Paper Citation Record · LEDGER

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models

As of 19 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 3 inbound Pith citation observations for arXiv:2411.10242.

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

pith.paper-citation-record.v1
2411.10242 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:54:19.224601Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:27:30.924737Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T02:07:33.490588Z

Reference resolution

28 of 28 outbound references displayed

verified exact1
verified fuzzy12
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 21709886-3c2e-409c-bd6c-67600f594df9 · outbound

This paper cites an unresolved cited work.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:54:19.940546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation df1b763a-cafb-46bb-8611-068f4f2266d6 · outbound

This paper cites black hole.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models black hole

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.845550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1f4c4e58-dbc3-4fee-966d-21d868eb3749 · outbound

This paper cites Table 3: Model-specific instantiation of the assistant prompt.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Table 3: Model-specific instantiation of the assistant prompt

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.918726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 45043830-e10c-419f-b9cc-39d2afefb6a7 · outbound

This paper cites The Llama 3 Herd of Models.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models The Llama 3 Herd of Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.039863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 719ccea3-9be8-4c00-8a33-b6b979c14df3 · outbound

This paper cites AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.056145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 879f1fd6-c7ff-43ed-9aa6-03c03bb0821a · outbound

This paper cites Scalable Extraction of Training Data from (Production) Language Models.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Scalable Extraction of Training Data from (Production) Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.063840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab1e3ec1-9963-45f9-ba81-a7f4da1e23a1 · outbound

This paper cites Understanding Transformers via N-gram Statistics.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Understanding Transformers via N-gram Statistics

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.071209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46931ed1-aedc-402f-a259-8367be1cedc8 · outbound

This paper cites Does Writing with Language Models Reduce Content Diversity?.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Does Writing with Language Models Reduce Content Diversity?

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.077929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cab7f8e7-8327-48b5-841a-24cea1494a33 · outbound

This paper cites Privacy risks of general-purpose language models.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Privacy risks of general-purpose language models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:20.037587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5686168c-ff99-4abf-903b-be182c3c0e6a · outbound

This paper cites Membership inference attacks against machine learning models.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Membership inference attacks against machine learning models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.088940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e45a8618-8020-4f42-badc-8788c80c57c1 · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.100984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15a014cc-466d-4ad5-a6c6-1205169705b3 · outbound

This paper cites Privacy risk in machine learning: Analyzing the connection to overfitting.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Privacy risk in machine learning: Analyzing the connection to overfitting

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.106680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a237033-3545-44c2-a880-502820b76ff3 · outbound

This paper cites LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.118870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 529fbcb9-265c-43c0-9e7f-ca19810b8aef · outbound

This paper cites Under review.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Under review

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.983866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2c1f8d55-e481-455c-9f1f-667dbf250cf6 · outbound

This paper cites Copy this text:.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Copy this text:

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.893700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c7d73801-61d1-4ab4-b101-f365967ca516 · outbound

This paper cites Under review.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Under review

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.870065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 06a26a10-f2e8-4482-a1c0-33fb45af7edb · outbound

This paper cites yolov3.weights.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models yolov3.weights

Reference 24

Resolution: verified exact; raw_fallback, observed 2026-08-12T19:54:19.393617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0b3aa300-1b00-45ea-9e49-13a499cdd9f4 · outbound

This paper cites Claude 3.5 Sonnet generated the following text for the prompt “Write a news article about The Catalan declaration of independence.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Claude 3.5 Sonnet generated the following text for the prompt “Write a news article about The Catalan declaration of independence

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.809539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 86472ce6-af98-45d8-b64f-473465a07804 · outbound

This paper cites Spain is living through a sad day,.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Spain is living through a sad day,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.787332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 87e7825d-a9e5-4939-831d-2c7126129d41 · outbound

This paper cites Schindler’s List.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Schindler’s List

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.766889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e7d930df-587d-4a9d-8113-997c31af06d0 · outbound

This paper cites independent writing.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models independent writing

Reference 500

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.960530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 024b0ba4-f64d-4789-b71c-86678b6bde7d · outbound

This paper cites This detection is the beginning of a new era: The field of gravitational wave astronomy is now a reality,.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models This detection is the beginning of a new era: The field of gravitational wave astronomy is now a reality,

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:19.827471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 27fa27ef-cd25-4ad3-8fca-2e4c18e65cd9 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.095661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5253d434-45fd-4aa2-b207-8f84c77fc6cc · outbound

This paper cites WildChat: 1M ChatGPT Interaction Logs in the Wild.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models WildChat: 1M ChatGPT Interaction Logs in the Wild

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.113181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f5bd5f6-c68b-4d34-893d-f6464c6be5ef · outbound

This paper cites Quantifying Memorization Across Neural Language Models.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Quantifying Memorization Across Neural Language Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.032446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 529f0d03-4e79-4f12-ba7d-604136337926 · outbound

This paper cites Reconstructing training data with informed adversaries.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Reconstructing training data with informed adversaries

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:54:20.065820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 55fa256b-e306-464e-945b-b949beb1dc94 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Measuring Massive Multitask Language Understanding

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.049122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dbb4d42-5518-4b8a-81e4-ff664c9dd5bd · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-12T19:54:19.019137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 554a1aab-d4a9-4732-b58f-c68ceb5c21c6 · inbound

Membership Inference Attacks on Sequence Models cites this paper.

Membership Inference Attacks on Sequence Models Measuring Non-Adversarial Reproduction of Training Data in Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:30.924737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 125ac473-0634-420a-81d4-4ca8f561fee9 · inbound

LLMs Can Leak Training Data But Do They Want To? A Propensity-Aware Evaluation of Memorization in LLMs cites this paper.

LLMs Can Leak Training Data But Do They Want To? A Propensity-Aware Evaluation of Memorization in LLMs Measuring Non-Adversarial Reproduction of Training Data in Large Language Models

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T12:56:57.472921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 403014c9-b9b9-47b7-a38c-6620ed20f3eb · inbound

SoK: Colluding Adversaries in Machine Learning Pipelines cites this paper.

SoK: Colluding Adversaries in Machine Learning Pipelines Measuring Non-Adversarial Reproduction of Training Data in Large Language Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-03T02:07:33.492459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.