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Paper Citation Record · LEDGER

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation

As of 10 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2502.02340.

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

pith.paper-citation-record.v1
2502.02340 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T12:34:11.754991Z

measured 30 of 30 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:22:24.450368Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:22:32.161802Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact1
  • verified fuzzy20
  • unresolved8
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b7060f04-c5dd-4e1a-9a4f-2f61c642a50c · outbound

This paper cites Medical image segmentation using deep learning: A survey,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Medical image segmentation using deep learning: A survey,

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 dcafecaa-98ad-4f06-8ad0-e916759cf289 · outbound

This paper cites Deep learning tech- niques for medical image segmentation: achievements and challenges,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Deep learning tech- niques for medical image segmentation: achievements and challenges,

Reference 2

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raw_fallback, observed 2026-08-09T12:34:12.135862Z

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 bcb40672-7a23-4a4c-b611-143b9a336b12 · outbound

This paper cites Transfer learning techniques for medical image analysis: A review,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Transfer learning techniques for medical image analysis: A review,

Reference 3

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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 de0895d9-32c3-43d8-bb50-a07e41784e6f · outbound

This paper cites Transfer learning in med- ical image segmentation: New insights from analysis of the dynamics of model parameters and learned representations,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Transfer learning in med- ical image segmentation: New insights from analysis of the dynamics of model parameters and learned representations,

Reference 4

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raw_fallback, observed 2026-08-09T12:34:12.109283Z

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 de3ba1ef-dfa3-4782-b570-5162f280571f · outbound

This paper cites A survey on transfer learning,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation A survey on transfer learning,

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:34:11.655527Z digest=sha256:54550cd32f5a196fd7f3ebaf3aa776b4105d5fa3d4c5fd7f54243280bcde057f

Observation 53ccd64a-b5cc-4b04-bad6-9c8ddb9b3fd0 · outbound

This paper cites Characterizing and avoiding negative transfer,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Characterizing and avoiding negative transfer,

Reference 6

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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 3520b19b-372f-4820-98e5-490a085e94a4 · outbound

This paper cites Domain adaptation for medical image analysis: a survey,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Domain adaptation for medical image analysis: a survey,

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c0abd5eb-b879-45a3-8564-569b594173e3 · outbound

This paper cites A survey on negative transfer,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation A survey on negative transfer,

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.

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Observation c4824f2a-bc74-43b9-b2ac-3132314996a1 · outbound

This paper cites Finding the most trans- ferable tasks for brain image segmentation,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Finding the most trans- ferable tasks for brain image segmentation,

Reference 9

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raw_fallback, observed 2026-08-09T12:34:12.049754Z

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 e76b0ed1-32a2-485f-801d-46d67295fd3d · outbound

This paper cites A cross-dataset adaptive domain selection transfer learning framework for motor imagery-based brain-computer interfaces,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation A cross-dataset adaptive domain selection transfer learning framework for motor imagery-based brain-computer interfaces,

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 fdbdfc95-ab7f-4f28-950a-2f22061f21d0 · outbound

This paper cites Non-negative transfer learning with consistent inter-domain distribution,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Non-negative transfer learning with consistent inter-domain distribution,

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 d73a7354-0d01-4f03-933c-1d4fc4eba5fc · outbound

This paper cites Dual transfer learning,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Dual transfer learning,

Reference 12

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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 1036a1d4-cf27-42a8-a8a9-88ceca956fe0 · outbound

This paper cites A kernel two-sample test,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation A kernel two-sample test,

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fbfca59f-15d9-487d-9ae0-5cd641d111f8 · outbound

This paper cites On information and sufficiency,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation On information and sufficiency,

Reference 14

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Unavailable: canonical work link unavailable.

