Paper Citation Record · LEDGER

What is YOLOv5: A deep look into the internal features of the popular object detector

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2407.20892.

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

pith.paper-citation-record.v1
2407.20892 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:32.473069Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-08T01:14:27.474077Z

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 1a37ea7e-5397-4c57-b329-beddd2f502ac · inbound

YOLOv11: An Overview of the Key Architectural Enhancements cites this paper.

YOLOv11: An Overview of the Key Architectural Enhancements What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-12T13:29:16.339949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3622c13e-9f3c-4029-9304-5df61a0990a7 · inbound

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions cites this paper.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.473069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06562e01-0a62-4426-8c0f-188f43a06579 · inbound

DMS-Net:Dual-Modal Multi-Scale Siamese Network for Binocular Fundus Image Classification cites this paper.

DMS-Net:Dual-Modal Multi-Scale Siamese Network for Binocular Fundus Image Classification What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T10:28:49.384151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 502ef217-58a9-4934-a50c-4f8d33461731 · inbound

Geofenced Unmanned Aerial Robotic Defender for Deer Detection and Deterrence (GUARD) cites this paper.

Geofenced Unmanned Aerial Robotic Defender for Deer Detection and Deterrence (GUARD) What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T21:07:15.113940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d476950d-820e-4b8f-8341-223b862daa70 · inbound

Rethinking Video Human-Object Interaction: Set Prediction over Time for Unified Detection and Anticipation cites this paper.

Rethinking Video Human-Object Interaction: Set Prediction over Time for Unified Detection and Anticipation What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:50:58.481937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 75089bc2-284c-43e5-b877-f9e66f3872cc · inbound

A Marine Debris Detection Framework for Ocean Robots via Self-Attention Enhancement and Feature Interaction Optimization cites this paper.

A Marine Debris Detection Framework for Ocean Robots via Self-Attention Enhancement and Feature Interaction Optimization What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:00:54.219082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5cad8bbb-c524-4a8f-8480-1784fb907eb5 · inbound

Tetris: Tile-level Sampling for Efficient and High-Fidelity Video Object Tracking cites this paper.

Tetris: Tile-level Sampling for Efficient and High-Fidelity Video Object Tracking What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:24:00.790138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6d172b3e-f73d-4451-9a14-799f82786023 · inbound

Tetris: Tile-level Sampling for Efficient and High-Fidelity Video Object Tracking cites this paper.

Tetris: Tile-level Sampling for Efficient and High-Fidelity Video Object Tracking What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T13:14:36.657156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3bb2586-f7a9-4d79-ac0f-859a11d13e0b · inbound

LEVIRDet: A Million-Scale 159-Category Dataset and Foundation Model for Universal Remote Sensing Object Detection cites this paper.

LEVIRDet: A Million-Scale 159-Category Dataset and Foundation Model for Universal Remote Sensing Object Detection What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-07-04T19:20:06.606075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c81c0272-6f9d-458a-a2cc-483b71026d53 · inbound

LEVIRDet: A Million-Scale 159-Category Dataset and Foundation Model for Universal Remote Sensing Object Detection cites this paper.

LEVIRDet: A Million-Scale 159-Category Dataset and Foundation Model for Universal Remote Sensing Object Detection What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 78

Resolution: unresolved; no resolver link, observed 2026-07-12T12:17:51.491548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb4aff1e-22a8-4318-bc23-e480c91c7da3 · inbound

Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models cites this paper.

Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T09:05:37.356440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 61fc6a88-10d5-48c0-91c5-be3a0b8c32c0 · inbound

Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models cites this paper.

Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T09:19:34.971524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e950ada8-eb22-4f7b-b1d0-4000ee684b51 · inbound

A Stereo Visual SLAM System Using Object-Level Motion Estimation and Geometric Filtering Based on Cross Disparity cites this paper.

A Stereo Visual SLAM System Using Object-Level Motion Estimation and Geometric Filtering Based on Cross Disparity What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-03T12:08:06.392342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ba96274e-1b95-4659-ba6b-083aff33b748 · inbound

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection cites this paper.

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 27

Resolution: metadata mismatch; local_arxiv, observed 2026-07-08T01:14:27.475898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a3ab7375-18de-4966-a629-79a7b86b0fa9 · inbound

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection cites this paper.

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-11T07:49:40.867148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0317c23-6713-4443-a7fd-eb6ddc99266f · inbound

ISAC and Vision Fusion for Fine-Grained Low-Altitude Target Recognition cites this paper.

ISAC and Vision Fusion for Fine-Grained Low-Altitude Target Recognition What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-30T12:31:16.303904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.