Paper Citation Record · LEDGER

Tight Privacy Audit in One Run

As of 7 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 2 inbound Pith citation observations for arXiv:2509.08704.

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

pith.paper-citation-record.v1
2509.08704 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T20:29:12.832727Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T09:48:10.362600Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:48:03.222941Z

Reference resolution

34 of 34 outbound references displayed

verified exact0
verified fuzzy0
unresolved34
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8f618332-d87e-4b7a-8ec0-c22b8322b868 · outbound

This paper cites Deep learning with differential privacy.

Tight Privacy Audit in One Run Deep learning with differential privacy

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.741926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1df5e2e-1743-4bd3-b26d-9138f2330f55 · outbound

This paper cites Deciding differential privacy for programs with finite inputs and outputs.

Tight Privacy Audit in One Run Deciding differential privacy for programs with finite inputs and outputs

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.745815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db16e484-7958-42e1-a16c-957a67b96f8e · outbound

This paper cites Dp-finder: Finding differential privacy violations by sampling and optimization.

Tight Privacy Audit in One Run Dp-finder: Finding differential privacy violations by sampling and optimization

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.748834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e01e611c-4705-4da7-9464-2e61046c3d3b · outbound

This paper cites Dp-sniper: Black-box discovery of differential privacy vi- olations using classifiers.

Tight Privacy Audit in One Run Dp-sniper: Black-box discovery of differential privacy vi- olations using classifiers

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.751801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8bc1a1f-2307-4ce1-9c4e-6f9f866ecf00 · outbound

This paper cites Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model.

Tight Privacy Audit in One Run Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.754763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c82f6b5c-0a5e-4f52-acef-7a1cfdec0788 · outbound

This paper cites On the Privacy Properties of Variants on the Sparse Vector Technique.

Tight Privacy Audit in One Run On the Privacy Properties of Variants on the Sparse Vector Technique

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.757757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 129cd253-7eb4-46d8-bba7-5b643391db67 · outbound

This paper cites The use of confidence or fiducial limits illustrated in the case of the binomial.Biometrika, 26(4):404–413, 1934.

Tight Privacy Audit in One Run The use of confidence or fiducial limits illustrated in the case of the binomial.Biometrika, 26(4):404–413, 1934

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.761197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e7ca237-26ba-49dd-a64d-6f6efe507767 · outbound

This paper cites Gaussian differential privacy.Journal of the Royal Statistical Society, 2021.

Tight Privacy Audit in One Run Gaussian differential privacy.Journal of the Royal Statistical Society, 2021

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.763906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 703f0b22-d3bd-4c67-8248-3ba1580870b3 · outbound

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

Tight Privacy Audit in One Run Calibrating noise to sensitivity in private data analysis

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.766445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2c64922-db95-4f9d-ae4e-06d59a537277 · outbound

This paper cites On the complexity of differentially private data release: efficient algorithms and hardness results.

Tight Privacy Audit in One Run On the complexity of differentially private data release: efficient algorithms and hardness results

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.769139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ba018ea-7063-4ba2-bb5b-1c2788a85d57 · outbound

This paper cites The algorithmic foundations of differential privacy.Foundations and Trends® in Theoretical Computer Science, 9(3–4):211–407, 2014.

Tight Privacy Audit in One Run The algorithmic foundations of differential privacy.Foundations and Trends® in Theoretical Computer Science, 9(3–4):211–407, 2014

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.771813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5580d1a4-c54f-4c17-9815-10a60341f779 · outbound

This paper cites PhD thesis, State University of New York at Buffalo, 2020.

Tight Privacy Audit in One Run PhD thesis, State University of New York at Buffalo, 2020

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.774701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26db283d-1867-482c-921c-0ed325392420 · outbound

This paper cites Auditing dif- ferentially private machine learning: How private is private sgd?Ad- vances in Neural Information Processing Systems, 33:22205–22216, 2020.

Tight Privacy Audit in One Run Auditing dif- ferentially private machine learning: How private is private sgd?Ad- vances in Neural Information Processing Systems, 33:22205–22216, 2020

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.777135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd07bc5c-c981-4517-8082-c1c8e6253bac · outbound

This paper cites https://github.com/google/ jax/pull/3646.

Tight Privacy Audit in One Run https://github.com/google/ jax/pull/3646

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.779631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c480182-2467-4203-a4b0-686ef8fdb9fe · outbound

This paper cites A gen- eral framework for auditing differentially private machine learning.

Tight Privacy Audit in One Run A gen- eral framework for auditing differentially private machine learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.782210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2acaf33e-0b7f-4438-91ca-8edc11f4bd53 · outbound

This paper cites CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning.

Tight Privacy Audit in One Run CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.784641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecf3f8fe-276b-4313-93f7-9ec6aa1912a2 · outbound

This paper cites Auditing $f$-Differential Privacy in One Run.

Tight Privacy Audit in One Run Auditing $f$-Differential Privacy in One Run

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.787455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45a4d7da-7073-4925-bcdb-d8ffcc5b7e99 · outbound

This paper cites Antipodes of label differential privacy: Pate and alibi.

