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Paper Citation Record · LEDGER

Auditing of Unlearning Algorithms

As of 23 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.05898.

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

pith.paper-citation-record.v1
2607.05898 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-08T21:30:38.122700Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

25 of 25 outbound references displayed

  • verified exact6
  • verified fuzzy9
  • unresolved2
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 51d84c9a-b55c-4388-8fc6-29df2f2d9350 · outbound

This paper cites Local Differential Privacy: a tutorial.

Auditing of Unlearning Algorithms Local Differential Privacy: a tutorial

Reference 2

Resolution
metadata mismatch
local_arxiv, observed 2026-07-08T21:35:37.712222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:c9868e8c901b6064e1ff5e3a805f508861727a02abd941f549984e32a8955bae

Observation a907bc4a-aa16-4537-87c6-6c393d2134b8 · outbound

This paper cites Membership Inference Attacks From First Principles.

Auditing of Unlearning Algorithms Membership Inference Attacks From First Principles

Reference 3

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metadata mismatch
local_arxiv, observed 2026-07-08T21:35:37.694884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:88af9ac74829a57973ae59d8bb9eb0cdb28e4fa6480c9e7bf241b92dd9e9334d

Observation c5a9d605-cd33-427b-9a56-2aa9b1483387 · outbound

This paper cites unbounded.

Auditing of Unlearning Algorithms unbounded

Reference 4

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arxiv_id, observed 2026-07-08T21:35:37.602530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:caef093c154a2763416fbc77c6e71b4cabeb5e8ee0c299b97e94d70d7083898d

Observation 26aa60c6-66ce-4275-a01c-f91204987c88 · outbound

This paper cites Cheng, P.

Auditing of Unlearning Algorithms Cheng, P

Reference 5

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metadata mismatch
arxiv_id, observed 2026-07-08T21:35:37.705041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:8ca0c05a1179b57dc8cfdb044ca815f78a2f11d0c843d103009c4aa7f2f93b90

Observation 128c9eb7-6256-438c-abf3-20c8badb4f60 · outbound

This paper cites 2014.The Algorithmic Foundations of Differential Privacy.

Auditing of Unlearning Algorithms 2014.The Algorithmic Foundations of Differential Privacy

Reference 6

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metadata mismatch
doi, observed 2026-07-08T21:35:37.605782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:709e4bd1939801a9c325968df12715ada2ac1a0b7a6a3a0c72016e3007023a86

Observation d5dc7cbd-7d25-4a08-a467-b036f3cea758 · outbound

This paper cites On the Necessity of Output Distribution Reweighting for Effective Class Unlearning.

Auditing of Unlearning Algorithms On the Necessity of Output Distribution Reweighting for Effective Class Unlearning

Reference 7

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verified exact
arxiv_id, observed 2026-07-14T01:19:53.864690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:3c35bff57ca4169d3522334d223f14e8452611de4f13f7e0d64878478d6719da

Observation 86cf1d17-a777-42ea-8a1d-3e6d21ba8b78 · outbound

This paper cites Certified Unlearning for Neural Networks.

Auditing of Unlearning Algorithms Certified Unlearning for Neural Networks

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-07-08T21:35:37.709904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:ad980ce5c16066e0d8b20feb9997048da75abb710a009ef144500e711f5afe70

Observation 33f20d46-06a6-46d0-b2f5-04a878ba87c8 · outbound

This paper cites Milad Nasr, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, and Nicholas Carlini.

Auditing of Unlearning Algorithms Milad Nasr, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, and Nicholas Carlini

Reference 9

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verified exact
arxiv_id, observed 2026-07-08T21:35:37.717399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:f4952bf5feff6e6560f3a948279d2eda73e1f9c2b40baabe1da726bd70719ce4

Observation 56adf3c5-d326-49a3-8b29-111313616d2f · outbound

This paper cites Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning.

