Pith. sign in

Paper Citation Record · LEDGER

DiffusionDet: Diffusion Model for Object Detection

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2211.09788.

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

pith.paper-citation-record.v1
2211.09788 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:08:15.933637Z

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

40
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 b005ba31-e47a-4d9a-8faa-90e9d99992c3 · inbound

DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory cites this paper.

DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory DiffusionDet: Diffusion Model for Object Detection

Reference 138

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:03:57.997786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-20T13:03:57.828598Z digest=sha256:ff26838070a63d84e0ea232ec7cfccd9ffdb0ae2670306760edbd6af8b98aba0

Observation 30d7e396-ddc3-4277-ae71-fc15469366d9 · inbound

A Privacy Enhancing Technique to Evade Detection by Street Video Cameras Without Using Adversarial Accessories cites this paper.

A Privacy Enhancing Technique to Evade Detection by Street Video Cameras Without Using Adversarial Accessories DiffusionDet: Diffusion Model for Object Detection

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T14:08:15.933637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:08:15.933637Z digest=sha256:115224df9822c049ae9481988fa09270c5397b45617c90ab6985a64b552df9d2

Observation 8261f965-bd40-48cb-9979-cb60972020a5 · inbound

VisAlgae 2023: A Dataset and Challenge for Algae Detection in Microscopy Images cites this paper.

VisAlgae 2023: A Dataset and Challenge for Algae Detection in Microscopy Images DiffusionDet: Diffusion Model for Object Detection

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:10.628962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:10.628962Z digest=sha256:6811945337ca772bd05407014378a6c9b90c2d1ddd3e256553006ab363455b52

Observation cf810e96-7647-45f0-89ce-c4036b0690c1 · inbound

Probabilistic Spatial Interpolation of Sparse Data using Diffusion Models cites this paper.

Probabilistic Spatial Interpolation of Sparse Data using Diffusion Models DiffusionDet: Diffusion Model for Object Detection

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T13:59:02.845226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:59:02.845226Z digest=sha256:f1a0496ad43e1987c5958fd6887bd5dab0a83ef3e5267ce9e12b6c509bcbfb22

Observation 2fdf076e-e891-43d4-b114-ef1ac38476bd · inbound

SHeRL-FL: When Representation Learning Meets Split Learning in Hierarchical Federated Learning cites this paper.

SHeRL-FL: When Representation Learning Meets Split Learning in Hierarchical Federated Learning DiffusionDet: Diffusion Model for Object Detection

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T22:03:09.607119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:03:09.607119Z digest=sha256:4861ea495ed321642cc9514844713a43357954d3838ce871fbbe9708526dbb1f