Pith. sign in

Paper Citation Record · LEDGER

Auditing of Unlearning Algorithms

As of 9 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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:69d9fbbb00e11ffba5f490f17a1d7fe3142c1eb30f316d1325cc91306ba18d74

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:c3749ee60702fb842497f09c8306192af5bf8d6f13bab64c8e3483fa93dc01fa

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

This paper cites unbounded.

Auditing of Unlearning Algorithms unbounded

Reference 4

Resolution
metadata mismatch
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:fdb006e0a7422381eb3e8ecbe4072da5d308dcc72a4430430d538090e6edaa41

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

This paper cites Cheng, P.

Auditing of Unlearning Algorithms Cheng, P

Reference 5

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:36fa8364c3044ea41d59302454f397e1d398e740253c24c0ef3100bf3e3f18de

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:f6b0c142ff6356f5aa2f5ff06ae09dbea795eed074e8aa184929af96c9d86938

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:ed2c5835c5b950a806422ca76a586e58beea08730a8fbe44a78943e2c9266d6c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:831751ec0ce986542d4001c766b854c6ac391ae3e971d926a7d2218d0bc42a11

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:524ea2ca7f820eae079e0a3e5463f10784eacc479c1a6e60c10ee9bc37ca37ac

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:a4332832e43aff9089b1f571fb73c3b61493604738ebfc41e3f5834c01046607

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:f7196bbb6350fa869e36f8b79efcdf5ffdd801a3125947faad06f9be5da5990d

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:3d80dc755aa8aeb9ea570d6d403c6edea02095c9e2c73cd7aaa0235d33b53119

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:057f6af7c17a59f472510431508e0891cd4b3a9e33be9da3ec420ed71ed1d47e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:adc487a45840d0db6b5ddd41ed386e94a6c65d47a94bc971247216a2e26a2520

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

This paper cites an unresolved cited work.

Auditing of Unlearning Algorithms Unresolved cited work

Reference 16

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:d69809fa46070cc6c727596a63c8ff40102075fc60ee0157c151aa32bfcf28d7

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:6ac6c1b11ca2a3d9b566ebe1b687e0d3b10c8d095cc95b9032db18900dca7de5

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:a3a934425298d194c852d2442b49700c5a40b9bd6494c0aac45d6d58ed9ad740

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:b2d0fd98746b6b4bfb06730013e8c857383ca4e02bd33a44c41d69880e454d64

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:23acf621b6b4ab6c14543c99744c420a82245289707185bdc36c56bc7728edde

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

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T21:35:37.999598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:bb3b60fc7ede3446f3b51a01318261ad5989851f2baa91e4d39ab4660a079086

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:312091f63b2003242accc479a7a97e677f7809ffbd2cb7609e8186a162f5e4ff

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

This paper cites an unresolved cited work.

Auditing of Unlearning Algorithms Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-07-08T21:35:38.008879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:548c72f8dfa780882372bab31c0111a351e218d7bda382d81899f49c70e797be

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

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T21:35:37.992203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:f2e894fc03168aeb546f6c7d69eca9575c4a4ac53d23dfab189cbfc503d00308

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:f02a8e7630e15320074d9f6e0697e5a4eb36ef46a91a29aa0b2fa37d7f93a94b

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

This paper cites an unresolved cited work.

Auditing of Unlearning Algorithms Unresolved cited work

Reference 26

Resolution
malformed identifier
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:51a1754c7ca393d92dbd44b2fb21cc029ea275fb3e9d517fed19d64b0a7995fd

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T21:30:38.122700Z digest=sha256:0329864fc562c5689cea1ff74d3d801cb809fc17f17e9c902d87de7b8ab7e280

Pith citing papers

No inbound Pith citation observations are available.