Paper Citation Record · LEDGER

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2507.16337.

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

pith.paper-citation-record.v1
2507.16337 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

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measured 42 of 42 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 2026-08-01T17:19:30.684784Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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verified fuzzy33
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c029b87c-a331-479b-b690-d15ba7101cab · outbound

This paper cites A multi-centre polyp detection and segmentation dataset for generalisability assessment.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution A multi-centre polyp detection and segmentation dataset for generalisability assessment

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:07.452445Z

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Observation b156d543-03d7-404b-9584-981963bfad45 · outbound

This paper cites ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models

Reference 2

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Observation 82595064-9565-4400-8a85-02a3dfaeefbc · outbound

This paper cites Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:07.180241Z

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Observation 829d52dc-dc33-4d12-a9e6-5c20cc40c205 · outbound

This paper cites Semantically mean- ingful class prototype learning for one-shot image segmenta- tion.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Semantically mean- ingful class prototype learning for one-shot image segmenta- tion

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:06.923298Z

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Observation 570f41df-f48d-42f4-b6e6-bcd708970d4d · outbound

This paper cites A mutually supervised graph attention network for few-shot segmentation: The perspective of fully utilizing limited samples.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution A mutually supervised graph attention network for few-shot segmentation: The perspective of fully utilizing limited samples

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:06.663781Z

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Observation 32416433-954c-483d-900a-364bc08ec4b4 · outbound

This paper cites Coinnet: A convolution-involution net- work with a novel statistical attention for automatic polyp segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Coinnet: A convolution-involution net- work with a novel statistical attention for automatic polyp segmentation

Reference 6

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Observation 6a81db01-15ef-4618-aafd-e7e1134bdab3 · outbound

This paper cites Kvasir-seg: A segmented polyp dataset.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Kvasir-seg: A segmented polyp dataset

Reference 7

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Observation 8211e29c-3edc-4b78-9730-866ce1095f2b · outbound

This paper cites Transnetr: transformer-based residual network for polyp segmentation with multi-center out-of-distribution testing.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Transnetr: transformer-based residual network for polyp segmentation with multi-center out-of-distribution testing

Reference 8

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Observation a5fb2733-d03b-40d6-bd61-ec2ce10a6cd2 · outbound

This paper cites Learning what not to segment: A new perspective on few- shot segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Learning what not to segment: A new perspective on few- shot segmentation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:05.650994Z

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Observation 39e98e9f-57a3-46f7-bfdd-10c2d410de54 · outbound

This paper cites Cross-domain few-shot se- mantic segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Cross-domain few-shot se- mantic segmentation

Reference 10

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Observation 77f17ac7-04f3-4f9f-8413-ae5154ee2bd6 · outbound

This paper cites Semantic-SAM: Segment and Recognize Anything at Any Granularity.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Semantic-SAM: Segment and Recognize Anything at Any Granularity

Reference 11

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Observation 2bd53d32-f797-4c39-be63-31ff48b848cc · outbound

This paper cites Adaptive prototype learning and allocation for few-shot segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Adaptive prototype learning and allocation for few-shot segmentation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:05.155563Z

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Observation 0b2cdfb6-182f-4413-9e1d-902cda649822 · outbound

This paper cites Tcc- net: Temporally consistent context-free network for semi- supervised video polyp segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Tcc- net: Temporally consistent context-free network for semi- supervised video polyp segmentation

Reference 13

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Observation e1d68c34-b345-418a-9ff2-c3e9b6c94fb3 · outbound

This paper cites Polyp-sam: Transfer sam for polyp segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Polyp-sam: Transfer sam for polyp segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:04.705019Z

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Observation 28c5ad82-41a0-4f0a-add6-03a4bc5b073b · outbound

This paper cites Clip is also an efficient segmenter: A text-driven approach for weakly supervised semantic segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Clip is also an efficient segmenter: A text-driven approach for weakly supervised semantic segmentation

Reference 15

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Observation ced99fdc-69c0-4fb7-b8d0-68a5dabb9814 · outbound

This paper cites Inter- mediate prototype mining transformer for few-shot semantic segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Inter- mediate prototype mining transformer for few-shot semantic segmentation

Reference 16

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Observation f8ac10fd-a231-4e2b-87d5-c4c685a1b3b3 · outbound

This paper cites Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching

Reference 17

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Observation 22a5a3da-fbe1-481a-a3f6-2ad3d6631032 · outbound

This paper cites Bad results with multiple point prompts.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Bad results with multiple point prompts

Reference 18

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Observation 58bc16d4-b03e-4a3b-9a55-8865dcc85fc2 · outbound

This paper cites Segment anything in medical images.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Segment anything in medical images

Reference 19

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Observation 0cefd05b-29b7-4810-b2c9-dfbff227ab49 · outbound

This paper cites Segic: Unleashing the emergent correspondence for in-context segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Segic: Unleashing the emergent correspondence for in-context segmentation

Reference 20

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Observation 1b4ebbc9-3273-46c0-8363-9856e2df5ba8 · outbound

This paper cites Cross-domain few-shot segmentation via iterative support-query correspon- dence mining.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Cross-domain few-shot segmentation via iterative support-query correspon- dence mining

