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Paper Citation Record · LEDGER

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns

As of 11 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.00997.

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

pith.paper-citation-record.v1
2506.00997 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:59:08.711344Z

measured 39 of 39 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact1
  • verified fuzzy29
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6fb0f9a3-8eac-41ab-acca-f7c00fa4adf1 · outbound

This paper cites Tide: A general toolbox for identifying object detection errors,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Tide: A general toolbox for identifying object detection errors,

Reference 1

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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.

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Observation 64b26199-7885-4ce4-b0ba-9fa5b002c07b · outbound

This paper cites A trainable pedestrian detection system,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns A trainable pedestrian detection system,

Reference 2

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raw_fallback, observed 2026-08-07T11:59:14.639742Z

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.

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Observation 403737e3-7a99-4f82-874e-1d0b2513c4c8 · outbound

This paper cites Histograms of oriented gradients for human detection,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Histograms of oriented gradients for human detection,

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a2af2829-8665-49cd-b588-41789cc225e7 · outbound

This paper cites The 2005 pascal visual object classes challenge,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns The 2005 pascal visual object classes challenge,

Reference 4

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raw_fallback, observed 2026-08-07T11:59:14.468321Z

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.

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Observation 1b741d05-698e-4959-8f9f-8ae1c0a9a313 · outbound

This paper cites The pascal visual object classes challenge 2012 (voc2012) development kit,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns The pascal visual object classes challenge 2012 (voc2012) development kit,

Reference 5

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raw_fallback, observed 2026-08-07T11:59:14.305950Z

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.

source=pdf_text observed=2026-08-07T11:59:04.787079Z digest=sha256:0eb34f7115c96bf44ab0d6b1ac0bf881e3c3209c2beb09c16151ac1cea3b19f0

Observation 183a7fb1-691b-4c4a-97d4-db01ccb0dd84 · outbound

This paper cites MS COCO: Common Objects in Context,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns MS COCO: Common Objects in Context,

Reference 6

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raw_fallback, observed 2026-08-07T11:59:14.106513Z

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.

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Observation e1dc6252-827d-4d3a-962c-b86b4e285308 · outbound

This paper cites Benchmarking a Benchmark: How Reliable is MS-COCO?.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Benchmarking a Benchmark: How Reliable is MS-COCO?

Reference 7

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no resolver link, observed 2026-08-07T11:59:05.044782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 53894d20-cb13-45e3-9561-533bb11a621b · outbound

This paper cites The effect of improving annotation quality on object detection datasets: A preliminary study,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns The effect of improving annotation quality on object detection datasets: A preliminary study,

Reference 8

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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.

source=pdf_text observed=2026-08-07T11:59:05.161454Z digest=sha256:ac104905f4cb7d2664ced818730562f6ad771e4addcaeff16274eef1d8d1e8d5

Observation cd500dde-3a13-496c-b516-76e3834bd859 · outbound

This paper cites The pascal visual object classes challenge 2006 (voc 2006) results (technical report). september 2006,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns The pascal visual object classes challenge 2006 (voc 2006) results (technical report). september 2006,

Reference 9

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raw_fallback, observed 2026-08-07T11:59:13.769034Z

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.

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Observation d2b5065d-5c7a-428c-af26-d5c2198dde7b · outbound

This paper cites The pascal visual object classes challenge 2007 (voc 2007) results (2007),.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns The pascal visual object classes challenge 2007 (voc 2007) results (2007),

Reference 10

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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.

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Observation a622fb98-ac2d-4b32-a066-ed25a8e1cee4 · outbound

This paper cites Pascal voc 2008 challenge,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Pascal voc 2008 challenge,

Reference 11

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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.

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Observation d39c9040-f6b4-4f0b-8f83-05e56a2f40bd · outbound

This paper cites The pascal visual object classes challenge 2009 (voc2009) results. http,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns The pascal visual object classes challenge 2009 (voc2009) results. http,

Reference 12

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raw_fallback, observed 2026-08-07T11:59:13.276360Z

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.

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Observation e09fed70-dbc1-46e0-9423-dd9def3b507f · outbound

This paper cites The pascal visual object classes (voc) chal- lenge,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns The pascal visual object classes (voc) chal- lenge,

Reference 13

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raw_fallback, observed 2026-08-07T11:59:13.134313Z

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.

source=pdf_text observed=2026-08-07T11:59:05.715179Z digest=sha256:4c0dd3015ca072bd15bdc8c7a1bc76b04b2f7ac85011038b06cc4dfbfa62ba02

Observation 7bbb9c86-2beb-4aa1-bf36-8070577da2d7 · outbound

This paper cites The pascal visual object classes challenge 2011 (voc2011) results, 2011< http://www. pascal-network. org/challenges,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns The pascal visual object classes challenge 2011 (voc2011) results, 2011< http://www. pascal-network. org/challenges,

Reference 14

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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.

source=pdf_text observed=2026-08-07T11:59:05.843542Z digest=sha256:be0979e4220b5d7ca582cba0433c5531309908cd22bf1d943aab657f9f03d2b7

