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Paper Citation Record · LEDGER

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation

As of 9 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.09481.

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pith.paper-citation-record.v1
2607.09481 v1

Coverage vector

measured 42 of 42 reference resolution

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measured 42 of 42 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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42 of 42 outbound references displayed

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Outbound references

Observation bc438ef5-c596-4620-8d0c-f3abc88777b0 · outbound

This paper cites BiomedParse-V: Scaling foundation model for universal text-guided volumetric biomedical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation BiomedParse-V: Scaling foundation model for universal text-guided volumetric biomedical image segmentation,

Reference 1

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Observation b5ffb46a-9610-4aed-b186-d828cb13926c · outbound

This paper cites U-Net: Convolutional net- works for biomedical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation U-Net: Convolutional net- works for biomedical image segmentation,

Reference 2

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Observation 875b6e9e-99b7-49ae-9129-1d5c1e192747 · outbound

This paper cites nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 3

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Observation 4ddfc3be-475c-4e5f-9945-4d60e4a1e830 · outbound

This paper cites UCTransNet: rethinking the skip connections in U-Net from a channel-wise perspective with transformer,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation UCTransNet: rethinking the skip connections in U-Net from a channel-wise perspective with transformer,

Reference 4

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Observation a25034c8-ffff-4922-ae90-0b5aedbd6b05 · outbound

This paper cites LViT: Language meets vision transformer in medical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation LViT: Language meets vision transformer in medical image segmentation,

Reference 5

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Observation 5b287eff-ec43-452f-9aa3-541e3bc1cf85 · outbound

This paper cites Ariadne’s thread: Using text prompts to improve segmentation of infected areas from chest X-ray images,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Ariadne’s thread: Using text prompts to improve segmentation of infected areas from chest X-ray images,

Reference 6

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Observation f0577f7e-39c4-4b88-840d-659bd79eb1a2 · outbound

This paper cites DuSSS: dual semantic similarity-supervised vision-language model for semi-supervised medi- cal image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation DuSSS: dual semantic similarity-supervised vision-language model for semi-supervised medi- cal image segmentation,

Reference 7

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Observation a3be5972-5dab-417a-a079-46aadd2d6c48 · outbound

This paper cites Harnessing text insights with visual alignment for medical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Harnessing text insights with visual alignment for medical image segmentation,

Reference 8

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Observation d4921083-2cfd-46ec-a72d-8bf330b54a84 · outbound

This paper cites TGS-LGP: Text-guided medical image segmentation via local-global perception,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation TGS-LGP: Text-guided medical image segmentation via local-global perception,

Reference 9

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Observation 9e302b4a-2dca-4c78-8e1b-d20b84fee8d8 · outbound

This paper cites Segment anything,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Segment anything,

Reference 10

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Observation 452842f7-a7e0-45ee-904d-5e76c3e22539 · outbound

This paper cites SAM- Adapter: Adapting segment anything in underperformed scenes,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation SAM- Adapter: Adapting segment anything in underperformed scenes,

Reference 11

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Observation 03b7e64d-b888-43d7-ae18-99f2d6ca4307 · outbound

This paper cites Segment anything in medical images,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Segment anything in medical images,

Reference 12

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Observation d59b49a0-040a-4948-b033-ca8ac2db5b3a · outbound

This paper cites SAM 3: Segment anything with concepts,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation SAM 3: Segment anything with concepts,

Reference 13

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Observation b4fb145b-944f-4214-ab7e-4ede346df877 · outbound

This paper cites Gloria: A multimodal global-local representation learning framework for label- efficient medical image recognition,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Gloria: A multimodal global-local representation learning framework for label- efficient medical image recognition,

Reference 14

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Observation aefa5b16-4b8a-49aa-8d93-e3dee10b8730 · outbound

This paper cites TGANet: Text-guided attention for improved polyp segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation TGANet: Text-guided attention for improved polyp segmentation,

Reference 15

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Observation e7fdba59-b59e-470d-b135-f26957fde633 · outbound

This paper cites Text-guided cross-position attention for segmentation: Case of medical image,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Text-guided cross-position attention for segmentation: Case of medical image,

Reference 16

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Observation 2803b427-e6bc-49c4-9ac2-9d95c568b561 · outbound

This paper cites Common vision-language attention for text-guided medical image segmentation of pneumonia,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Common vision-language attention for text-guided medical image segmentation of pneumonia,

Reference 17

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Observation bb31a07f-e572-41a9-8ac4-4384525a5a1a · outbound

This paper cites Frequency- domain multi-modal fusion for language-guided medical image segmen- tation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Frequency- domain multi-modal fusion for language-guided medical image segmen- tation,

Reference 18

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Observation 5fc763b3-4094-4963-b32e-83692abbd300 · outbound

This paper cites Bi-VLGM: Bi-level class-severity- aware vision-language graph matching for text guided medical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Bi-VLGM: Bi-level class-severity- aware vision-language graph matching for text guided medical image segmentation,

Reference 19

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Observation df6530c3-e939-4551-95e2-22673d4b1a1b · outbound

This paper cites LGA: A language guide adapter for advancing the SAM model’s capabilities in medical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation LGA: A language guide adapter for advancing the SAM model’s capabilities in medical image segmentation,

