Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Training Foundation Models as Data Compression: On Information, Model Weights and Copyright Law
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.13493.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T16:40:27.067104Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T23:11:18.069690Z
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 4cbff724-f585-4e2d-993d-ff544519fb21 · inbound
LCIRC: A Recurrent Compression Approach for Efficient Long-form Context and Query Dependent Modeling in LLMs cites this paper.
LCIRC: A Recurrent Compression Approach for Efficient Long-form Context and Query Dependent Modeling in LLMs Training Foundation Models as Data Compression: On Information, Model Weights and Copyright Law
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:40:27.067104Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 849b7994-5b61-4c5b-9a40-82a4eb5ecb3b · inbound
Erase Persona, Forget Lore: Benchmarking Multimodal Copyright Unlearning in Large Vision Language Models cites this paper.
Erase Persona, Forget Lore: Benchmarking Multimodal Copyright Unlearning in Large Vision Language Models Training Foundation Models as Data Compression: On Information, Model Weights and Copyright Law
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T23:11:18.075337Z
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 f8ca8aba-604e-4c92-aa7f-e64472853cd9 · inbound
Probabilistic "Copies" in Generative AI Models cites this paper.
Probabilistic "Copies" in Generative AI Models Training Foundation Models as Data Compression: On Information, Model Weights and Copyright Law
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T01:52:11.098275Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.