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Paper Citation Record · LEDGER

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection

As of 15 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:1908.07882.

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

pith.paper-citation-record.v1
1908.07882 v3

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:12:52.291460Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

  • verified exact1
  • verified fuzzy22
  • unresolved17
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81e38ff6-9086-4994-a2e7-70c439967f3e · outbound

This paper cites Wasserstein GAN.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Wasserstein GAN

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bf3ae81a-9b92-448d-9d84-aba154aee3b2 · outbound

This paper cites Generalization and equilibrium in generative adversarial nets (gans).

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Generalization and equilibrium in generative adversarial nets (gans)

Reference 2

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

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Observation 07d4b54e-c233-4483-baec-a68caaba3a7d · outbound

This paper cites Tenenbaum, William T.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Tenenbaum, William T

Reference 3

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

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Observation 7e7aab72-18ab-45e1-9dea-e6977c650970 · outbound

This paper cites Ritchie, and Nick Weston.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Ritchie, and Nick Weston

Reference 4

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

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Observation b8872112-d2d6-47f0-9e93-7026d4ec31f6 · outbound

This paper cites The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks

Reference 5

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Observation 20168476-03e7-430c-8640-6f7af2b7e1d7 · outbound

This paper cites Cartoongan: Generative adversarial networks for photo cartoonization.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Cartoongan: Generative adversarial networks for photo cartoonization

Reference 6

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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.

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Observation 0eb8c303-66ee-476f-a8f0-f028151d9095 · outbound

This paper cites Adaptive learning with robust generalization guarantees.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Adaptive learning with robust generalization guarantees

Reference 7

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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.

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Observation 0eb4c364-b431-46ea-9a5e-67a3e084dbda · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Imagenet: A large-scale hierarchical image database

Reference 8

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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.

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Observation fdadfc79-03f2-4a3e-b77d-fdf02bd548a7 · outbound

This paper cites Differential privacy.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Differential privacy

Reference 9

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Observation ae2ec441-2170-4ead-b586-ba1b60056d7f · outbound

This paper cites The algorithmic foundations of differential privacy.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection The algorithmic foundations of differential privacy

Reference 10

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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.

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Observation 3f887fcd-96ee-4d62-961d-5b8908c850f9 · outbound

This paper cites Generative adversarial nets.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Generative adversarial nets

Reference 11

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Observation e9091784-7c01-4829-acb4-899dfa16b938 · outbound

This paper cites Courville.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Courville

Reference 12

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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.

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Observation a143f60b-4641-4362-84ac-801ac6310d4b · outbound

This paper cites LOGAN: Membership Inference Attacks Against Generative Models.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection LOGAN: Membership Inference Attacks Against Generative Models

Reference 13

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source=pdf_text observed=2026-08-14T12:12:52.182509Z digest=sha256:dfa9e0e0599fb6f9ade1b74f480ac9ee4d73bab02f8e7aa5dd7c520a2a42dc2d

Observation 50a39bb2-b4de-4b92-b986-fbd1deaa6976 · outbound

This paper cites Bayesian modelling and monte carlo inference for GAN.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Bayesian modelling and monte carlo inference for GAN

Reference 14

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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.

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Observation d7e20cb6-2064-46c0-b879-0781bfdf2084 · outbound

This paper cites Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

Reference 15

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raw_fallback, observed 2026-08-14T12:12:52.632254Z

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.

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Observation a8bf33cf-3cd9-4fe6-8dd8-32454a12355c · outbound

This paper cites A Style-Based Generator Architecture for Generative Adversarial Networks.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection A Style-Based Generator Architecture for Generative Adversarial Networks

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 897b8e73-2a52-4786-865f-1d5d0b623a8d · outbound

This paper cites Kingma and Jimmy Ba.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Kingma and Jimmy Ba

Reference 17

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Source-reported events for the cited work

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Observation c101f77e-71f3-4e39-a292-1ff3ac5532a4 · outbound

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

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Learning multiple layers of features from tiny images

Reference 18

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source=pdf_text observed=2026-08-14T12:12:52.203057Z digest=sha256:0aecac034522fc3833d5fe5b5c9ec98c35fb188524fda2eee1ed3e9972e717ed

Observation f5c15932-705a-479f-82d9-27bb62ab056b · outbound

This paper cites Huang Erik Learned-Miller.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Huang Erik Learned-Miller

Reference 19

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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.

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Observation fbf47bab-d988-4a44-bb28-526e0902b46f · outbound

This paper cites Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, and Wenzhe Shi.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, and Wenzhe Shi

Reference 20

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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.

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Observation 6ed8a50e-3a8a-455c-b0c2-5154aab4305a · outbound

This paper cites an unresolved cited work.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Unresolved cited work

Reference 21

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

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Observation 32ea0e35-f96e-4800-ad26-cfa324fd877b · outbound

This paper cites Spectral normalization for generative adversarial networks.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Spectral normalization for generative adversarial networks

Reference 22

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Observation 696bc0d4-fd6e-43e8-8485-ad9d6fc8d4e0 · outbound

This paper cites Generalization bounds of SGLD for non-convex learning: Two theoretical viewpoints.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Generalization bounds of SGLD for non-convex learning: Two theoretical viewpoints

Reference 23

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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.

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Observation c4b93faa-bc77-4e99-92cd-7ce79e936820 · outbound

This paper cites f-gan: Training generative neural sam- plers using variational divergence minimization.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection f-gan: Training generative neural sam- plers using variational divergence minimization

Reference 24

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raw_fallback, observed 2026-08-14T12:12:52.547114Z

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.

