Paper Citation Record · LEDGER

FSSD: Feature Fusion Single Shot Multibox Detector

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1712.00960.

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

pith.paper-citation-record.v1
1712.00960 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:43:59.450292Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:20:06.573273Z

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 a8abe2a4-a439-4f08-9a6e-8811984e2963 · inbound

Towards Adversarially Robust Object Detection cites this paper.

Towards Adversarially Robust Object Detection FSSD: Feature Fusion Single Shot Multibox Detector

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-24T17:04:42.941443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e1f9148a-938e-45ed-a490-e22a2cb754fc · inbound

Improve Underwater Object Detection through YOLOv12 Architecture and Physics-informed Augmentation cites this paper.

Improve Underwater Object Detection through YOLOv12 Architecture and Physics-informed Augmentation FSSD: Feature Fusion Single Shot Multibox Detector

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T21:43:59.450292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f036aee-1d8a-41ab-bac9-3f464060a836 · inbound

Are Candidate Models Really Needed for Active Learning? cites this paper.

Are Candidate Models Really Needed for Active Learning? FSSD: Feature Fusion Single Shot Multibox Detector

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T05:19:45.922377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation da364c36-d996-4ce8-b3a4-1b3bb182ddb2 · inbound

Balancing Uncertainty and Diversity of Samples: Leveraging Diversity of Least, High Confidence Samples for Effective Active Learning cites this paper.

Balancing Uncertainty and Diversity of Samples: Leveraging Diversity of Least, High Confidence Samples for Effective Active Learning FSSD: Feature Fusion Single Shot Multibox Detector

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T06:44:42.045775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fcc3f087-f47e-483a-b2fd-480e9492861f · 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 FSSD: Feature Fusion Single Shot Multibox Detector

Reference 83

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T19:20:06.575744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0c02424c-d642-498c-add1-7d24b469f943 · 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 FSSD: Feature Fusion Single Shot Multibox Detector

Reference 83

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.