Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Benchmarking Classical, Deep, and Generative Models for Human Activity Recognition
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2501.08471.
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 2026-06-27T07:09:27.953953Z
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
0
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 d0be8f45-2fb0-4d0d-b495-5b8e3fbd4c00 · inbound
BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition cites this paper.
BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition Benchmarking Classical, Deep, and Generative Models for Human Activity Recognition
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:56:34.067554Z
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.
Observation d74eff55-ac3e-440d-a3fd-94cffaa3ed00 · inbound
WHAR Arena: Benchmarking the State of the Art in Efficient Wearable Human Activity Recognition cites this paper.
WHAR Arena: Benchmarking the State of the Art in Efficient Wearable Human Activity Recognition Benchmarking Classical, Deep, and Generative Models for Human Activity Recognition
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T07:10:41.073175Z
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.