Paper Citation Record · LEDGER

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers

As of 9 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2509.06885.

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

pith.paper-citation-record.v1
2509.06885 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:02:49.986457Z

measured 17 of 17 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

verified exact0
verified fuzzy1
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation beeb52b5-98d5-444e-a178-7764c11f2a4f · outbound

This paper cites Unsupervised Learning of Visual Features by Contrasting Cluster Assignments.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Unsupervised Learning of Visual Features by Contrasting Cluster Assignments

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.917803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6765783-74eb-4aa6-974f-d4b31ae09d78 · outbound

This paper cites Contrastive learning of global and local features for medical image segmentation with limited annotations.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Contrastive learning of global and local features for medical image segmentation with limited annotations

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T23:02:50.278537Z

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 c22147b7-6550-4f90-b417-d9e3baa31478 · outbound

This paper cites A Simple Framework for Contrastive Learning of Visual Representations.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers A Simple Framework for Contrastive Learning of Visual Representations

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.928644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa6d0eae-5970-4a30-bd3a-e91595f67937 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.933748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 721a89fa-b430-44c2-bd2d-eae07884e6c5 · outbound

This paper cites Bootstrap your own latent: A new approach to self-supervised Learning.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Bootstrap your own latent: A new approach to self-supervised Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.943532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 605c6a3d-08e5-4bbd-ab21-9d058fc3bd38 · outbound

This paper cites UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.957998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2faeec3-ee9e-43dc-9a9c-0930f73cff53 · outbound

This paper cites Segment Anything.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Segment Anything

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.967451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7c4456a-6ba3-4065-b42c-afd37677612c · outbound

This paper cites Frontiers in Genet- ics 12, 639930.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Frontiers in Genet- ics 12, 639930

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-08-04T23:02:50.076814Z

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 50038ca8-e954-4570-832f-b705424c8e29 · outbound

This paper cites BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net models.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net models

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T23:02:50.053349Z

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 738e9194-03c1-4d8d-98bf-f53613c716fe · outbound

This paper cites Medical Image Analysis 53, 197–207.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Medical Image Analysis 53, 197–207

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-08-04T23:02:50.030550Z

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 18dafdb8-82e3-4b80-b48b-5a8515414bbe · outbound

This paper cites IEEE Transactions on Medical Imaging 34, 1993–2024.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers IEEE Transactions on Medical Imaging 34, 1993–2024

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T23:02:50.345736Z

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 a5bce1af-75b6-4fd4-92e5-2c97b8d5b5e4 · outbound

This paper cites an unresolved cited work.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Unresolved cited work

Reference 2016

Resolution: metadata mismatch; arxiv_id, observed 2026-08-04T23:02:50.184018Z

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 e5c5b2b2-8bf9-461a-8bab-ee15b7b42c4d · outbound

This paper cites Momentum Contrast for Unsupervised Visual Representation Learning.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Momentum Contrast for Unsupervised Visual Representation Learning

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.953255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fab2590e-0a6c-491a-b908-30964697592a · outbound

This paper cites an unresolved cited work.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Unresolved cited work

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.907577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1fce885-43d4-4d32-8ece-09dc806a5256 · outbound

This paper cites Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.912816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c54a6954-3e88-4d78-b056-1100279a9902 · outbound

This paper cites An Effective Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers An Effective Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds

Reference 2023

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T23:02:50.119178Z

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 d4264993-daeb-439b-b39b-3b2fe8363c78 · outbound

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

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation

Reference 2025

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T23:02:50.223335Z

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.

Pith citing papers

No inbound Pith citation observations are available.