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Paper Citation Record · LEDGER

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models

As of 21 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.15084.

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

pith.paper-citation-record.v1
2607.15084 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T00:17:40.169998Z

measured 38 of 38 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation 0269214a-3c43-4174-af43-f69a2b184250 · outbound

This paper cites Abadi, A.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Abadi, A

Reference 1

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Observation 15d75e97-ea0a-409e-8852-1464f9d404e4 · outbound

This paper cites an unresolved cited work.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 2

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Observation ebcf248a-9733-48ea-9825-ddd262beafed · outbound

This paper cites Banerjee, I.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Banerjee, I

Reference 3

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Observation 3463f26a-9e88-452e-8a73-abf491d115fc · outbound

This paper cites Bourtoule, V.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Bourtoule, V

Reference 4

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Observation ab0f0d36-4288-4d2e-998f-b3570d470c80 · outbound

This paper cites Carlini, S.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Carlini, S

Reference 5

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Observation aa212c85-b218-4259-bb61-c4dcc485acdb · outbound

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 6

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 7

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Observation 491566f5-3474-4ea6-bae2-6b0d588bd714 · outbound

This paper cites DeAlcala, G.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models DeAlcala, G

Reference 8

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Observation 3eb9d0f0-a7fd-4754-947e-de552715fb9b · outbound

This paper cites DeAlcala, A.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models DeAlcala, A

Reference 9

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 10

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Observation 766a3f72-95ef-4e85-ae2d-4870c837550b · outbound

This paper cites Dosovitskiy, L.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Dosovitskiy, L

Reference 11

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Observation e8ddae1e-aba1-46f5-8a08-c61fa4055672 · outbound

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 12

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Observation cc2d617a-ddf3-4aeb-963e-d5cdd28e99b9 · outbound

This paper cites Fredrikson, S.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Fredrikson, S

Reference 13

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Observation 41fc75cc-bcb3-4e27-9317-94770e853f94 · outbound

This paper cites Official Journal of the European Union, L 119, 1–88, 2016.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Official Journal of the European Union, L 119, 1–88, 2016

Reference 14

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Observation 9d81002d-7260-4e19-9040-4d712f1a912c · outbound

This paper cites Golatkar, A.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Golatkar, A

Reference 15

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 16

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Observation 2da367f5-2303-49d3-acf9-550e4d668151 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Distilling the Knowledge in a Neural Network

Reference 17

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 18

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 19

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Observation 9c92d3bd-7f77-4e89-9f78-de29fc6749fb · outbound

This paper cites Inference Attacks Against Face Recognition Model without Classification Layers.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Inference Attacks Against Face Recognition Model without Classification Layers

Reference 20

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Observation 105ef6fa-4768-455d-bb43-7d02331234bc · outbound

This paper cites Knoche, S.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Knoche, S

Reference 21

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Observation 6f81873d-2650-4c87-a5d1-d297ef7e38c9 · outbound

This paper cites User-Level Membership Inference Attack against Metric Embedding Learning.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models User-Level Membership Inference Attack against Metric Embedding Learning

Reference 22

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 23

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Observation ad0a87ff-eaa9-4f9d-b4bc-26563950ad48 · outbound

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Mancera, D

Reference 24

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 25

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

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This paper cites Moschoglou, A.

Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Moschoglou, A

Reference 27

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Rezaei and X

Reference 28

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Salem, Y

Reference 29

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Sengupta, J

Reference 30

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Shokri, M

Reference 31

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Touvron, M

Reference 32

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Zheng and W

Reference 35

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 2021

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Quantifying Training Membership Information in the Hyperspherical Embedding Geometry of Face Recognition Models Unresolved cited work

Reference 4699

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Pith citing papers

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