Paper Citation Record · LEDGER

Copyright Violations and Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2310.13771.

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

pith.paper-citation-record.v1
2310.13771 v1

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 2026-08-09T19:14:53.502562Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:56:57.472305Z

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 55806582-a37b-4bc8-824f-7fd18e833c1c · inbound

Agents Are All You Need for LLM Unlearning cites this paper.

Agents Are All You Need for LLM Unlearning Copyright Violations and Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T19:14:53.502562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f45330f-b883-462a-8846-a0c872513e62 · inbound

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

A Lightweight Method to Disrupt Memorized Sequences in LLM Copyright Violations and Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T20:08:57.393267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a5da79f-86cc-4e64-a088-1fc2b2a00fa4 · inbound

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations cites this paper.

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations Copyright Violations and Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T15:26:07.596081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d033728a-5206-4d78-b945-ea21c8165ee4 · inbound

Extracting memorized pieces of (copyrighted) books from open-weight language models cites this paper.

Extracting memorized pieces of (copyrighted) books from open-weight language models Copyright Violations and Large Language Models

Reference 145

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:01:38.061122Z

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 2d590d4f-411f-4dca-8363-3e5bdbf79279 · inbound

The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs cites this paper.

The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs Copyright Violations and Large Language Models

Reference 192

Resolution: unresolved; no resolver link, observed 2026-08-07T10:17:27.184411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 329dd458-b6ee-4f3c-bbaa-24217d06738c · inbound

UCD: Unlearning in LLMs via Contrastive Decoding cites this paper.

UCD: Unlearning in LLMs via Contrastive Decoding Copyright Violations and Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T04:22:59.843628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bbaf945-3fbb-412b-888d-12b6e30a0c10 · 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 Copyright Violations and Large Language Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T00:46:10.117323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd95ff86-081d-4c09-b762-f3e60dc85696 · inbound

Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding cites this paper.

Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding Copyright Violations and Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T23:39:06.136500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 449d9b17-8f0a-4d6d-beeb-29c05d6c9290 · inbound

Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning cites this paper.

Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning Copyright Violations and Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T12:25:02.634993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd667fec-e0ec-4f70-b9e9-d989264bb328 · inbound

Representation-Guided Parameter-Efficient LLM Unlearning cites this paper.

Representation-Guided Parameter-Efficient LLM Unlearning Copyright Violations and Large Language Models

Reference 51

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:06:19.381603Z

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 f513883f-2f2e-4ae9-81eb-54f0e5aec315 · 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 Copyright Violations and Large Language Models

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T12:56:57.473655Z

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 b794534b-365c-44d3-b03b-33cba2e7334d · inbound

Probabilistic "Copies" in Generative AI Models cites this paper.

Probabilistic "Copies" in Generative AI Models Copyright Violations and Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T01:52:09.107659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.