Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Evaluating Copyright Takedown Methods for Language Models
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2406.18664.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:19:16.804479Z
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
1
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 f7cefec3-e17d-4cd4-9faa-9b448b925f90 · inbound
Copyright-Protected Language Generation via Adaptive Model Fusion cites this paper.
Copyright-Protected Language Generation via Adaptive Model Fusion Evaluating Copyright Takedown Methods for Language Models
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T19:34:17.775724Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3080bab-9420-4b6a-8948-00f41382fc25 · inbound
Investigating the Feasibility of Mitigating Potential Copyright Infringement via Large Language Model Unlearning cites this paper.
Investigating the Feasibility of Mitigating Potential Copyright Infringement via Large Language Model Unlearning Evaluating Copyright Takedown Methods for Language Models
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:16:49.692646Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 767a0473-9d9e-46c5-b629-e3cc4a28a799 · inbound
Synthetic Data Can Mislead Evaluations: Membership Inference as Machine Text Detection cites this paper.
Synthetic Data Can Mislead Evaluations: Membership Inference as Machine Text Detection Evaluating Copyright Takedown Methods for Language Models
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:58:01.341382Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d726cdf2-ef62-40bb-b0e5-65a195ad6b0a · inbound
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations cites this paper.
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations Evaluating Copyright Takedown Methods for Language Models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T15:26:07.788546Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 74ab519e-c890-4398-984d-2999893ebf01 · inbound
Certified Mitigation of Worst-Case LLM Copyright Infringement cites this paper.
Certified Mitigation of Worst-Case LLM Copyright Infringement Evaluating Copyright Takedown Methods for Language Models
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:19:16.804479Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce5cf811-f625-4750-bdde-2d4f4203fb52 · inbound
DUSK: Do Not Unlearn Shared Knowledge cites this paper.
DUSK: Do Not Unlearn Shared Knowledge Evaluating Copyright Takedown Methods for Language Models
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:24.944971Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a12748b-76df-4d96-8a36-beba2ee09e70 · inbound
R-TOFU: Unlearning in Large Reasoning Models cites this paper.
R-TOFU: Unlearning in Large Reasoning Models Evaluating Copyright Takedown Methods for Language Models
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:10.239286Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 465cb9f7-6bc9-4e16-bd73-dab91a77ee27 · inbound
AI as a Tool for Simulation-Based Experiments in Literary Studies cites this paper.
AI as a Tool for Simulation-Based Experiments in Literary Studies Evaluating Copyright Takedown Methods for Language Models
Reference 68
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T15:02:18.941205Z
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.