Auditing of Unlearning Algorithms Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning

Reference 10

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metadata mismatch
local_arxiv, observed 2026-07-08T21:35:37.699950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:37593406dbf24520959326644371e8e63ab3cdeefab417d11cf9cea57bf0808c

Observation 9a68df50-837d-4478-807a-8f9e447ef829 · outbound

This paper cites Membership Inference Attacks against Machine Learning Models.

Auditing of Unlearning Algorithms Membership Inference Attacks against Machine Learning Models

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-07-08T21:35:37.702290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:a973c18d611c2ec122cecfae1446989476e901c7ee71782ad8e6f3eb36aba371

Observation 5d245d98-8f8e-4cfd-ab5c-4dcea7514038 · outbound

This paper cites Privacy Auditing with One (1) Training Run.

Auditing of Unlearning Algorithms Privacy Auditing with One (1) Training Run

Reference 13

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verified exact
local_arxiv, observed 2026-07-08T21:35:37.714555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:8dedc0081a77eaf484b92372e6664c23cf3e26caa4f7d2054212b60902af73db

Observation 3f848e8a-71fa-4170-bbb9-bf0a39558a93 · outbound

This paper cites URL https://doi.org/ 10.1198/jasa.2009.tm08651.

Auditing of Unlearning Algorithms URL https://doi.org/ 10.1198/jasa.2009.tm08651

Reference 14

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verified exact
doi, observed 2026-07-08T21:35:37.604080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:172645a6d4d3eb593bfaaf76c72ce39313f53bc1c86ed62ec1f30a7560c032ad

Observation 24efbdc3-53e3-4518-bc9c-7163d59e9074 · outbound

This paper cites Towards Certified Unlearning for Deep Neural Networks.

Auditing of Unlearning Algorithms Towards Certified Unlearning for Deep Neural Networks

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-07-08T21:35:37.697381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:edc409d7aa207079c1c22942d29679b517df1099f01d42f0c732e10c22f96f96

Observation c5f0fd6e-4ae8-458a-ad0f-8f22b14c0f6e · outbound

This paper cites an unresolved cited work.

Auditing of Unlearning Algorithms Unresolved cited work

Reference 16

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unresolved
raw_fallback, observed 2026-07-08T21:35:38.010587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:63e90452f8e4ccce61bf4f426e328c09ca55f9c2ea5a19c94cc58c322eea7609

Observation b4fe7a65-1f8c-4b44-9623-c41fd7251d33 · outbound

This paper cites 16 Define the upper tailP ε(v) :=Pr u=v πε(u).

Auditing of Unlearning Algorithms 16 Define the upper tailP ε(v) :=Pr u=v πε(u)

Reference 17

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verified fuzzy
raw_fallback, observed 2026-07-08T21:35:37.997811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:e3f02e3a01761b8653afadb2136386d11a66fec775055527a9a6d06bd5ab7a78

Observation 3e1387e8-31fd-43bf-a9b7-f2c3d7176e6f · outbound

This paper cites From the training portion, we designate 10% of the points as the forget set Df (4,500 points), and use the remaining 40,500 points as the retain set Dr.

Auditing of Unlearning Algorithms From the training portion, we designate 10% of the points as the forget set Df (4,500 points), and use the remaining 40,500 points as the retain set Dr

Reference 18

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verified fuzzy
raw_fallback, observed 2026-07-08T21:35:38.003362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:7531e123d085479d902bbc88c8410ee37ec3761c1746cb914872fc6b242be64a

Observation 5df96742-13ed-4e7c-a615-03d6c8405cfc · outbound

This paper cites A discussion of why this split between auditor instantiations is appropriate is given in Section F.4, with a more detailed study in Section F.

