Paper Citation Record · LEDGER

Beyond Confusion: A Fine-grained Dialectical Examination of Human Activity Recognition Benchmark Datasets

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2412.09037.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.09037 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:42:55.645407Z

measured 1 of 1 external citation measurements

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 5c5da559-4918-48e1-8dea-3458f74f2af9 · inbound

FedFitTech: A Baseline in Federated Learning for Fitness Tracking cites this paper.

FedFitTech: A Baseline in Federated Learning for Fitness Tracking Beyond Confusion: A Fine-grained Dialectical Examination of Human Activity Recognition Benchmark Datasets

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:55.645407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24c2b8f8-d372-4dec-a98d-810593d23d7c · inbound

TinierHAR: Towards Ultra-Lightweight Deep Learning Models for Efficient Human Activity Recognition on Edge Devices cites this paper.

TinierHAR: Towards Ultra-Lightweight Deep Learning Models for Efficient Human Activity Recognition on Edge Devices Beyond Confusion: A Fine-grained Dialectical Examination of Human Activity Recognition Benchmark Datasets

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T18:31:33.561835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f46ffb1-2ef3-41ae-82f8-7c4dbf489c2d · inbound

BabyMamba-HAR: Lightweight Selective State Space Models for Efficient Human Activity Recognition on Resource Constrained Devices cites this paper.

BabyMamba-HAR: Lightweight Selective State Space Models for Efficient Human Activity Recognition on Resource Constrained Devices Beyond Confusion: A Fine-grained Dialectical Examination of Human Activity Recognition Benchmark Datasets

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-21T13:24:11.055779Z

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 ba306e2b-41b7-49b0-84ee-113c1a01580c · 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 Beyond Confusion: A Fine-grained Dialectical Examination of Human Activity Recognition Benchmark Datasets

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-27T07:10:41.159089Z

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.