Paper Citation Record · LEDGER

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer

As of 14 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.12982.

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

pith.paper-citation-record.v1
2506.12982 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:03.479929Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

34 of 34 outbound references displayed

verified exact1
verified fuzzy25
unresolved8
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 121603b3-c3c8-4fa1-91cb-0d361e9a426d · outbound

This paper cites Computing receptive fields of convolutional neural networks.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Computing receptive fields of convolutional neural networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.536866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d9c37fc8-f615-41b0-b61b-32b42d6841be · outbound

This paper cites Advances in medical image analysis with vision transformers: a comprehensive review.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Advances in medical image analysis with vision transformers: a comprehensive review

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.530417Z

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Observation 298bc71d-fd4c-457e-bb0e-de4202cf6ffd · outbound

This paper cites Med-former: A transformer based architecture for medical image classification.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Med-former: A transformer based architecture for medical image classification

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.523287Z

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Observation e314b164-6d93-4c17-bac4-6063c24cea80 · outbound

This paper cites Coatnet: Marrying convolution and attention for all data sizes.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Coatnet: Marrying convolution and attention for all data sizes

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.516390Z

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Observation 50520a72-5c57-44a4-8a2c-aed2f291d68b · outbound

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

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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Observation b3af8723-7c72-4972-8629-18843815f874 · outbound

This paper cites Convit: Improving vision transformers with soft convolutional inductive biases.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Convit: Improving vision transformers with soft convolutional inductive biases

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.509453Z

Source-reported events for the cited work

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Observation d4639b79-7dd1-4def-b9ba-5baafb7d5221 · outbound

This paper cites Rmt: Retentive networks meet vision transformers.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Rmt: Retentive networks meet vision transformers

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.502640Z

Source-reported events for the cited work

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Observation 1f0487c9-c931-4c7b-b903-10e3e60a3165 · outbound

This paper cites Cmt: Convolutional neural networks meet vision transformers.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Cmt: Convolutional neural networks meet vision transformers

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.496119Z

Source-reported events for the cited work

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Observation d4222645-5575-48b0-9e1a-89fe1025b94e · outbound

This paper cites Higt: Hierarchical interaction graph-transformer for whole slide image analysis.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Higt: Hierarchical interaction graph-transformer for whole slide image analysis

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.489171Z

Source-reported events for the cited work

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Observation 5f5091d8-991a-4355-94ed-01c3315b7ef6 · outbound

This paper cites Deep residual learning for image recognition.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Deep residual learning for image recognition

Reference 10

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Source-reported events for the cited work

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Observation def84805-d051-4d8a-bd84-ccae8d84e67e · outbound

This paper cites Conv2former: A simple transformer-style convnet for visual recognition.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Conv2former: A simple transformer-style convnet for visual recognition

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.478390Z

Source-reported events for the cited work

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Observation 92195be2-b7e0-409c-8cb0-cc7e922c4c70 · outbound

This paper cites Benchmarking self-supervised learning on diverse pathology datasets.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Benchmarking self-supervised learning on diverse pathology datasets

Reference 12

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Source-reported events for the cited work

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Observation 9b464d33-8b4f-4436-ac47-0df59a554708 · outbound

This paper cites Vision Transformer for Small-Size Datasets.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Vision Transformer for Small-Size Datasets

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.774613Z

Source-reported events for the cited work

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Observation 3053d9d7-c1e7-44c5-a0a8-de337fa5567b · outbound

This paper cites Mvitv2: Improved multiscale vision transformers for classification and detection.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Mvitv2: Improved multiscale vision transformers for classification and detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.468463Z

Source-reported events for the cited work

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Observation 52397976-09f5-4ae8-9038-7b709136d20c · outbound

This paper cites LocalViT: Analyzing Locality in Vision Transformers.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer LocalViT: Analyzing Locality in Vision Transformers

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.924074Z

Source-reported events for the cited work

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Observation 5f28b332-df95-4833-b04a-638ef511a154 · outbound

