Paper Citation Record · LEDGER

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry

As of 9 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.13046.

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

pith.paper-citation-record.v1
2607.13046 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:05:28.776717Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation e9f31f08-a145-4f20-82ba-2f57fde1a9d8 · outbound

This paper cites Quantum machine learning.Nature, 549(7671):195–202, 2017.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Quantum machine learning.Nature, 549(7671):195–202, 2017

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:24.860059Z

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Observation c2a2ebe8-73cd-4197-b99e-0d59ac194ff6 · outbound

This paper cites Practical secure aggregation for privacy-preserving machine learning.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Practical secure aggregation for privacy-preserving machine learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:24.926729Z

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Observation 6a5fcf4d-e3a8-4117-98b4-a338fab7a799 · outbound

This paper cites Sampling using su (n) gauge equivariant flows.Physical Review D, 103(7):074504, 2021.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Sampling using su (n) gauge equivariant flows.Physical Review D, 103(7):074504, 2021

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:24.994177Z

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Observation db90ce56-9534-45ea-8110-eba1fa10d9d6 · outbound

This paper cites Learning equivariant maps with variational quantum circuits.Physical Review Applied, 23(4):044007, 2025.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Learning equivariant maps with variational quantum circuits.Physical Review Applied, 23(4):044007, 2025

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:25.123071Z

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Observation ff529882-05c2-464a-85b3-262664e10e35 · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:25.239797Z

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Observation dd076e63-c78a-4317-a538-18dd28c01dd8 · outbound

This paper cites Geometric deep learning: going beyond euclidean data.IEEE Signal Processing Magazine, 34(4):18–42, 2017.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Geometric deep learning: going beyond euclidean data.IEEE Signal Processing Magazine, 34(4):18–42, 2017

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:25.365756Z

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Observation 8f5dfb92-c162-4120-a9b6-43a7b4e3e9a7 · outbound

This paper cites Ipguard: Protecting intellectual property of deep neural networks via fingerprinting the classification boundary.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Ipguard: Protecting intellectual property of deep neural networks via fingerprinting the classification boundary

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:25.452668Z

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Observation 21f6c747-46d2-487d-bdd0-3430a9349459 · outbound

This paper cites Variational quan- tum algorithms.Nature Reviews Physics, 3(9):625–644, 2021.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Variational quan- tum algorithms.Nature Reviews Physics, 3(9):625–644, 2021

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:25.596402Z

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Observation f1224535-846a-46ec-a9c9-906397868f0b · outbound

This paper cites Digital image steganog- raphy: Survey and analysis of current methods.Signal processing, 90(3):727–752, 2010.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Digital image steganog- raphy: Survey and analysis of current methods.Signal processing, 90(3):727–752, 2010

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:25.745747Z

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Observation e722528f-0db3-4fe5-8e89-7fd5a7eb4624 · outbound

This paper cites Group equivariant convolutional networks.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Group equivariant convolutional networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:25.906500Z

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Observation c572d949-bb71-4e6c-a88d-8fbcb32444ca · outbound

This paper cites Spherical CNNs.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Spherical CNNs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.061702Z

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Observation cea406e8-de01-4e73-bb3b-d87e630d10e5 · outbound

This paper cites University of Florida, 2025.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry University of Florida, 2025

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.184283Z

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Observation 8973c483-cdf8-40c9-901e-79a11f473b6f · outbound

This paper cites Outlier Detection through Null Space Analysis of Neural Networks.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Outlier Detection through Null Space Analysis of Neural Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.290973Z

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Observation 72481f01-7974-474d-bea8-fdae1c3a216c · outbound

This paper cites Differential privacy: A survey of results.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Differential privacy: A survey of results

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.348423Z

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Observation 29923c79-63c0-4841-ac34-2305aebcae87 · outbound

This paper cites Calibrating noise to sensi- tivity in private data analysis.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Calibrating noise to sensi- tivity in private data analysis

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.424552Z

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Observation 6fe2b997-d190-4e98-a01f-b82fbae11284 · outbound

This paper cites Se (3)-transformers: 3d roto- translation equivariant attention networks.Advances in neural information processing systems, 33:1970–1981, 2020.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Se (3)-transformers: 3d roto- translation equivariant attention networks.Advances in neural information processing systems, 33:1970–1981, 2020

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.511407Z

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Observation 1a0bf100-be0e-4939-8cdf-2651d177d3dc · outbound

This paper cites Fully homomorphic encryption using ideal lattices.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Fully homomorphic encryption using ideal lattices

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.608797Z

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Observation d16827e0-9294-4377-a51f-f0247cf2307e · outbound

This paper cites Geometric deep learning and equivariant neural networks.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Geometric deep learning and equivariant neural networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.677973Z

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Observation 1e76b113-0427-4784-9cf1-fd05b7e02296 · outbound

This paper cites Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.765072Z

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Observation e26f9fe8-962d-458b-97b9-5c9bb458dcec · outbound

