Paper Citation Record · LEDGER

GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2501.12844.

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

pith.paper-citation-record.v1
2501.12844 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:19:39.297253Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T05:41:02.337122Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cc78ee30-9b42-49da-9c72-395193677c1e · inbound

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction cites this paper.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T18:19:39.297253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b26af42b-fdcf-4005-b805-1f4b94f0a0a4 · inbound

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation cites this paper.

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-08T19:33:21.530680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc65e7c0-ccea-46a0-b602-82a8332fe21e · inbound

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation cites this paper.

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T05:03:37.291706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f420e6a7-5d32-45ff-9649-900a76a3f5e7 · inbound

MARL-MambaContour: Unleashing Multi-Agent Deep Reinforcement Learning for Active Contour Optimization in Medical Image Segmentation cites this paper.

MARL-MambaContour: Unleashing Multi-Agent Deep Reinforcement Learning for Active Contour Optimization in Medical Image Segmentation GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

Reference 156

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:07.847863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10226bcc-f05f-4cd8-9e39-a4174f69d9fb · inbound

CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation cites this paper.

CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

Reference 114

Resolution: unresolved; no resolver link, observed 2026-08-06T21:54:43.655950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41eac1b0-cdf4-4bdf-863e-1fd282e2c195 · inbound

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation cites this paper.

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-10T05:41:02.338709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.