis.com/what-is-a-good-psnr-value-for-image/, 2022.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning What is a good psnr value for image? https: //poletoparis.com/what-is-a-good-psnr-value-for-image/, 2022

Reference 8

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Observation e1f3da12-4be8-4f96-87e8-1ea07a5c3087 · outbound

This paper cites Inverting gradients-how easy is it to break privacy in fed- erated learning?Advances in Neural Information Processing Systems, 33:16937–16947, 2020.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Inverting gradients-how easy is it to break privacy in fed- erated learning?Advances in Neural Information Processing Systems, 33:16937–16947, 2020

Reference 9

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Observation 1992d6e4-0ec0-4d60-a00c-26d05ce22643 · outbound

This paper cites A new federated learning framework against gradient inversion attacks.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning A new federated learning framework against gradient inversion attacks

Reference 10

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Observation ab72ed89-eb2b-42fb-ab54-638d575e1466 · outbound

This paper cites Deep residual learning for image recognition.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Deep residual learning for image recognition

Reference 11

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Observation 82442579-1812-4708-ba95-9de4574434c0 · outbound

This paper cites Evaluating gradient inversion attacks and defenses in federated learning.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Evaluating gradient inversion attacks and defenses in federated learning

Reference 12

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Observation fc0c733d-07e8-47fd-9b0a-749d7991ffa1 · outbound

This paper cites Instahide: Instance-hiding schemes for private distributed learning.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Instahide: Instance-hiding schemes for private distributed learning

Reference 13

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Observation 1cd0e73f-d1f5-4c3c-ba65-aecf13fa23a4 · outbound

This paper cites Plotneuralnet.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Plotneuralnet

Reference 14

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Observation ea484f66-3faa-4294-8599-2e85a6a5a422 · outbound

This paper cites Gradient inversion with generative image prior.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Gradient inversion with generative image prior

Reference 15

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Observation c3e9705e-b81f-466e-a01a-c3727efeec95 · outbound

This paper cites Cafe: Catastrophic data leakage in vertical federated learning.Advances in Neural Information Processing Systems, 34:994–1006, 2021.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Cafe: Catastrophic data leakage in vertical federated learning.Advances in Neural Information Processing Systems, 34:994–1006, 2021

Reference 16

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Observation 59faa6d0-4028-4248-9e88-3754e084ac0c · outbound

This paper cites FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning

Reference 17

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Observation dd7d05cc-84c3-4eed-bb5f-24fa7ce6c288 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Adam: A Method for Stochastic Optimization

Reference 18

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Observation d2e610ae-54fc-4e7e-910b-a923710d2493 · outbound

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

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Learning multiple layers of features from tiny images

Reference 19

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Observation 8e1e7bb8-3ad5-49db-8ad9-3be53e9c6a0d · outbound

This paper cites an unresolved cited work.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Unresolved cited work

Reference 20

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Observation 0c823262-3a2d-4047-b1f1-a1ab58d49551 · outbound

This paper cites Gradient disaggregation: Breaking privacy in federated learning by reconstructing the user participant matrix.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Gradient disaggregation: Breaking privacy in federated learning by reconstructing the user participant matrix

Reference 21

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Observation 6eead534-abda-4678-8b53-071e0815eea2 · outbound

This paper cites Gradient-based learning applied to document recognition.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Gradient-based learning applied to document recognition

Reference 22

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Observation 41515737-fdab-4dc5-9b77-63b209ab5850 · outbound

This paper cites Deep leakage from gradients in multiple-label medical image classification.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Deep leakage from gradients in multiple-label medical image classification

Reference 23

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Observation fd074321-a778-4a82-ab25-96f9d8861c70 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Pytorch: An imperative style, high-performance deep learning library

Reference 24

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Observation b9c67d57-c6d6-4a31-8260-79be1b2fdf85 · outbound

This paper cites Privacy-preserving deep learning via additively homo- morphic encryption.IEEE Transactions on Information Forensics and Security, 13(5):1333–1345, 2018.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Privacy-preserving deep learning via additively homo- morphic encryption.IEEE Transactions on Information Forensics and Security, 13(5):1333–1345, 2018

Reference 25

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Observation ffcf379f-0193-4a23-88ea-b3c459920a25 · outbound

This paper cites On the Convergence of Adam and Beyond.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning On the Convergence of Adam and Beyond

Reference 26

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Observation 545dec65-2fb0-4663-b7ad-1762e6eb143f · outbound

This paper cites Dropout is not all you need to prevent gradient leakage.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Dropout is not all you need to prevent gradient leakage

Reference 27

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Observation a9c20c28-371b-4421-b679-f78e716e4bac · outbound

This paper cites Real-world anomaly detection in surveillance videos.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Real-world anomaly detection in surveillance videos

Reference 28

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Observation 4bb1f400-244d-4172-ab5e-e45544367e5e · outbound

This paper cites On the convergence proof of amsgrad and a new version.IEEE Access, 7:61706–61716, 2019.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning On the convergence proof of amsgrad and a new version.IEEE Access, 7:61706–61716, 2019

Reference 29

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Observation ebe3671a-b32e-4305-879e-b8edf786f9b3 · outbound

This paper cites TabLeak: Tabular Data Leakage in Federated Learning.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning TabLeak: Tabular Data Leakage in Federated Learning