This paper cites an unresolved cited work.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Unresolved cited work

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.813426Z

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Observation a93bd72e-9e77-4926-953c-dcacb119336e · outbound

This paper cites Hall.Lie Groups, Lie Algebras, and Representations: An Elementary Introduction.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Hall.Lie Groups, Lie Algebras, and Representations: An Elementary Introduction

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:26.907632Z

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Observation 9ee55921-aa1f-44db-9c48-036e4352b52d · outbound

This paper cites Advances and open problems in federated learning.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Advances and open problems in federated learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:27.086853Z

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Observation 625418d0-dd2e-42b2-b6d3-0df63959a42d · outbound

This paper cites Equivariant flow-based sampling for lattice gauge theory.Physical Review Letters, 125(12):121601, 2020.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Equivariant flow-based sampling for lattice gauge theory.Physical Review Letters, 125(12):121601, 2020

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:27.252142Z

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Observation 04bb7f7a-280a-4ddc-9a52-6eea98af0770 · outbound

This paper cites On the generalization of equivariance and convolution in neural networks to the action of compact groups.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry On the generalization of equivariance and convolution in neural networks to the action of compact groups

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:27.372584Z

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Observation 4afb6156-c04a-4fd8-8f05-59ecd143b2fb · outbound

This paper cites A review of applications in federated learning.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry A review of applications in federated learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:27.524754Z

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Observation 1d2c02b2-41da-4ea1-b52d-4229e293179a · outbound

This paper cites Null space properties of neural networks with applications to image steganography.Mathematics, 13(21):3394, 2025.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Null space properties of neural networks with applications to image steganography.Mathematics, 13(21):3394, 2025

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:27.646431Z

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Observation 978fe0bd-1e7b-47c2-88a1-ed8580c8f086 · outbound

This paper cites Deep Neural Network Fingerprinting by Conferrable Adversarial Examples.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Deep Neural Network Fingerprinting by Conferrable Adversarial Examples

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:27.774368Z

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Observation 06bf7f1a-bfe5-41d2-862b-4c0c8bead38f · outbound

This paper cites Federated Learning: Opportunities and Challenges.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Federated Learning: Opportunities and Challenges

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:27.873595Z

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Observation 9f02c88d-9771-4713-997a-06a81a959b43 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Communication-efficient learning of deep networks from decentralized data

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:27.980905Z

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Observation 0a96633c-70cb-4ef9-9bf2-e7f102791e9c · outbound

This paper cites An overview of image steganography.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry An overview of image steganography

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.052560Z

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Observation fd211473-4246-40c3-b807-5e82f4463704 · outbound

This paper cites Finger- printing deep neural networks globally via universal adversarial perturbations.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Finger- printing deep neural networks globally via universal adversarial perturbations

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.131714Z

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Observation 55510c37-b54b-4f3e-8922-24e611c17a8d · outbound

This paper cites Quantum chemistry structures and properties of 134 kilo molecules.Scientific data, 1(1):1–7, 2014.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Quantum chemistry structures and properties of 134 kilo molecules.Scientific data, 1(1):1–7, 2014

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.212647Z

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Observation 656116d5-abcc-49ea-b175-938ef0507113 · outbound

This paper cites Protecting artificial intelligence ips: a survey of watermarking and fingerprinting for machine learning.CAAI Transactions on Intelligence Technology, 6(2):180–191, 2021.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Protecting artificial intelligence ips: a survey of watermarking and fingerprinting for machine learning.CAAI Transactions on Intelligence Technology, 6(2):180–191, 2021

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.263477Z

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Observation c83a0863-0859-4313-843a-616f6b846d72 · outbound

This paper cites Enumeration of 166 billion organic small molecules in the chemical universe database gdb-17.Journal of chemical information and modeling, 52(11):2864–2875, 2012.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Enumeration of 166 billion organic small molecules in the chemical universe database gdb-17.Journal of chemical information and modeling, 52(11):2864–2875, 2012

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.336412Z

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Observation db3d7d5c-1d26-4edc-9b20-9787f0b48022 · outbound

This paper cites Circuit-centric quantum classifiers.Physical Review A, 101(3):032308, 2020.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Circuit-centric quantum classifiers.Physical Review A, 101(3):032308, 2020

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.431993Z

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Observation b8f13a29-9108-4c1f-b878-6d6d854a000e · outbound

This paper cites Springer, 2012.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Springer, 2012

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.510966Z

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Observation 5250d1a7-ba1d-4550-af87-5476f4f39588 · outbound

This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.632636Z

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Observation 55d67890-9cca-450e-b1e8-456e86fa8fb9 · outbound

This paper cites A survey on federated learning: challenges and applications.International journal of machine learning and cybernetics, 14(2):513–535, 2023.

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry A survey on federated learning: challenges and applications.International journal of machine learning and cybernetics, 14(2):513–535, 2023

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T11:05:28.776717Z

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Pith citing papers

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