Paper Citation Record · LEDGER

SoK: Memorization in General-Purpose Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.18362.

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

pith.paper-citation-record.v1
2310.18362 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:08:57.369870Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

9
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0b5f86ce-1c4d-4fd1-aef5-8d253e9d7ad4 · inbound

A Lightweight Method to Disrupt Memorized Sequences in LLM cites this paper.

A Lightweight Method to Disrupt Memorized Sequences in LLM SoK: Memorization in General-Purpose Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T20:08:57.369870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2e60055-69b5-49b5-91f2-8f32525c57dd · inbound

Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning cites this paper.

Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning SoK: Memorization in General-Purpose Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:40.334702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2eff85a8-1aa0-4996-8708-19237e3aeab7 · inbound

On Recipe Memorization and Creativity in Large Language Models: Is Your Model a Creative Cook, a Bad Cook, or Merely a Plagiator? cites this paper.

On Recipe Memorization and Creativity in Large Language Models: Is Your Model a Creative Cook, a Bad Cook, or Merely a Plagiator? SoK: Memorization in General-Purpose Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T21:44:55.805747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8ba0765-3593-4dd7-83e0-63b5f11a000f · inbound

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems cites this paper.

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems SoK: Memorization in General-Purpose Large Language Models

Reference 112

Resolution: unresolved; no resolver link, observed 2026-08-04T17:46:19.280598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6f5e668-4c45-4d90-861b-4016884b25dd · inbound

Output Vector Editing for Memorization Mitigation in Large Language Models cites this paper.

Output Vector Editing for Memorization Mitigation in Large Language Models SoK: Memorization in General-Purpose Large Language Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-26T21:30:02.925245Z

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.

Observation 69834fa3-7d04-4ffe-b282-6e938e7b1224 · inbound

LLM-ACES: Closed-Loop Discovery of Dynamical Systems with LLM-Guided Adaptive Search cites this paper.

LLM-ACES: Closed-Loop Discovery of Dynamical Systems with LLM-Guided Adaptive Search SoK: Memorization in General-Purpose Large Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:39:59.940159Z

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.

Observation 0b42cc23-501a-4c7a-a4a8-2627bae30ee2 · inbound

Probing Memorization of Tabular In-Context Learning cites this paper.

Probing Memorization of Tabular In-Context Learning SoK: Memorization in General-Purpose Large Language Models

Reference 190

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:25:40.743102Z

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.