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Paper Citation Record · LEDGER

YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2406.10139.

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

pith.paper-citation-record.v1
2406.10139 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:55:50.365602Z

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

51
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 7ac17f75-c017-42c4-a6f2-9f408de53f9b · inbound

What is YOLOv6? A Deep Insight into the Object Detection Model cites this paper.

What is YOLOv6? A Deep Insight into the Object Detection Model YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T13:34:55.297243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:34:55.297243Z digest=sha256:c7813f1e6f100b4b5ccb954599d90093191d06dc3b80fd335fcdb2d991854ff8

Observation 76ceebd0-6a5d-4647-9b20-486110b3b032 · inbound

Performance of YOLOv7 in Kitchen Safety While Handling Knife cites this paper.

Performance of YOLOv7 in Kitchen Safety While Handling Knife YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T21:15:57.432554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:15:57.432554Z digest=sha256:2f28b3c8c090a634421e52f7cd954d18d91d1fb404ee0e82b9e46508764ed024

Observation aa233475-9fc4-4106-8c44-08af0deb7d56 · inbound

YOLOv8 to YOLO11: A Comprehensive Architecture In-depth Comparative Review cites this paper.

YOLOv8 to YOLO11: A Comprehensive Architecture In-depth Comparative Review YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-23T05:12:34.662353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-23T05:08:02.223581Z digest=sha256:15ac7ad6fb193adedfdcafa9e87c619ad2e330521102a5a2e2840954b47a2816

Observation b3d8e78e-6d89-47a1-b785-a38066b2be61 · inbound

Enhancing Quantum-ready QUBO-based Suppression for Object Detection with Appearance and Confidence Features cites this paper.

Enhancing Quantum-ready QUBO-based Suppression for Object Detection with Appearance and Confidence Features YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-09T10:46:46.398527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:46:46.398527Z digest=sha256:8486764a0b068fe27823fc633d24b9e17ea2dff617cb7e6e2c630a045b330059

Observation c28383d0-50eb-4340-a723-351b3f1e868a · inbound

YOLOv4: A Breakthrough in Real-Time Object Detection cites this paper.

YOLOv4: A Breakthrough in Real-Time Object Detection YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-08T23:20:54.185822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:20:54.185822Z digest=sha256:7243ea3c45fbbef4a187e6fe9fc364e527994bc0181ad3ae1e0bbcc91c0b6d07

Observation cefaf406-16b4-4e5f-8d28-7db6c336e913 · inbound

Improving Object Detection Performance through YOLOv8: A Comprehensive Training and Evaluation Study cites this paper.

Improving Object Detection Performance through YOLOv8: A Comprehensive Training and Evaluation Study YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-15T20:55:50.365602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:50.365602Z digest=sha256:47189bf67bf1226b24fe5a6fab77598892dab920e2b2155d5823587676549012

Observation 7c974cfa-a230-4a1b-9d00-b6edee8b2d83 · inbound

A Low-Cost Machine Learning Approach for Timber Diameter Estimation cites this paper.

A Low-Cost Machine Learning Approach for Timber Diameter Estimation YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T14:57:55.473731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:57:55.473731Z digest=sha256:5fc82a02ddbfc7d122b98ce152dd6b271110447da477a02da886d78ebc22092d

Observation cbd2ce1f-1511-49e1-9f2a-fa5b8283d99c · inbound

A geometric and deep learning reproducible pipeline for monitoring floating anthropogenic debris in urban rivers using in situ cameras cites this paper.

A geometric and deep learning reproducible pipeline for monitoring floating anthropogenic debris in urban rivers using in situ cameras YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-04T07:54:02.180148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:54:02.180148Z digest=sha256:625933b36d48255d462030ed02f67b8e463d77f12256875177d3357c313150d0