Paper Citation Record · LEDGER

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 10 inbound Pith citation observations for arXiv:2509.00833.

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

pith.paper-citation-record.v1
2509.00833 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:14:15.343680Z

measured 24 of 24 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T07:37:45.280850Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

14 of 14 outbound references displayed

verified exact0
verified fuzzy2
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation bc71abf9-f551-40bb-9d5a-684c1aeb56be · outbound

This paper cites Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.292502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ce70d33-7fdf-4a67-8f05-4d15ca64a5ec · outbound

This paper cites an unresolved cited work.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-05T13:14:15.503215Z

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.

Observation d98905da-0d51-40ba-a777-39ab84cca841 · outbound

This paper cites Anomalydino: Boosting patch-based few-shot anomaly detection with dinov2.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 Anomalydino: Boosting patch-based few-shot anomaly detection with dinov2

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:14:15.491618Z

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.

Observation 2b1bba06-cfa3-46e8-aa24-b5a13b095305 · outbound

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

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 DINOv2: Learning Robust Visual Features without Supervision

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.329533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbd06ad7-5de4-40a3-960a-1aad392da16e · outbound

This paper cites DINOv3.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 DINOv3

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.332805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfe54a33-c123-4b71-bd17-da54f5fef6f0 · outbound

This paper cites Image Segmentation in Foundation Model Era: A Survey.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 Image Segmentation in Foundation Model Era: A Survey

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.343680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe3ad6e9-2977-42b1-bbf0-a083e086a490 · outbound

This paper cites Decoupled Weight Decay Regularization.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 Decoupled Weight Decay Regularization

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.316526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ab9786d-d6bd-47c8-8589-b90e152f2d99 · outbound

This paper cites DINOv3 with Test-Time Training for Medical Image Registration.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 DINOv3 with Test-Time Training for Medical Image Registration

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.336239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61f415dc-dbe3-4cbe-a4fa-e30ae53a332d · outbound

This paper cites SegDiff: Image Segmentation with Diffusion Probabilistic Models.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 SegDiff: Image Segmentation with Diffusion Probabilistic Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.297034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bc78556-802f-479b-be49-660a106a633c · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 Attention U-Net: Learning Where to Look for the Pancreas

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.325391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4b8d8a5-2c6e-431e-9dc0-283e7b8d0a15 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.301186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09973a80-48a8-4c75-b3be-1a7401f26d22 · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.321224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4862a7df-adac-46c6-9f02-60d516d76694 · outbound

This paper cites Re- visiting shadow detection: A new benchmark dataset for complex world.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 Re- visiting shadow detection: A new benchmark dataset for complex world

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:14:15.479911Z

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.

Observation 34e351ad-2916-454e-a508-60e969b055c9 · outbound

This paper cites Fast Segment Anything.

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3 Fast Segment Anything

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T13:14:15.339975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 35a9c913-463d-4651-a3ed-ef440381c3fa · inbound

Resolution scaling governs DINOv3 transfer performance in chest radiograph classification cites this paper.

Resolution scaling governs DINOv3 transfer performance in chest radiograph classification SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:06:09.087628Z

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.

Observation b97038d0-8ac0-4739-b084-520bbefd5267 · inbound

The pretraining domain outweighs the training objective in setting the privacy-utility trade-off of differentially private medical image analysis cites this paper.

The pretraining domain outweighs the training objective in setting the privacy-utility trade-off of differentially private medical image analysis SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T07:37:45.280850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf712052-4aa9-47e9-ae16-d170f5ac96c4 · inbound

LUMOS: Latent Universal Medical Priors for Segmentation cites this paper.

LUMOS: Latent Universal Medical Priors for Segmentation SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T19:46:37.475327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94ce1a21-e495-4ddc-9c09-5f0c56a0ce2d · inbound

Uncovering the Latent Potential of Deep Intermediate Representations cites this paper.

Uncovering the Latent Potential of Deep Intermediate Representations SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:36:39.247887Z

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.

Observation 2a4f8411-bef8-4a06-bc8b-1de710bbadf9 · inbound

HD-DinoMoE: A Class-Aware Hierarchical Dual Mixture-of-Experts Network for Scleral Anomaly Segmentation in Complex Acquisition Scenarios cites this paper.

HD-DinoMoE: A Class-Aware Hierarchical Dual Mixture-of-Experts Network for Scleral Anomaly Segmentation in Complex Acquisition Scenarios SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:46:45.608845Z

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.

Observation 17f73e81-95c8-412f-8021-37d0a875e6f2 · inbound

Recover Semantics First, Generate Better: Improved Latent Modeling for 3D MRI Reconstruction and Cross-Contrast Synthesis cites this paper.

Recover Semantics First, Generate Better: Improved Latent Modeling for 3D MRI Reconstruction and Cross-Contrast Synthesis SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:58:57.520535Z

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.

Observation eb55de74-7434-48da-bffe-b3c9cd6ab477 · inbound

DINO-Med3D: Bridging Dimension and Domain Gaps in Volumetric Segmentation via Progressive Adaptation cites this paper.

DINO-Med3D: Bridging Dimension and Domain Gaps in Volumetric Segmentation via Progressive Adaptation SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:19:13.031854Z

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.

Observation f422bc4b-4454-4910-b2ac-60b30e4c4734 · inbound

SemCityLoc: Aerial 6DoF Localization Using Semantic 3D City Models cites this paper.

SemCityLoc: Aerial 6DoF Localization Using Semantic 3D City Models SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-01T18:15:58.422298Z

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.

Observation 6afff8d2-88d5-4260-9bcd-9277e1b32752 · inbound

Step-Attention Refinement of DINOv3 Features for Efficient Anterior Eye Segmentation cites this paper.

Step-Attention Refinement of DINOv3 Features for Efficient Anterior Eye Segmentation SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-30T11:33:36.859421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 101ef915-fb71-48e7-a42e-7e5cb4e555ad · inbound

Step-Attention Refinement of DINOv3 Features for Efficient Anterior Eye Segmentation cites this paper.

Step-Attention Refinement of DINOv3 Features for Efficient Anterior Eye Segmentation SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T01:24:56.182970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.