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Observation a64f7ac2-23ad-4e74-a448-70cb4d634b0c · outbound

This paper cites Improving eeg-based emotion classification using conditional transfer learning,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Improving eeg-based emotion classification using conditional transfer learning,

Reference 15

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raw_fallback, observed 2026-08-09T12:34:11.977315Z

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 c74a1c9f-46d6-4024-b3e9-77d09ef3ca8b · outbound

This paper cites Transferability and hardness of supervised classification tasks,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Transferability and hardness of supervised classification tasks,

Reference 16

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raw_fallback, observed 2026-08-09T12:34:11.963973Z

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 268a0646-247b-4cbf-8b96-75092b8fd641 · outbound

This paper cites An information-theoretic approach to transferability in task transfer learning,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation An information-theoretic approach to transferability in task transfer learning,

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 c4efb0ac-e315-427f-8c9c-30ace11c1750 · outbound

This paper cites Leep: A new measure to evaluate transferability of learned representations,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Leep: A new measure to evaluate transferability of learned representations,

Reference 18

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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 022b378b-4597-486e-9e73-5d86a50f8cd0 · outbound

This paper cites Logme: Practical assessment of pre-trained models for transfer learning,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Logme: Practical assessment of pre-trained models for transfer learning,

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-09T12:34:11.924317Z

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 e548a3f4-c850-42ea-a3d5-6607228b81ef · outbound

This paper cites Otce: A transferability metric for cross- domain cross-task representations,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Otce: A transferability metric for cross- domain cross-task representations,

Reference 20

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raw_fallback, observed 2026-08-09T12:34:11.910234Z

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 8eb65e16-9cba-4621-af20-c7477086e999 · outbound

This paper cites Where and how to transfer: Knowledge aggregation-induced transferability perception for unsupervised domain adaptation,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Where and how to transfer: Knowledge aggregation-induced transferability perception for unsupervised domain adaptation,

Reference 21

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raw_fallback, observed 2026-08-09T12:34:11.896781Z

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 4459e4cc-244d-4682-b973-e14d49b746d6 · outbound

This paper cites Efficient prediction of model transferability in semantic segmentation tasks,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Efficient prediction of model transferability in semantic segmentation tasks,

Reference 22

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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 f4cfcc03-5ccb-43c1-8074-e2bc045e20dc · outbound

This paper cites Deep semantic segmentation of natural and medical images: a review,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Deep semantic segmentation of natural and medical images: a review,

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-09T12:34:11.868977Z

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 4e470f9a-01ae-42da-8fa4-446b3653d9c1 · outbound

This paper cites The Federated Tumor Segmentation (FeTS) Challenge.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation The Federated Tumor Segmentation (FeTS) Challenge

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation dfd5242a-a518-461f-a494-5128e8117ced · outbound

This paper cites OpenFL: An open-source framework for Federated Learning.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation OpenFL: An open-source framework for Federated Learning

Reference 25

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no resolver link, observed 2026-08-09T12:34:11.739949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:34:11.739949Z digest=sha256:94c055899c38796affed8691ea4339469bbbb56168da7b76349c1262201abf90

Observation 02e04cb9-994a-48dc-8717-716ba7e0f08f · outbound

This paper cites Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features,

Reference 26

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no resolver link, observed 2026-08-09T12:34:11.744444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a6c3b1cc-f362-4cc1-a116-f9b87da83da2 · outbound

This paper cites Multi-site infant brain segmentation algorithms: the iseg-2019 challenge,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Multi-site infant brain segmentation algorithms: the iseg-2019 challenge,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-09T12:34:11.847137Z

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 29ba9c41-0dc3-4bb2-9784-b40d87dedc47 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation U-net: Convolutional networks for biomedical image segmentation,

Reference 28

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no resolver link, observed 2026-08-09T12:34:11.751491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e01ddc7f-1dc3-44ae-b77e-c3e3e4113008 · outbound

This paper cites Transfer learning with class-weighted and focal loss function for automatic skin cancer classification.

Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation Transfer learning with class-weighted and focal loss function for automatic skin cancer classification

Reference 29

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local_arxiv, observed 2026-08-09T12:34:11.796430Z

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=2026-08-09T12:34:11.754991Z digest=sha256:ef74755a97f1af97e3b7d604eff642f5eed6038b535a735af6004493529c060c

Pith citing papers

Observation bce40d5c-2352-4754-933c-8c6608dd42e9 · inbound

Understanding Knowledge Transferability for Transfer Learning: A Survey cites this paper.

Understanding Knowledge Transferability for Transfer Learning: A Survey Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation

Reference 22

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local_arxiv, observed 2026-08-06T20:22:32.200391Z

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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