This paper cites Scale-aware modulation meet transformer.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Scale-aware modulation meet transformer

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.461660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cdd0b2fb-d693-44db-8011-068cc29c180d · outbound

This paper cites Exploiting geometric features via hierarchical graph pyramid transformer for cancer diagnosis using histopathological images.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Exploiting geometric features via hierarchical graph pyramid transformer for cancer diagnosis using histopathological images

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.455126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5e1bf034-b649-4439-931d-92c2e631d6c2 · outbound

This paper cites Efficient training of visual transformers with small datasets.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Efficient training of visual transformers with small datasets

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.448424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3f4df035-9a75-439e-a79c-e617f38d61ce · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Swin transformer: Hierarchical vision transformer using shifted windows

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.441813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eeb6cd80-34e1-48e8-8777-2d5faebc73f0 · outbound

This paper cites Hybrid ladder transformers with efficient parallel-cross attention for medical image segmentation.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Hybrid ladder transformers with efficient parallel-cross attention for medical image segmentation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.434969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 65557212-abf7-4534-b817-70631fa746e1 · outbound

This paper cites Medvit: a robust vision transformer for generalized medical image classification.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Medvit: a robust vision transformer for generalized medical image classification

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.428180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 18ce1c21-9bc2-4adc-b51f-0a62698bd0cb · outbound

This paper cites Cell-detr: Efficient cell detection and classification in wsis with transformers.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Cell-detr: Efficient cell detection and classification in wsis with transformers

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.421183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 00624969-f0c4-4b55-8cff-7f266306305d · outbound

This paper cites Do vision transformers see like convolutional neural networks? Advances in neural information processing systems, 34: 0 12116--12128, 2021.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Do vision transformers see like convolutional neural networks? Advances in neural information processing systems, 34: 0 12116--12128, 2021

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.305020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 78f39b2a-4334-4bc3-8079-eb6aa7f762a9 · outbound

This paper cites Transformers in medical imaging: A survey.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Transformers in medical imaging: A survey

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:05.209668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7469ffd3-ae0c-49b7-9e3e-835abbd6deea · outbound

This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Transmil: Transformer based correlated multiple instance learning for whole slide image classification

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:04.989612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 92a00660-ca49-474d-9aae-997f94d1973c · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Training data-efficient image transformers & distillation through attention

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:04.786575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0c0b9d61-4cf6-4e23-a466-f9b00e5cca5a · outbound

This paper cites Uctransnet: rethinking the skip connections in u-net from a channel-wise perspective with transformer.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Uctransnet: rethinking the skip connections in u-net from a channel-wise perspective with transformer

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:04.591573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 121df421-3e5a-4ac0-afa0-34baf9cc7704 · outbound

This paper cites The cancer genome atlas pan-cancer analysis project.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer The cancer genome atlas pan-cancer analysis project

Reference 28

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Source-reported events for the cited work

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Observation 2ea0001f-c4b9-4962-9c5b-63b9e7cdde7c · outbound

This paper cites Cvt: Introducing convolutions to vision transformers.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Cvt: Introducing convolutions to vision transformers

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:04.415585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5b54213b-59f5-44c4-a77a-9f180444fed0 · outbound

This paper cites Co-scale conv-attentional image transformers.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Co-scale conv-attentional image transformers

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:04.170358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 22ee1fca-c355-4cad-817c-890a6cf07767 · outbound

This paper cites Incorporating convolution designs into visual transformers.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Incorporating convolution designs into visual transformers

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:03.960318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7267ffd3-39ec-4805-a027-f49bd04c39d4 · outbound

This paper cites CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:42:03.788724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 002b6ea9-b74b-47ae-ab6c-537edb0442c0 · outbound

This paper cites Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:03.322168Z

Source-reported events for the cited work

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Observation edb0aeb1-3b24-468a-9ba1-c8724a95bdc9 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:03.479929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.