Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Information Filtering Networks: Theoretical Foundations, Generative Methodologies, and Real-World Applications
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2505.03812.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T05:52:08.706988Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T14:35:46.890621Z
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 b1f2c57c-b8c7-4e3a-a52e-34fdcc4a49ff · inbound
The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets cites this paper.
The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets Information Filtering Networks: Theoretical Foundations, Generative Methodologies, and Real-World Applications
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:52:08.706988Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c9d37c35-e8be-49c9-b33c-98ded70cb63c · inbound
Compositional Sparsity as an Inductive Bias for Neural Architecture Design cites this paper.
Compositional Sparsity as an Inductive Bias for Neural Architecture Design Information Filtering Networks: Theoretical Foundations, Generative Methodologies, and Real-World Applications
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T14:35:46.892311Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.