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Paper Citation Record · LEDGER

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation

As of 20 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2412.05572.

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

pith.paper-citation-record.v1
2412.05572 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:40:02.322216Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T01:01:19.226387Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T01:01:19.382124Z

Reference resolution

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy19
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a575d857-e3c7-4da3-b5d4-4e3b8e5a78aa · outbound

This paper cites Domain generalization via invariant feature representation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Domain generalization via invariant feature representation,

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 97c6b7c8-9f56-481a-9a42-550176d3e6ca · outbound

This paper cites Domain generalization with adversarial feature learning,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Domain generalization with adversarial feature learning,

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 041d1174-7e16-4ad7-a7f6-9221297be808 · outbound

This paper cites Deep domain generalization via conditional invariant adversarial networks,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Deep domain generalization via conditional invariant adversarial networks,

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4e59bde6-da5f-417a-a8a3-c8aa1de7fdcf · outbound

This paper cites Generalizable medical image segmentation via random amplitude mixup and domain-specific image restoration,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Generalizable medical image segmentation via random amplitude mixup and domain-specific image restoration,

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T20:40:02.110075Z digest=sha256:df72c673f6dcfedf82c3cc5753f8e2e18c9efafada09ff85282a4d08b61bdec8

Observation 96f038cb-a3b0-43cb-9e08-738be83f2c2f · outbound

This paper cites Generalizing to unseen domains: A survey on domain generalization,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Generalizing to unseen domains: A survey on domain generalization,

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c994aa86-7482-4d26-b810-fc34f9f26353 · outbound

This paper cites Domain generalization: A survey,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Domain generalization: A survey,

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 84364ce0-f264-47ae-a109-5b985cb5021d · outbound

This paper cites Treasure in distribution: a domain randomization based multi- source domain generalization for 2d medical image segmentation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Treasure in distribution: a domain randomization based multi- source domain generalization for 2d medical image segmentation,

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T20:40:02.166153Z digest=sha256:464219ce770f95abdc12fb78ebf303023be64bf03e620331a3de6e604ba63b10

Observation a3eb7c9e-eaa7-450f-a6fd-ce0dcd6c4737 · outbound

This paper cites Seit: Structural enhancement for unsupervised image translation in frequency domain,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Seit: Structural enhancement for unsupervised image translation in frequency domain,

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c24f29b1-01eb-433a-8943-36e77a0049fd · outbound

This paper cites Mixstyle neural networks for domain generalization and adaptation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Mixstyle neural networks for domain generalization and adaptation,

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 8bf020ac-5290-453e-b839-5a662daa033a · outbound

This paper cites Learning to learn single domain generalization,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Learning to learn single domain generalization,

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d943ac71-95f4-44f6-a91a-57df21ebf56f · outbound

This paper cites Selfreg: Self-supervised contrastive regularization for domain gen- eralization,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Selfreg: Self-supervised contrastive regularization for domain gen- eralization,

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 79cfe9c2-b26a-402c-8975-2fca7c3cc1c4 · outbound

This paper cites Sepico: Semantic-guided pixel contrast for domain adaptive semantic segmentation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Sepico: Semantic-guided pixel contrast for domain adaptive semantic segmentation,

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 56a6279d-f8fc-4734-8051-f98f5c801824 · outbound

This paper cites Learning to generalize: Meta-learning for domain generalization,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Learning to generalize: Meta-learning for domain generalization,

Reference 13

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1a40d028-5b0e-410c-ae06-52447a5dd0ae · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation V-net: Fully convolutional neural networks for volumetric medical image segmentation,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T20:40:02.227175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9d555829-a825-421a-a8e4-c67196835666 · outbound

This paper cites an unresolved cited work.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 659c0bc1-29fb-4608-bde0-50e18e68cd7b · outbound

This paper cites Cddsa: Contrastive domain disentanglement and style augmentation for generalizable medical image segmentation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Cddsa: Contrastive domain disentanglement and style augmentation for generalizable medical image segmentation,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 860bad92-a8ce-48b2-ab33-ac520adb4c65 · outbound

This paper cites Learning robust shape regularization for generalizable medical image segmentation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Learning robust shape regularization for generalizable medical image segmentation,

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 06a74489-4cf7-42c4-83a8-0c4f5c3a9d01 · outbound

This paper cites Domain generalization with correlated style uncertainty,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Domain generalization with correlated style uncertainty,

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d23e7837-eb92-4d6a-9802-d040a51b9ec5 · outbound

This paper cites From denoising training to test-time adaptation: Enhancing domain generalization for medical image segmentation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation From denoising training to test-time adaptation: Enhancing domain generalization for medical image segmentation,

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 37988f01-b3e9-4111-b3f7-74d9e4043804 · outbound

This paper cites Dofe: Domain-oriented feature embedding for generalizable fundus image segmentation on unseen datasets,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Dofe: Domain-oriented feature embedding for generalizable fundus image segmentation on unseen datasets,

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 2dc6f400-df72-41c9-a9d3-d5be00e7a85f · outbound

This paper cites Shape-aware meta-learning for generalizing prostate mri segmentation to unseen domains,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Shape-aware meta-learning for generalizing prostate mri segmentation to unseen domains,

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 63a4a33a-fc95-4bf6-81a0-fccb143b0ec7 · outbound

This paper cites Domain specific convolution and high frequency reconstruction based unsupervised domain adap- tation for medical image segmentation,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Domain specific convolution and high frequency reconstruction based unsupervised domain adap- tation for medical image segmentation,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:40:02.404822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-11T20:40:02.297149Z digest=sha256:8aa94da6268cb0a30ba011e7030ec0f2cf1bdf1d88244a6b7027f06f0eaf0136

Observation c9620635-c9d9-4c90-a55d-0bc3252fbbb6 · outbound

This paper cites Deep residual learning for image recognition,.

From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation Deep residual learning for image recognition,

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:40:02.322216Z digest=sha256:3bd10faed11a1ecf2d601d0fa38c406ae78946802ae4955a8bc1c996053d42d1

Pith citing papers

Observation bde46a2f-7c9d-4856-94b4-1e655f96fa25 · inbound

DistMedVL: Distributional Vision-Language Alignment for Uncertainty-Aware Medical Image Segmentation cites this paper.

DistMedVL: Distributional Vision-Language Alignment for Uncertainty-Aware Medical Image Segmentation From Deterministic to Probabilistic: A Novel Perspective on Domain Generalization for Medical Image Segmentation

Reference 19

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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