Tight Privacy Audit in One Run Antipodes of label differential privacy: Pate and alibi

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.790301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e570c3f-d043-4454-9660-67634d587fe8 · outbound

This paper cites On significance of the least significant bits for dif- ferential privacy.

Tight Privacy Audit in One Run On significance of the least significant bits for dif- ferential privacy

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.792845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab1300f6-1984-46a8-9ad5-166cbe939d18 · outbound

This paper cites R\'enyi Differential Privacy of the Sampled Gaussian Mechanism.

Tight Privacy Audit in One Run R\'enyi Differential Privacy of the Sampled Gaussian Mechanism

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.795378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55c83d18-1b7a-4f22-b914-8710457e7f12 · outbound

This paper cites Tight auditing of differentially private machine learning.

Tight Privacy Audit in One Run Tight auditing of differentially private machine learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.798279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aff35756-7556-4ab1-ab80-e6d3655ac789 · outbound

This paper cites Adversary instantiation: Lower bounds for differentially private machine learning.

Tight Privacy Audit in One Run Adversary instantiation: Lower bounds for differentially private machine learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.800824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc7dab67-2637-495a-8b88-44a435bd3c82 · outbound

This paper cites an unresolved cited work.

Tight Privacy Audit in One Run Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.803444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46795b8f-6b97-4176-9e51-0540b3964a0a · outbound

This paper cites https://www.flowhunt.io/glossary/cost-of-llm/?utm source=chatgpt.com.

Tight Privacy Audit in One Run https://www.flowhunt.io/glossary/cost-of-llm/?utm source=chatgpt.com

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.806194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65ee6220-580d-4746-b9f7-98ffe80da8f7 · outbound

This paper cites Springer, 2007.

Tight Privacy Audit in One Run Springer, 2007

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.808928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 072cc418-3fb1-4d61-a461-77da63ad1fdb · outbound

This paper cites Membership inference attacks against machine learning models.

Tight Privacy Audit in One Run Membership inference attacks against machine learning models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.811378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe372758-83f5-4522-afa4-6463e5c43d16 · outbound

This paper cites Privacy auditing with one (1) training run.Advances in Neural Information Processing Systems, 36:49268–49280, 2023.

Tight Privacy Audit in One Run Privacy auditing with one (1) training run.Advances in Neural Information Processing Systems, 36:49268–49280, 2023

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.813951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f27451f-ba7d-49bf-aabb-0ae0a3d2f346 · outbound

This paper cites Debugging Differential Privacy: A Case Study for Privacy Auditing.

Tight Privacy Audit in One Run Debugging Differential Privacy: A Case Study for Privacy Auditing

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.816703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5261450c-b267-4409-add8-32b21398e402 · outbound

This paper cites Checkdp: An automated and integrated approach for proving differential privacy or finding precise counterexamples.

Tight Privacy Audit in One Run Checkdp: An automated and integrated approach for proving differential privacy or finding precise counterexamples

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.819693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e4aac32-dcd3-4058-8768-57c4c1235bbc · outbound

This paper cites Randomized response: A survey technique for eliminating evasive answer bias.Journal of the American Statistical Association, 60(309):63–69, 1965.

Tight Privacy Audit in One Run Randomized response: A survey technique for eliminating evasive answer bias.Journal of the American Statistical Association, 60(309):63–69, 1965

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.822174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e86883cb-cc74-4257-b6ab-bd694198ad1a · outbound

This paper cites A statistical framework for differential privacy.Journal of the American Statistical Association, 105(489):375–389, 2010.

Tight Privacy Audit in One Run A statistical framework for differential privacy.Journal of the American Statistical Association, 105(489):375–389, 2010

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.824826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba8204fc-0c2a-4ec1-b637-64e553db5a04 · outbound

This paper cites Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run.

Tight Privacy Audit in One Run Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.827382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ddea888-c562-464d-9bed-70f6cdbb000a · outbound

This paper cites Bayesian estimation of differential privacy.

Tight Privacy Audit in One Run Bayesian estimation of differential privacy

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.829998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afe7475e-04db-4b7f-9245-efe088106e6c · outbound

This paper cites white- box.

Tight Privacy Audit in One Run white- box

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-04T20:29:12.832727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 6929d25b-5f03-4380-80d4-7d9f27f6e9d8 · inbound

Rethinking the Security of DP-SGD: A Corrected Analysis of Differentially Private Machine Learning cites this paper.

Rethinking the Security of DP-SGD: A Corrected Analysis of Differentially Private Machine Learning Tight Privacy Audit in One Run

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-20T18:18:52.485626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c86c0910-579d-4394-a053-3610048a2485 · inbound

Let's Ask Gauss: Improved One-Run Privacy Auditing cites this paper.

Let's Ask Gauss: Improved One-Run Privacy Auditing Tight Privacy Audit in One Run

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:48:03.224319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.