Pith. sign in

Paper Citation Record · LEDGER

Measuring Forgetting of Memorized Training Examples

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2207.00099.

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

pith.paper-citation-record.v1
2207.00099 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:24:37.500912Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T21:10:09.130679Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6d78239e-2f2f-4093-9c75-d5bcd3c57040 · inbound

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling cites this paper.

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling Measuring Forgetting of Memorized Training Examples

Reference 183

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T17:45:17.857530Z

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=arxiv_source observed=2026-05-15T17:45:17.540282Z digest=sha256:5b36fa508994ac81d70aa4bedeea43562acaad566cb3c68ae748638678c537dd

Observation 00eddf17-d7ab-4bd5-9e88-fc36d926e132 · inbound

PaLM 2 Technical Report cites this paper.

PaLM 2 Technical Report Measuring Forgetting of Memorized Training Examples

Reference 163

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T11:59:27.079286Z

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=arxiv_source observed=2026-05-12T11:59:25.813128Z digest=sha256:90593bb18ad06974d23bfd70bb908911f95a8b45fbf902334d15f2666cd8033a

Observation d3462358-bb7a-408f-a453-1666fa2d4152 · inbound

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment cites this paper.

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment Measuring Forgetting of Memorized Training Examples

Reference 183

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:30:45.003474Z

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=2026-05-17T22:30:44.520703Z digest=sha256:b1d0dbfb62fafa4ce6f126c3887d42081c4fccfebda0d81cab8176453ae8deac

Observation f2014641-a06c-44c2-b04e-9ae8c43b7e27 · inbound

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection cites this paper.

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection Measuring Forgetting of Memorized Training Examples

Reference 66

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T14:15:11.051443Z

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=arxiv_source observed=2026-05-12T14:15:10.907921Z digest=sha256:fc0d291dd57db2e13efde7fc0aee71257f0a651417404f20a3ea5c3a757627e1

Observation 11d60ce6-0088-4547-bd41-1511f0853261 · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey Measuring Forgetting of Memorized Training Examples

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:58:26.499355Z

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=2026-05-23T20:58:16.237327Z digest=sha256:137e3bbf39bc96fa93b53fc89f5a8380b6e102313c8d340b5b2ead491e8fbe70

Observation 9b91824f-952f-4ee1-a652-d78207fcb38f · inbound

Skewed Memorization in Large Language Models: Quantification and Decomposition cites this paper.

Skewed Memorization in Large Language Models: Quantification and Decomposition Measuring Forgetting of Memorized Training Examples

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-09T16:24:37.500912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:24:37.500912Z digest=sha256:546197be1d9d2ec24e7975d631b9f851730dd90e8ec12fbbb54b25787e15f948

Observation ce438300-d9a4-4d31-b98a-0eb2f309df2c · inbound

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation cites this paper.

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation Measuring Forgetting of Memorized Training Examples

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T00:46:10.097075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:46:10.097075Z digest=sha256:6c5cb6af34130bad9d899467a385bc7dac61b7f88a7adf177e8f600c0a17006a

Observation f0f6c9ba-01fa-4a9c-a6bc-d728ebb78d84 · inbound

Rethinking Memorization Measures and their Implications in Large Language Models cites this paper.

Rethinking Memorization Measures and their Implications in Large Language Models Measuring Forgetting of Memorized Training Examples

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T15:54:34.984512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:54:34.984512Z digest=sha256:fb64be40e8917c56ab263bb7588f36fd2b253281ce844c71ebc02856e08113f8

Observation fd695d9c-6181-4fa0-8a1b-277f7590a41d · inbound

Forgetting is Everywhere cites this paper.

Forgetting is Everywhere Measuring Forgetting of Memorized Training Examples

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-03T23:42:03.965439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:42:03.965439Z digest=sha256:740f46b742e179ca67c7bd251a2813e62e308e1a93aea8f800a873333636c103

Observation 1ce0260a-923c-47dc-822e-c3dba9ca1aeb · inbound

Towards Reliable Testing of Machine Unlearning cites this paper.

Towards Reliable Testing of Machine Unlearning Measuring Forgetting of Memorized Training Examples

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:25:18.324596Z

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=2026-05-10T11:24:29.533446Z digest=sha256:b42767a4053e2618ee7a3da9b1c5ba1f13f9f0e4fb0c23db96e6188fe205417f

Observation 75507299-eb8a-4078-83fb-a22a249ceb3b · inbound

Optimizer-Model Consistency: Full Finetuning with the Same Optimizer as Pretraining Forgets Less cites this paper.

Optimizer-Model Consistency: Full Finetuning with the Same Optimizer as Pretraining Forgets Less Measuring Forgetting of Memorized Training Examples

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:26:08.593021Z

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=2026-05-08T12:00:49.127471Z digest=sha256:5c091ec7b227c21c6e6d1b2039460f9bd2f907a7f4f793565ac6145e76fc8707

Observation 0b459912-896e-4b75-b42b-c12a349be940 · inbound

Natural Ungrokking: Asymmetric Control of Which Rules Survive Pretraining cites this paper.

Natural Ungrokking: Asymmetric Control of Which Rules Survive Pretraining Measuring Forgetting of Memorized Training Examples

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-04T21:10:09.132368Z

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=arxiv_source observed=2026-06-25T19:04:11.976747Z digest=sha256:ebd8015eec43602813b477f5ddc5e51b1df3b3fc77db32d8dbef1c4c4aa4413e