Reference 21

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Observation deb6e327-4a64-4502-8ee5-c2a5c0b01278 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution DINOv2: Learning Robust Visual Features without Supervision

Reference 22

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This paper cites Fuzzynet: A fuzzy attention module for polyp segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Fuzzynet: A fuzzy attention module for polyp segmentation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:03.072448Z

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Observation 944956be-cebf-4911-a17c-c7886ac40b95 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Learning transferable visual models from natural language supervi- sion

Reference 24

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This paper cites Medical im- age segmentation via cascaded attention decoding.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Medical im- age segmentation via cascaded attention decoding

Reference 25

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Observation 1dc7f408-b570-4546-a947-82101ae5a716 · outbound

This paper cites Pp-sam: Perturbed prompts for robust adaption of segment anything model for polyp segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Pp-sam: Perturbed prompts for robust adaption of segment anything model for polyp segmentation

Reference 26

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Observation e73c48d8-4c7c-4944-8cc0-852fd2afa74b · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution SAM 2: Segment Anything in Images and Videos

Reference 27

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Observation e475f60d-40ee-4532-8b23-86d6f1c9591e · outbound

This paper cites Piccolo white-light and narrow- band imaging colonoscopic dataset: A performance compar- ative of models and datasets.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Piccolo white-light and narrow- band imaging colonoscopic dataset: A performance compar- ative of models and datasets

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:02.276084Z

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Observation a49da3f4-ea76-4d0b-b939-1d7ae4e9ab0e · outbound

This paper cites Dense cross-query-and-support attention weighted mask aggrega- tion for few-shot segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Dense cross-query-and-support attention weighted mask aggrega- tion for few-shot segmentation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:02.031523Z

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Observation d3eeb39d-8d7b-4530-86ed-c0d3f9ee7cce · outbound

This paper cites Johansen, Dag Johansen, Michael A.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Johansen, Dag Johansen, Michael A

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:01.761344Z

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Observation 8835abe4-4d7f-4e19-89bf-9141e9df8b84 · outbound

This paper cites Automated polyp detection in colonoscopy videos using shape and context information.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Automated polyp detection in colonoscopy videos using shape and context information

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:01.463063Z

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Observation b3ab80c9-b4de-4404-b52e-81a40c5e5dff · outbound

This paper cites Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medi- cal images.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medi- cal images

Reference 32

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Observation 583c8165-bebd-4451-8628-8528fcaeb645 · outbound

This paper cites S 2 me: Spatial-spectral mutual teaching and ensemble learning for scribble-supervised polyp seg- mentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution S 2 me: Spatial-spectral mutual teaching and ensemble learning for scribble-supervised polyp seg- mentation

Reference 33

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Observation db0d42f0-e5ac-48c6-80f9-c5b396d2dcfd · outbound

This paper cites Xbound-former: Toward cross-scale boundary modeling in transformers.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Xbound-former: Toward cross-scale boundary modeling in transformers

Reference 34

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This paper cites Seggpt: Towards seg- menting everything in context.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Seggpt: Towards seg- menting everything in context

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:00.411972Z

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Observation fa5eb08d-4b85-4bbc-947f-b5b365e2b149 · outbound

This paper cites Shallow attention network for polyp seg- mentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Shallow attention network for polyp seg- mentation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:19:00.152675Z

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Observation 44a02640-240e-493e-827f-c6a0318152a5 · outbound

This paper cites Eviprompt: A training-free evidential prompt generation method for adapting segment anything model in medical im- ages.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Eviprompt: A training-free evidential prompt generation method for adapting segment anything model in medical im- ages

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:18:59.971156Z

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Observation 7c058081-de9d-4111-97e7-c3c6864fccc8 · outbound

This paper cites Mianet: Aggregating unbiased instance and general informa- tion for few-shot semantic segmentation.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Mianet: Aggregating unbiased instance and general informa- tion for few-shot semantic segmentation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:18:59.698007Z

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Observation a4a8dfe0-f352-430d-8e1a-948e246bb639 · outbound

This paper cites Few-shot segmentation via cycle-consistent trans- former.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Few-shot segmentation via cycle-consistent trans- former

Reference 39

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Observation 6a20726f-fafa-4c05-8960-617bb4d76f25 · outbound

This paper cites Personalize Segment Anything Model with One Shot.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Personalize Segment Anything Model with One Shot

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T15:18:59.097141Z

Source-reported events for the cited work

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Observation 02e3c77c-cbd3-4291-bd72-7bff3b6b69ea · outbound

This paper cites Cross-level feature aggre- gation network for polyp segmentation.Pattern Recognition, 140:109555, 2023.

One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution Cross-level feature aggre- gation network for polyp segmentation.Pattern Recognition, 140:109555, 2023

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:18:59.473872Z

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Pith citing papers

Observation dd486ad1-80bf-4f43-8265-a44669dd11bc · inbound

Memory-Supported Synergistic Adaptation for Training-Free Test-Time Medical Image Segmentation cites this paper.

Memory-Supported Synergistic Adaptation for Training-Free Test-Time Medical Image Segmentation One Polyp Identifies All: One-Shot Polyp Segmentation with SAM via Cascaded Priors and Iterative Prompt Evolution

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T17:19:30.684784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.