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Observation dc1fccc3-a93a-485f-ac02-23c1840155b6 · outbound

This paper cites Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities

Reference 25

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Observation d3354ff8-d1f1-4d26-a670-06b048a9e044 · outbound

This paper cites Unsupervised representation learning with deep convolutional generative adversarial networks.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Unsupervised representation learning with deep convolutional generative adversarial networks

Reference 26

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raw_fallback, observed 2026-08-14T12:12:52.535811Z

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.

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Observation 12f64f0f-c62b-4693-9cde-086a856a52bb · outbound

This paper cites Bayesian GAN.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Bayesian GAN

Reference 27

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raw_fallback, observed 2026-08-14T12:12:52.523964Z

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.

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Observation 19cd7a1b-0629-4b32-973b-8927182578f6 · outbound

This paper cites Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen

Reference 28

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raw_fallback, observed 2026-08-14T12:12:52.511338Z

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.

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Observation 438afacb-e9c9-42ca-af9c-ca5484c921ea · outbound

This paper cites an unresolved cited work.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Unresolved cited work

Reference 29

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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.

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Observation 95dccc5f-0783-4dfe-ad19-d5fe13749004 · outbound

This paper cites Learnability, stability and uniform convergence.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Learnability, stability and uniform convergence

Reference 30

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raw_fallback, observed 2026-08-14T12:12:52.487485Z

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.

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Observation 9a778d63-972e-4a7f-869f-cb53e35e90d9 · outbound

This paper cites Membership inference attacks against machine learning models.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Membership inference attacks against machine learning models

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-14T12:12:52.475239Z

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.

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Observation f028185c-1aa8-4731-b010-0f0df81ca8b5 · outbound

This paper cites Towards Demystifying Membership Inference Attacks.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Towards Demystifying Membership Inference Attacks

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:12:52.261628Z digest=sha256:7be738330f5f0cdb91162c5edf3a10006d3dfcb88172e6b264ceea2a8e644da2

Observation 09ddffaa-49fe-44fe-910e-ecdf6757789a · outbound

This paper cites High-dimensional probability: An introduction with applications in data science, volume 47.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection High-dimensional probability: An introduction with applications in data science, volume 47

Reference 33

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no resolver link, observed 2026-08-14T12:12:52.265226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:12:52.265226Z digest=sha256:642cbd1e1069a8a564e78720b205e62854d3aa25d9982f352e1817c2c58b2ad1

Observation e7c0c852-0faa-40f3-817a-206a35ca9f61 · outbound

This paper cites Fienberg, and Alexander J.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Fienberg, and Alexander J

Reference 34

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raw_fallback, observed 2026-08-14T12:12:52.455873Z

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.

source=pdf_text observed=2026-08-14T12:12:52.269286Z digest=sha256:e135c99077cc3df9c32a4534b5a6dc6cc190728d9f2ff0d2828629703f0f811f

Observation 51c9d00f-3fb8-4c71-9344-23299ad94ea1 · outbound

This paper cites Fienberg.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Fienberg

Reference 35

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raw_fallback, observed 2026-08-14T12:12:52.445153Z

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.

source=pdf_text observed=2026-08-14T12:12:52.273044Z digest=sha256:a136554daa1184a6aae75bd30610fc199fd26f8cc8303b13d62171bb68ecec20

Observation 1b00177c-5879-439d-b12f-9f11ee16d2b5 · outbound

This paper cites SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution

Reference 36

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verified exact
local_arxiv, observed 2026-08-14T12:12:52.340859Z

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.

source=pdf_text observed=2026-08-14T12:12:52.277066Z digest=sha256:d33686863622b9bbbc4bc96938eb5a4d35368a181f6ca52be7481aba30796fb6

Observation f678b6a2-c1e5-4313-aa96-d34c2d8b9cf2 · outbound

This paper cites Privacy risk in machine learning: Analyzing the connection to overfitting.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Privacy risk in machine learning: Analyzing the connection to overfitting

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:12:52.433879Z

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.

source=pdf_text observed=2026-08-14T12:12:52.281591Z digest=sha256:4fb0769b7e1be59d26914e3ba84251703417d847dfce1b759e0fd903a6a38e2d

Observation 46c0abfb-c054-4ed8-95cd-d71e0791b3af · outbound

This paper cites Self-Attention Generative Adversarial Networks.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Self-Attention Generative Adversarial Networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-14T12:12:52.284867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:12:52.284867Z digest=sha256:faf40e78090169f8b33db4fd1cd63a1141ee557ebc4fdbefd94c7198d4aab378

Observation 71d8b77e-d437-4f47-87cd-415f0bdd43f0 · outbound

This paper cites an unresolved cited work.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-14T12:12:52.422199Z

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.

source=pdf_text observed=2026-08-14T12:12:52.288291Z digest=sha256:efc980c2cd20d84f64cf0f7a8602eadfa12a1aa05d37698b8403c4e7cbd1225d

Observation 6dfef60a-0472-40a7-b2f8-5ee52a5a87d0 · outbound

This paper cites an unresolved cited work.

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-14T12:12:52.410911Z

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.

source=pdf_text observed=2026-08-14T12:12:52.291460Z digest=sha256:8002570b2de3e734e5f28dad55c4a0c30a6866bf69fd8ddb4eb7216cbed403f2

Pith citing papers

No inbound Pith citation observations are available.