Paper Citation Record · LEDGER

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation

As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 2 inbound Pith citation observations for arXiv:2501.16246.

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

pith.paper-citation-record.v1
2501.16246 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:40:59.155668Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:40:59.050415Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:56:04.519377Z

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy19
unresolved3
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c2dd954a-a1f9-45ea-8787-cf5f5f3c16e5 · outbound

This paper cites CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T13:40:59.050415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b2d81a9-c15a-409f-a239-3746022f9650 · outbound

This paper cites an image of brain tissue showing typical signal intensity without any re- gions of abnormal intensity or suspicious mass.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation an image of brain tissue showing typical signal intensity without any re- gions of abnormal intensity or suspicious mass

Reference 2

Resolution: malformed identifier; raw_fallback, observed 2026-08-10T13:40:59.524302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 090a126b-f4c1-4d43-883e-ac4707f51f87 · outbound

This paper cites Dataset and Implementation We evaluated our method on the BraTS2020 that comprises 369 cases each containing 3D volumes in four modalities.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Dataset and Implementation We evaluated our method on the BraTS2020 that comprises 369 cases each containing 3D volumes in four modalities

Reference 3

Resolution: malformed identifier; raw_fallback, observed 2026-08-10T13:40:59.510526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 01a52424-4aa0-45e4-b45c-f1363d312ff5 · outbound

This paper cites It uses CLIP-derived image labels to supervise a classification network with Adaptive Masking- based Data Augmentation for enhanced CAM.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation It uses CLIP-derived image labels to supervise a classification network with Adaptive Masking- based Data Augmentation for enhanced CAM

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.495968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c5fa36bf-4f52-4ffe-839f-4cdfd8ce41c1 · outbound

This paper cites Ethical ap- proval was not required as confirmed by the license attached with the open-access data.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Ethical ap- proval was not required as confirmed by the license attached with the open-access data

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.480267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 54ed658a-7f9e-45a0-9411-26ca3a4b2389 · outbound

This paper cites an unresolved cited work.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-10T13:40:59.466680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ab467961-e990-43fd-90c1-2514dde30f54 · outbound

This paper cites Automatic brain tumor segmentation based on cascaded convolutional neural networks with uncertainty estimation,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Automatic brain tumor segmentation based on cascaded convolutional neural networks with uncertainty estimation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.453337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e67e2588-8708-4572-b94c-2d4d4602cf10 · outbound

This paper cites Deep learning models and traditional automated techniques for brain tumor segmentation in MRI: a review,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Deep learning models and traditional automated techniques for brain tumor segmentation in MRI: a review,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.439143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6f8f3eb2-9a4c-4ebf-8f96-4839769b46aa · outbound

This paper cites Self-semantic contour adaptation for cross modality brain tumor segmentation,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Self-semantic contour adaptation for cross modality brain tumor segmentation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.424285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 13a7103a-dd39-4ce0-9c7c-bf4e4763d9cd · outbound

This paper cites Brain tumor segmentation based on a hybrid clustering technique,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Brain tumor segmentation based on a hybrid clustering technique,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.409862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eb1184b4-1807-472b-b285-6d4cebb1eecb · outbound

This paper cites Level set method with automatic selective local statistics for brain tumor segmentation in MR images,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Level set method with automatic selective local statistics for brain tumor segmentation in MR images,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.395464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 50158ff8-6c86-4e1f-9d10-4984ba1c4900 · outbound

This paper cites Bayesian skip-autoencoders for un- supervised hyperintense anomaly detection in high res- olution brain MRI,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Bayesian skip-autoencoders for un- supervised hyperintense anomaly detection in high res- olution brain MRI,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.381236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 97312552-928a-44ff-93f5-0064743c04d1 · outbound

This paper cites Unsupervised region-based anomaly detection in brain MRI with ad- versarial image inpainting,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Unsupervised region-based anomaly detection in brain MRI with ad- versarial image inpainting,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.367424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 30232c60-41c1-4fc4-9e59-c18dff08a574 · outbound

This paper cites Constrained unsupervised anomaly segmentation,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Constrained unsupervised anomaly segmentation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.353662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6f92be96-cda7-4e92-a26b-98e9f9f9a6ab · outbound

This paper cites Self- supervised tumor segmentation with sim2real adapta- tion,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Self- supervised tumor segmentation with sim2real adapta- tion,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.340055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6c5960df-bd46-44d7-ac85-bf0b75e24190 · outbound

This paper cites Segment anything,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Segment anything,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.325735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b66695eb-c01c-494a-ab1d-5f7f4d714b61 · outbound

This paper cites Test-time adap- tation with SaLIP: a cascade of SAM and CLIP for zero- shot medical image segmentation,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Test-time adap- tation with SaLIP: a cascade of SAM and CLIP for zero- shot medical image segmentation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.310420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4bde4296-335e-451b-bd0a-edc94ba1c955 · outbound

This paper cites Learning transferable visual models from natural lan- guage supervision,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Learning transferable visual models from natural lan- guage supervision,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.294313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9117d8e6-8200-430e-bb59-6d70d6e01b2e · outbound

This paper cites Im- plicit field learning for unsupervised anomaly detection in medical images,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Im- plicit field learning for unsupervised anomaly detection in medical images,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.279896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 827b3ded-cc4a-47a8-ba59-37d5677c4a4b · outbound

This paper cites Layercam: Explor- ing hierarchical class activation maps for localization,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Layercam: Explor- ing hierarchical class activation maps for localization,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.265218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a04ce3d9-d349-430e-80da-d202ee8bd7dc · outbound

This paper cites Learning deep features for discriminative localization,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Learning deep features for discriminative localization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.250696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 00196902-f1a4-4eb9-b730-abc5394a2c9a · outbound

This paper cites Grad-cam: Visual explanations from deep net- works via gradient-based localization,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Grad-cam: Visual explanations from deep net- works via gradient-based localization,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.236722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b56feffe-f2d2-48c2-a57f-732c612867de · outbound

This paper cites Deep residual learning for image recognition,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation Deep residual learning for image recognition,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T13:40:59.151265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdbef989-e779-4793-b214-feab72648741 · outbound

This paper cites 3D U-Net: learning dense volumetric segmentation from sparse an- notation,.

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation 3D U-Net: learning dense volumetric segmentation from sparse an- notation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T13:40:59.212376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation c2dd954a-a1f9-45ea-8787-cf5f5f3c16e5 · inbound