Observation c9a0bc6f-cadf-46a3-99b5-2280799826c1 · outbound

This paper cites Imbalance problems in object detection: A review,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Imbalance problems in object detection: A review,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-07T11:59:12.830341Z

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.

source=pdf_text observed=2026-08-07T11:59:05.973684Z digest=sha256:8518f5c420a9cb033f9ec588874a8a8fb6ab02044560ecedfefe92bc0d91af5c

Observation c0ebbace-e77d-453f-98fe-eb3d5c5ea4cf · outbound

This paper cites Breaking beyond coco object detection.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Breaking beyond coco object detection

Reference 16

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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.

source=pdf_text observed=2026-08-07T11:59:06.054629Z digest=sha256:f42dad795edbeb21f32421a14ec0fdd665b30d08173032003d66b913f7739f8f

Observation 4680cbb8-44fa-4d30-821b-ec402896fb6e · outbound

This paper cites Rethinking pascal-voc and ms-coco dataset for small object detection,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Rethinking pascal-voc and ms-coco dataset for small object detection,

Reference 17

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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.

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Observation 552e095d-5ca8-4298-a0f1-798b4d37a379 · outbound

This paper cites Diagnosing State-Of-The-Art Object Proposal Methods.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Diagnosing State-Of-The-Art Object Proposal Methods

Reference 18

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local_arxiv, observed 2026-08-07T11:59:08.992631Z

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.

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Observation 52a0a048-ef9c-4cfd-a057-0638de11ae8e · outbound

This paper cites Can we trust bounding box annotations for object detection?.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Can we trust bounding box annotations for object detection?

Reference 19

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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.

source=pdf_text observed=2026-08-07T11:59:06.378470Z digest=sha256:633918b5790d6a0de9a4a0305912ba22c9b29dad31e02d26db58bfc4658bbf39

Observation 85d0ff15-e655-4f32-a5e9-40449cab02fb · outbound

This paper cites ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:59:06.491540Z digest=sha256:cc02d836ea5f0124f7946542edf679bd86dcb4213faa05824400b42a27f68b9e

Observation cead1d19-11ae-4059-9e48-7fadb8d3af95 · outbound

This paper cites Identifying label errors in object detection datasets by loss inspection,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Identifying label errors in object detection datasets by loss inspection,

Reference 21

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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.

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Observation f93f7079-7059-42d8-b79e-c25d54592080 · outbound

This paper cites Training robust object detectors from noisy category labels and imprecise bounding boxes,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Training robust object detectors from noisy category labels and imprecise bounding boxes,

Reference 22

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raw_fallback, observed 2026-08-07T11:59:11.841321Z

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.

source=pdf_text observed=2026-08-07T11:59:06.711988Z digest=sha256:40ff2260077b0658855eebc7ea4091c2de3a6d18695af80ee8e5956a30c3ed46

Observation e6c9664b-ea20-4bc6-a705-41f940e35d6e · outbound

This paper cites Robust object detection with inaccurate bounding boxes,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Robust object detection with inaccurate bounding boxes,

Reference 23

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raw_fallback, observed 2026-08-07T11:59:11.571980Z

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.

source=pdf_text observed=2026-08-07T11:59:06.826545Z digest=sha256:fad6b0c4d05945ba5340bb2be00818e97f9d3c06b51bb3f394e09b730e45b0e2

Observation ac3efe40-2a24-4d6c-ac30-dcb949aeb566 · outbound

This paper cites Pseco: Pseudo labeling and consistency training for semi-supervised object detection,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Pseco: Pseudo labeling and consistency training for semi-supervised object detection,

Reference 24

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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.

source=pdf_text observed=2026-08-07T11:59:06.974559Z digest=sha256:442cdc2acec21362e85cdb780426fe464e80bdcb68fb36e6db3b27e5881143a0

Observation d9a6457d-c4ea-457c-b517-d2d219660edf · outbound

This paper cites Dense teacher: Dense pseudo-labels for semi-supervised ob- ject detection,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Dense teacher: Dense pseudo-labels for semi-supervised ob- ject detection,

Reference 25

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raw_fallback, observed 2026-08-07T11:59:11.137104Z

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.

source=pdf_text observed=2026-08-07T11:59:07.115840Z digest=sha256:ca29ace39c3b68ab93dd07298f6d7761102b583f563bb97c6e43042541685b42

Observation 8e1249ba-f420-4d43-b205-64be8c7103e6 · outbound

This paper cites Pseudo-label enhancement for weakly supervised object detection using self- supervised vision transformer,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Pseudo-label enhancement for weakly supervised object detection using self- supervised vision transformer,

Reference 26

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raw_fallback, observed 2026-08-07T11:59:10.870016Z

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.

source=pdf_text observed=2026-08-07T11:59:07.238648Z digest=sha256:8cf2b3c151854eb429c9e30b25db6db9a8b11edd2b375c0d59ae4da03959006d

Observation 421b8526-9c04-4e7d-9b7b-cfdc649b6c81 · outbound

This paper cites Enhancing few-shot object detection through pseudo-label mining,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Enhancing few-shot object detection through pseudo-label mining,

