Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
F$^3$Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2504.08222.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:13:33.998898Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T16:41:37.841329Z
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 ddbfa56d-1376-410a-8ede-f4f73264ce2a · inbound
Enhancing Sports Strategy with Video Analytics and Data Mining: Assessing the effectiveness of Multimodal LLMs in tennis video analysis cites this paper.
Enhancing Sports Strategy with Video Analytics and Data Mining: Assessing the effectiveness of Multimodal LLMs in tennis video analysis F$^3$Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:12:00.437572Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 96609eb1-0a4d-40c4-9488-5fe4d460020d · inbound
Enhancing Sports Strategy with Video Analytics and Data Mining: Automated Video-Based Analytics Framework for Tennis Doubles cites this paper.
Enhancing Sports Strategy with Video Analytics and Data Mining: Automated Video-Based Analytics Framework for Tennis Doubles F$^3$Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:13:33.998898Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0caf659e-2891-4309-9635-9fa8cf0ad724 · inbound
FineBadminton: A Multi-Level Dataset for Fine-Grained Badminton Video Understanding cites this paper.
FineBadminton: A Multi-Level Dataset for Fine-Grained Badminton Video Understanding F$^3$Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:06:31.863473Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 031fbbac-8bbd-4773-bafa-f209b64b13ab · inbound
TennisTV: Do Multimodal Large Language Models Understand Tennis Rallies? cites this paper.
TennisTV: Do Multimodal Large Language Models Understand Tennis Rallies? F$^3$Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T16:41:37.844059Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 284af565-d090-4f18-8840-455ff3f941a3 · inbound
RefereeBench: Are Video MLLMs Ready to be Multi-Sport Referees cites this paper.
RefereeBench: Are Video MLLMs Ready to be Multi-Sport Referees F$^3$Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:48:02.273708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.