Reference 30

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Observation 23cc0bc8-b105-491e-8761-5e589404d8b0 · outbound

This paper cites Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems

Reference 31

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Observation 1d5c9f01-0484-4d9f-b3f9-2056d5c6b2bd · outbound

This paper cites Real-esrgan: Training real-world blind super-resolution with pure synthetic data.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Real-esrgan: Training real-world blind super-resolution with pure synthetic data

Reference 32

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Observation e2da10a3-25cc-4ad7-a24b-1c009faec132 · outbound

This paper cites SAPAG: A Self-Adaptive Privacy Attack From Gradients.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning SAPAG: A Self-Adaptive Privacy Attack From Gradients

Reference 33

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Observation de46572c-0fbf-4fb3-bbd1-b4c218caf5f0 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Image quality assessment: from error visibility to structural similarity

Reference 34

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Observation cd7ae4d8-7a5c-4ec1-aab3-6604de4bca2e · outbound

This paper cites A framework for evaluating client privacy leakages in federated learning.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning A framework for evaluating client privacy leakages in federated learning

Reference 35

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Observation 986fc633-b198-4d96-a364-fadbb82d6f8b · outbound

This paper cites Deep learning for video classification and captioning.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Deep learning for video classification and captioning

Reference 36

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Observation 034e62fb-ff67-4676-a158-e27ec1a5bc66 · outbound

This paper cites Revisiting gradient pruning: A dual realization for defending against gradient attacks.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Revisiting gradient pruning: A dual realization for defending against gradient attacks

Reference 37

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source=pdf_text observed=2026-08-04T19:43:59.875186Z digest=sha256:5fae7c6d1d357891f0fa5802a9907de1376c016a0355948b42aa83592e8356ca

Observation 7ea02892-40ab-4e8d-a78f-ea6ee8774068 · outbound

This paper cites LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning

Reference 38

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source=pdf_text observed=2026-08-04T19:43:59.936496Z digest=sha256:36ab0949ac8b948c2a957a47f40ba722cacb483dbd1204d2465f21eab68896ff

Observation 74b9d875-2816-45d4-b3b6-27a188656d47 · outbound

This paper cites Learning texture transformer network for image super-resolution.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Learning texture transformer network for image super-resolution

Reference 39

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source=pdf_text observed=2026-08-04T19:43:59.939959Z digest=sha256:0be5550ce73f68cebb1c2d97b067daae2b9017c08bae82463cb8a9cddea823f7

Observation af6759a1-c7fd-42ae-a1c4-045b187a2772 · outbound

This paper cites See through gradients: Image batch recovery via gradinversion.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning See through gradients: Image batch recovery via gradinversion

Reference 40

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source=pdf_text observed=2026-08-04T19:43:59.942847Z digest=sha256:228ea54d3022fbbceb972ec8af15c9755af6b77f12f12340f2c7be0eac69db88

Observation 865bef7c-e5af-4143-8994-6164b7e9eb84 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning mixup: Beyond Empirical Risk Minimization

Reference 41

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source=pdf_text observed=2026-08-04T19:43:59.945615Z digest=sha256:6d44a0480be17e0a8c983719056179dfd662d79961789cd5f6630ec85bc73882

Observation 2fa7eeb0-be68-4cf3-a34c-b83b51439ae8 · outbound

This paper cites CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling

Reference 42

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source=pdf_text observed=2026-08-04T19:43:59.948491Z digest=sha256:bcc941e35298a49edf30d87dce13d2f3ed42cd484b3fd2213a43e0f7eb5e21ae

Observation d6caf467-984a-4021-8203-b373ac4aa307 · outbound

This paper cites A Survey on Gradient Inversion: Attacks, Defenses and Future Directions.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning A Survey on Gradient Inversion: Attacks, Defenses and Future Directions

Reference 43

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source=pdf_text observed=2026-08-04T19:43:59.951934Z digest=sha256:7df2eb2a529f8e56ea838f2f284a80284d5be1d59398d3ab64b57a92532af528

Observation e4cd18d0-5e29-4f00-80fc-fe3627baa527 · outbound

This paper cites iDLG: Improved Deep Leakage from Gradients.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning iDLG: Improved Deep Leakage from Gradients

Reference 44

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source=pdf_text observed=2026-08-04T19:43:59.954962Z digest=sha256:e76db8248692b1b91b3820106902bbfca4467a9eedf7c9b7aeabdf73fbae79fe

Observation e9652ce0-db62-48f0-8105-a53bd3ca5d4c · outbound

This paper cites R-GAP: Recursive Gradient Attack on Privacy.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning R-GAP: Recursive Gradient Attack on Privacy

Reference 45

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source=pdf_text observed=2026-08-04T19:43:59.958179Z digest=sha256:f6db9acffdc631d67786f5bc57547d42fdc2337909ffb9367e37eec2d94b1dfc

Observation 86714b26-16b5-4d25-bd8d-01c7befb6e09 · outbound

This paper cites Deep leakage from gradients.

Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Deep leakage from gradients

Reference 46

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source=pdf_text observed=2026-08-04T19:43:59.961007Z digest=sha256:8c155087465406be72876cc72545c74a40ef969b4d833b6299d8ca546c646069

Pith citing papers

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