Auditing of Unlearning Algorithms A discussion of why this split between auditor instantiations is appropriate is given in Section F.4, with a more detailed study in Section F

Reference 19

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verified fuzzy
raw_fallback, observed 2026-07-08T21:35:37.994131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:5379511d7001bc32f34d93bb99768b7e2e37aa155fa45cc6a715dc1562b79d61

Observation 1054eea2-faf3-4b97-add4-439cc9336e31 · outbound

This paper cites The retain samples and sampled forget samples are then pooled and shuffled to form the training dataset.

Auditing of Unlearning Algorithms The retain samples and sampled forget samples are then pooled and shuffled to form the training dataset

Reference 20

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verified fuzzy
raw_fallback, observed 2026-07-08T21:35:37.995965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:1f44f6ecc5b3735e9d2c6fa38f12b18f4e3610ef728477a06aa43de11a210f66

Observation 90a972a5-c78f-4147-a676-0d2c377a77c6 · outbound

This paper cites Model.The model is a 2-layer stacked character-level LSTM following McMahan et al.

Auditing of Unlearning Algorithms Model.The model is a 2-layer stacked character-level LSTM following McMahan et al

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation c3ac2bda-97ba-4eb4-81c1-ed8e025befc5 · outbound

This paper cites further, however, perfect overlap becomes harder to attain — the auditor is forced to commit to low-confidence batches, which dilute the overlap score and pull the bound back down.

Auditing of Unlearning Algorithms further, however, perfect overlap becomes harder to attain — the auditor is forced to commit to low-confidence batches, which dilute the overlap score and pull the bound back down

Reference 22

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verified fuzzy
raw_fallback, observed 2026-07-08T21:35:38.001474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:c1223a9dd27193efed5014647e312d3b31eaf72e9a5818f2e772a3cfe2b13121

Observation e94e4c6e-de47-47ef-b333-43582c009d95 · outbound

This paper cites an unresolved cited work.

Auditing of Unlearning Algorithms Unresolved cited work

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:8f547a3db37073cda552eecdf8f09f3852fbc3949889a2ee488012462f5123b8

Observation ce264f85-26dd-4518-8deb-536b96c89ca1 · outbound

This paper cites To obtain tighter bounds in this regime we use L= 500 runs.

Auditing of Unlearning Algorithms To obtain tighter bounds in this regime we use L= 500 runs

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:2ee13724541b4da3cbd5113bd5827062fc0263c27a91640c40c86f26bc7b8d49

Observation d1f436f0-0172-410f-8366-3d1e54d28f09 · outbound

This paper cites Shakespeare.We vary q∈ {1,2,4} , Ef ∈ {5,7} , and λ∈ {0.5,1.0,1.5}.

Auditing of Unlearning Algorithms Shakespeare.We vary q∈ {1,2,4} , Ef ∈ {5,7} , and λ∈ {0.5,1.0,1.5}

Reference 25

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verified fuzzy
raw_fallback, observed 2026-07-08T21:35:38.005246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:70e80f509198aa753d787121c23cd6d488872917cd2c16b84c4d75b37831e2af

Observation 1d8998bf-03f0-47a4-8a92-7daf7cc2df04 · outbound

This paper cites an unresolved cited work.

Auditing of Unlearning Algorithms Unresolved cited work

Reference 26

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raw_fallback, observed 2026-07-08T21:35:38.007058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:ee891b4f8b1991aa898d11c08cfdec5d49e785cc716a0cd90be7200246e87653

Observation 6bc596f3-f53e-4de5-a9ed-c626fb16afc8 · outbound

This paper cites [2021]); this is because the norm bound (∆) used for the addition of Gaussian noise is closer to what is actually attained empirically.

Auditing of Unlearning Algorithms [2021]); this is because the norm bound (∆) used for the addition of Gaussian noise is closer to what is actually attained empirically

Reference 27

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verified fuzzy
raw_fallback, observed 2026-07-08T21:35:38.012459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:8ec1cc6cce29974ff31cac568f587c61155f829619a7260ff02eba3b75f42bf7

Pith citing papers

No inbound Pith citation observations are available.