Reference 20

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Observation d1fbfb29-e4ea-49a5-8628-e1bc3f8ec206 · outbound

This paper cites Learning to exploit temporal structure for biomedical vision- language processing,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Learning to exploit temporal structure for biomedical vision- language processing,

Reference 21

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Observation 9890cff9-c5f5-40d4-bb34-621505573d09 · outbound

This paper cites Publicly available clinical BERT embeddings,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Publicly available clinical BERT embeddings,

Reference 22

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Observation c34ec7f9-d705-4ffa-83c9-4796ae7a7556 · outbound

This paper cites A visual–language foundation model for pathology image analysis using medical Twitter,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation A visual–language foundation model for pathology image analysis using medical Twitter,

Reference 23

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Observation 69f5c113-9d4b-4cf0-a6c2-e41c1dbdbb70 · outbound

This paper cites G2D: From global to dense radiography representation learning via vision- language pre-training,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation G2D: From global to dense radiography representation learning via vision- language pre-training,

Reference 24

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Observation d861d9c0-84b0-4bb7-ad0b-40c9cbeaedc9 · outbound

This paper cites EviVLM: When evidential learning meets vision language model for medical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation EviVLM: When evidential learning meets vision language model for medical image segmentation,

Reference 25

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Observation aa1d62a0-49f5-40e0-aec1-08330c55efb9 · outbound

This paper cites MedKLIP: Medical knowledge enhanced language-image pre-training for x-ray diagnosis,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation MedKLIP: Medical knowledge enhanced language-image pre-training for x-ray diagnosis,

Reference 26

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Observation 6ffcd9fc-2b3d-4dff-9abd-3ea5ea598b1a · outbound

This paper cites CXR- CLIP: Toward large scale chest x-ray language-image pre-training,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation CXR- CLIP: Toward large scale chest x-ray language-image pre-training,

Reference 27

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Observation c9d1f0ff-8b2c-48ce-81c8-ec07a02aea1b · outbound

This paper cites A ConvNet for the 2020s,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation A ConvNet for the 2020s,

Reference 28

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Observation 86d9a08e-95ab-42c0-aa58-0d15b2e58849 · outbound

This paper cites Making the most of text semantics to improve biomedical vision–language processing,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Making the most of text semantics to improve biomedical vision–language processing,

Reference 29

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Observation d06b8275-7189-4ce4-82e5-e88a4225377f · outbound

This paper cites UNETR: Transformers for 3d medical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation UNETR: Transformers for 3d medical image segmentation,

Reference 30

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Observation 08efefa5-f31f-42b7-b606-b2efb8f45d2a · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Learning transferable visual models from natural language supervision,

Reference 31

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Observation fbdad86f-435b-4c1d-833f-1483d0390aba · outbound

This paper cites MosMedData: Chest CT Scans With COVID-19 Related Findings Dataset.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation MosMedData: Chest CT Scans With COVID-19 Related Findings Dataset

Reference 32

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Observation 7f75b96a-261c-4f48-ab30-dfcc3e0de57c · outbound

This paper cites OSegNet: Operational segmentation network for COVID-19 detection using chest x-ray images,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation OSegNet: Operational segmentation network for COVID-19 detection using chest x-ray images,

Reference 33

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Observation 640a594c-8061-49fb-a62a-823295e9f5c9 · outbound

This paper cites SIIM-ACR pneumothorax segmentation 2019,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation SIIM-ACR pneumothorax segmentation 2019,

Reference 34

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Observation 20127ba5-9602-4990-98f4-5ecfcc762534 · outbound

This paper cites Kvasir-seg: A segmented polyp dataset,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Kvasir-seg: A segmented polyp dataset,

Reference 35

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Observation cac3f59e-6a67-4092-81c2-cb7294c3a37a · outbound

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

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Swin Transformer: Hierarchical vision transformer using shifted windows,

Reference 36

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Observation 108a60b7-34f5-4bf5-a0b4-20ffbe7cb298 · outbound

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

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Training data-efficient image transformers & distillation through attention,

Reference 37

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Observation 02fe4d5d-5cf0-44d5-87ac-66da6a554d2f · outbound

This paper cites Deep residual learning for image recognition,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Deep residual learning for image recognition,

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Observation 88ef9bf6-9bcf-4654-98a0-5cb207c7d392 · outbound

This paper cites MultiResUNet: Rethinking the U-Net architecture for multimodal biomedical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation MultiResUNet: Rethinking the U-Net architecture for multimodal biomedical image segmentation,

Reference 39

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Observation 1a93ae88-503c-43f6-8db6-e60156a78fb1 · outbound

This paper cites Swin- Unet: Unet-like pure transformer for medical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Swin- Unet: Unet-like pure transformer for medical image segmentation,

Reference 40

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Observation d84bb43b-3b59-4787-a2b3-4dffc416a432 · outbound

This paper cites SAM-Med2D.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation SAM-Med2D

Reference 41

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Observation f7bf46a3-72c1-42ea-a827-df1d6bb0ce4c · outbound

This paper cites Cross- modal conditioned reconstruction for language-guided medical image segmentation,.

Decoupling Language Guidance from Backbones for Text-Guided Medical Segmentation Cross- modal conditioned reconstruction for language-guided medical image segmentation,

Reference 42

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