Paper Citation Record · LEDGER

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery

As of 7 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2607.14338.

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

pith.paper-citation-record.v1
2607.14338 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T02:31:02.860881Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

48 of 48 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b17ff350-25b9-425a-b8cc-eac0f4974348 · outbound

This paper cites 1986 , isbn =.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery 1986 , isbn =

Reference 1

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Observation cd48f361-581c-43e0-b314-21c670beffce · outbound

This paper cites an unresolved cited work.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Unresolved cited work

Reference 2

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Observation ef10a9cb-3556-479c-9555-a6282484d9fd · outbound

This paper cites Journal of Digital Imaging , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Journal of Digital Imaging , volume=

Reference 3

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Observation 181f3393-61ec-4277-b7ce-f43cae7df8fe · outbound

This paper cites Sensors , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Sensors , volume=

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T02:30:58.824836Z

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Observation 6b726047-a515-4932-999c-5cba42f4fb3d · outbound

This paper cites International Conference on Medical Image Computing and Computer-Assisted Intervention , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International Conference on Medical Image Computing and Computer-Assisted Intervention , pages=

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Observation 0d239eba-fb6b-4052-95c8-fb14fd995d2d · outbound

This paper cites Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed

Reference 6

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This paper cites International conference on machine learning , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International conference on machine learning , pages=

Reference 7

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Observation c3a0bdd6-1bfb-4ba3-96a4-eb625234eabf · outbound

This paper cites IEEE transactions on medical imaging , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery IEEE transactions on medical imaging , volume=

Reference 8

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Observation 71f5c95d-58b5-494f-86fa-05781d0d2895 · outbound

This paper cites CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss

Reference 9

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Observation 23071c18-9ba4-4ba7-a548-c5430e8cc4d3 · outbound

This paper cites 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) , pages=

Reference 10

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Observation 78f5a7c6-89f4-42fe-8eed-184d4f3a7ca8 · outbound

This paper cites Computerized Medical Imaging and Graphics , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Computerized Medical Imaging and Graphics , volume=

Reference 11

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Observation 02a32949-f724-4547-b1b6-8e8aa684c6a4 · outbound

This paper cites 2016 fourth international conference on 3D vision (3DV) , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery 2016 fourth international conference on 3D vision (3DV) , pages=

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T02:30:59.399947Z

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Observation 8aa21f19-e931-41b2-aed8-8e113bb80e8d · outbound

This paper cites Journal of the American statistical Association , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Journal of the American statistical Association , volume=

Reference 13

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Observation 5ab2a434-4985-4c65-b944-4351037500ab · outbound

This paper cites Computerized Medical Imaging and Graphics , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Computerized Medical Imaging and Graphics , volume=

Reference 14

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Observation e606e7f7-0980-4eff-9582-4f0fe70d9c28 · outbound

This paper cites International workshop on machine learning in medical imaging , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International workshop on machine learning in medical imaging , pages=

Reference 15

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Observation 3ef761cb-8775-4584-b368-99823ed129f8 · outbound

This paper cites Nature methods , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Nature methods , volume=

Reference 16

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Observation a171d014-2785-474a-816e-9924d3c7d404 · outbound

This paper cites Scientific data , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Scientific data , volume=

Reference 17

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Observation 08905ce0-ad40-4ef6-8648-3e702588df09 · outbound

This paper cites arXiv preprint arXiv:2504.12527 , year=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery arXiv preprint arXiv:2504.12527 , year=

Reference 18

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Observation a6727e2e-da0d-424c-a10d-074045786c88 · outbound

This paper cites Academic radiology , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Academic radiology , volume=

Reference 19

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Observation 63e1e043-cb0c-4e44-afcb-7aaad0afaf76 · outbound

This paper cites The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

Reference 20

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Observation 8f38bf65-007a-4798-8af7-452fa6771772 · outbound

This paper cites Advances in neural information processing systems , volume=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Advances in neural information processing systems , volume=

Reference 21

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Observation cb09e73f-cb77-4d2e-91b1-801d43a2d4f4 · outbound

This paper cites International Conference on Medical image computing and computer-assisted intervention , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International Conference on Medical image computing and computer-assisted intervention , pages=

Reference 22

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Observation a42d7f52-9ea3-458b-a137-cecf4266b195 · outbound

This paper cites Effect of the output activation function on the probabilities and errors in medical image segmentation.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Effect of the output activation function on the probabilities and errors in medical image segmentation

Reference 23

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Observation efb5adda-bc22-4e5a-821f-37a6552be735 · outbound

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

Reference 24

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Observation 434e17ec-7d94-4062-9200-9ca1366f4832 · outbound

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Monthly weather review , volume=

Reference 25

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This paper cites international conference on machine learning , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery international conference on machine learning , pages=

Reference 26

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Observation d8192da0-3061-49e9-b5dc-2e5edc513efe · outbound

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Advances in neural information processing systems , volume=

Reference 27

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 28

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery 2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019) , pages=

Reference 29

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Advances in large margin classifiers , volume=

Reference 30

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , pages=

Reference 31

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) , pages=

Reference 32

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Unresolved cited work

Reference 33

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Medical Image Analysis , volume=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Medical imaging 2019: image Processing , volume=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International MICCAI Brainlesion Workshop , pages=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Journal of the American Medical Informatics Association , volume=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Advances in neural information processing systems , volume=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Medical Image Analysis , volume=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery international conference on information processing in medical imaging , pages=

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This paper cites International conference on medical image computing and computer-assisted intervention , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International conference on medical image computing and computer-assisted intervention , pages=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Medical Image Analysis , volume=

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International Conference on Information Processing in Medical Imaging , pages=

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Observation e1cbec84-dd73-4a88-8888-00eb3eee3625 · outbound

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Beyond scalar losses: calibrating segmentation models via gradient vector field surgery Primus: Enforcing Attention Usage for 3D Medical Image Segmentation

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This paper cites International Conference on Medical Image Computing and Computer-Assisted Intervention , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International Conference on Medical Image Computing and Computer-Assisted Intervention , pages=

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This paper cites International conference on medical image computing and computer-assisted intervention , pages=.

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery International conference on medical image computing and computer-assisted intervention , pages=

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-02T02:31:02.860881Z

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Pith citing papers

No inbound Pith citation observations are available.