Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Attentive Survey of Attention Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1904.02874.
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 2026-08-06T04:20:09.174487Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T10:00:37.374667Z
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 037bc9e7-30df-4a56-9131-aec138dc2e9a · inbound
Deep Personalized Re-targeting cites this paper.
Deep Personalized Re-targeting An Attentive Survey of Attention Models
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T10:00:37.378091Z
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.
Observation 6bdac8b5-c13b-4ae7-a1c2-aaf766c68dba · inbound
Topos Theory for Generative AI and LLMs cites this paper.
Topos Theory for Generative AI and LLMs An Attentive Survey of Attention Models
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T04:20:09.174487Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b29156c-a736-4d92-99b4-038ec920198f · inbound
A Rose by Any Other Name Would Smell as Sweet: Categorical Homotopy Theory for Large Language Models cites this paper.
A Rose by Any Other Name Would Smell as Sweet: Categorical Homotopy Theory for Large Language Models An Attentive Survey of Attention Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:46:18.415612Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.