Paper Citation Record · LEDGER

Training Data Extraction From Pre-trained Language Models: A Survey

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2305.16157.

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

pith.paper-citation-record.v1
2305.16157 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:49:44.766456Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:38:43.800061Z

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 499c5ad2-eac6-46c7-a8cd-ec02c99ac667 · inbound

Industry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions cites this paper.

Industry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions Training Data Extraction From Pre-trained Language Models: A Survey

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-24T04:23:52.833925Z

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 6cd58c6c-a051-4c8e-990b-229f98191f18 · inbound

Automated Privacy Information Annotation in Large Language Model Interactions cites this paper.

Automated Privacy Information Annotation in Large Language Model Interactions Training Data Extraction From Pre-trained Language Models: A Survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:49:44.766456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aed2183e-791d-42a1-ad2e-b30a1bb9c7fc · inbound

Channel-Level Semantic Perturbations: Unlearnable Examples for Diverse Training Paradigms cites this paper.

Channel-Level Semantic Perturbations: Unlearnable Examples for Diverse Training Paradigms Training Data Extraction From Pre-trained Language Models: A Survey

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-10T07:11:53.515645Z

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 29d0ca2e-9c6f-49d9-8fac-b63c346a5dc6 · inbound

Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications cites this paper.

Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications Training Data Extraction From Pre-trained Language Models: A Survey

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T17:24:57.276447Z

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 2ec034f5-e745-4cee-8f61-6c76139dabe1 · inbound

Selective Token-Level Cryptographic Redaction for Privacy-Preserving Clinical Deployment of Large Language Models cites this paper.

Selective Token-Level Cryptographic Redaction for Privacy-Preserving Clinical Deployment of Large Language Models Training Data Extraction From Pre-trained Language Models: A Survey

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:06:30.144763Z

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 b5d84111-d3a6-4d90-823a-f55f6aff2fb6 · inbound

Loss Landscape Poisoning: Targeted Extraction of Unseen Training Data from LLMs cites this paper.

Loss Landscape Poisoning: Targeted Extraction of Unseen Training Data from LLMs Training Data Extraction From Pre-trained Language Models: A Survey

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:38:43.801565Z

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.