Reference 27

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raw_fallback, observed 2026-08-07T11:59:10.607343Z

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.

source=pdf_text observed=2026-08-07T11:59:07.341421Z digest=sha256:323ba46726a991d8932a45a53a6b8c207f6b5bed4c8b06263f654fd7bdd6c305

Observation eb5d0077-059f-4fbe-a96c-986e19b09d15 · outbound

This paper cites Faster r-cnn: To- wards real-time object detection with region proposal networks,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Faster r-cnn: To- wards real-time object detection with region proposal networks,

Reference 28

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no resolver link, observed 2026-08-07T11:59:07.487405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:59:07.487405Z digest=sha256:51b5306b56c882e1c71eeda681e1da9675d9947dc4163ffcd8e54ef678313076

Observation 99c4cd5e-5283-4f4c-86aa-42b1c9090758 · outbound

This paper cites Microsoft coco: Common objects in context,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Microsoft coco: Common objects in context,

Reference 29

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raw_fallback, observed 2026-08-07T11:59:10.390663Z

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.

source=pdf_text observed=2026-08-07T11:59:07.598058Z digest=sha256:a0960b8df03050c3867fe6cb59ef1ba79ae545f0b04e22b54e81baf85604231d

Observation 60d9b03f-26a5-4d8d-a051-2d5e711c8452 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns YOLOX: Exceeding YOLO Series in 2021

Reference 30

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no resolver link, observed 2026-08-07T11:59:07.696944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:59:07.696944Z digest=sha256:a247f045cec355b061fe4598b99299d4151889c540e3eb293bf9c5fee9ab25c4

Observation 9ee7bf0c-4a69-4ee7-b452-8622359b5e36 · outbound

This paper cites Focal loss for dense object detection,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Focal loss for dense object detection,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-07T11:59:10.167208Z

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.

source=pdf_text observed=2026-08-07T11:59:07.790681Z digest=sha256:45cbe77d30aff704433f12ba412e73fd4cae0bfce7a9f7bd0ef31e5a032429bb

Observation ade7a0a5-eb4f-4b61-be5b-1ec7fa0fef52 · outbound

This paper cites Objects365: A large-scale, high-quality dataset for object detection,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Objects365: A large-scale, high-quality dataset for object detection,

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-07T11:59:09.936121Z

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.

source=pdf_text observed=2026-08-07T11:59:07.912112Z digest=sha256:dc3377e2e007096271af227924162d790b4dd0005f6ada982c9ffc2ad52b98c2

Observation 4af5539d-121b-427c-874d-65a93436f789 · outbound

This paper cites Caltech-256 object category dataset,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Caltech-256 object category dataset,

Reference 33

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raw_fallback, observed 2026-08-07T11:59:09.727512Z

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.

source=pdf_text observed=2026-08-07T11:59:08.050962Z digest=sha256:e49ff78cc528aa6c4d4d00c2694b65b9e380749f6244a9d69b27aabea24781d9

Observation a03e5c4e-7eb6-483d-9c5d-34dfa6f04417 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Imagenet: A large-scale hierarchical image database,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T11:59:08.136596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:59:08.136596Z digest=sha256:d227fee557ba40fbdbbba734a87db20147fd314d8c981f61801298187cd64ad5

Observation 3c2993d1-8e74-4286-9f13-ba51eb4f8037 · outbound

This paper cites Cifar-10 (canadian institute for advanced research),.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Cifar-10 (canadian institute for advanced research),

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:59:09.408158Z

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.

source=pdf_text observed=2026-08-07T11:59:08.242469Z digest=sha256:3af0106a9c68ade3ef67d734d8a594285ffdbd3c73a254eabdcf779b8ae8f67f

Observation a263a695-870e-40b6-b1bf-eaccf80f9beb · outbound

This paper cites Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T11:59:08.343930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:59:08.343930Z digest=sha256:a484f7ad30e72b217e3e3572141ace8827ca97c0510bd8d196b07ef9f3821fd1

Observation c22c3eee-4069-4f8f-b106-c1702f0d2e25 · outbound

This paper cites YOLOv3: An Incremental Improvement.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns YOLOv3: An Incremental Improvement

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T11:59:08.480322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:59:08.480322Z digest=sha256:7539985dcf01b7dead6048629b9e17eacaab556d6b08e54f539234b2567ccdaf

Observation 5290c3ab-9559-4473-90e4-edceb6b956dd · outbound

This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T11:59:08.589473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:59:08.589473Z digest=sha256:d1733e379522a89d7b9a9c71190d6c8bd16410f0b45d7c3a846fcaba8cd8b17f

Observation fb1ca059-7075-4de4-adc7-7398375ac90d · outbound

This paper cites Libra r-cnn: Towards balanced learning for object detection,.

Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns Libra r-cnn: Towards balanced learning for object detection,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:59:09.174525Z

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.

source=pdf_text observed=2026-08-07T11:59:08.711344Z digest=sha256:d846f791f0ffa0f2e65dcc2f8aa6453d8c43fb006e728f4838799c78b171d197

Pith citing papers

No inbound Pith citation observations are available.