ACE: Anatomically Consistent Embeddings in Composition and Decomposition | Paper Citation Record

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This paper cites RSNA pneumonia detection ACE Nodule POPAR Effusion Mass Atelectasis DINO BYOL Cardiomegaly Infiltration Pneumonia Pneumothorax Adam Figure 13.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition RSNA pneumonia detection ACE Nodule POPAR Effusion Mass Atelectasis DINO BYOL Cardiomegaly Infiltration Pneumonia Pneumothorax Adam Figure 13

Reference 1

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ACE: Anatomically Consistent Embeddings in Composition and Decomposition Unresolved cited work

Reference 2

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Observation a626ad8e-12a1-420c-acbb-8ff0ac27f0bc · outbound

This paper cites Variance- invariance-covariance regularization for self-supervised learning.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Variance- invariance-covariance regularization for self-supervised learning

Reference 3

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Observation 645ece08-56f8-45b2-a7fb-2e47a1f85873 · outbound

This paper cites Vicregl: Self- supervised learning of local visual features.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Vicregl: Self- supervised learning of local visual features

Reference 4

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Observation ef485a2b-4e2a-4b48-951d-1c4a42c62880 · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Unsupervised learning of visual features by contrasting cluster assignments

Reference 5

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This paper cites Emerg- ing properties in self-supervised vision transformers.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Emerg- ing properties in self-supervised vision transformers

Reference 6

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Observation 3d32e8a0-12b9-4095-a242-4c58e0805304 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition A simple framework for contrastive learning of visual representations

Reference 7

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Observation e222932a-8e72-4b5c-9f35-832fcda75727 · outbound

This paper cites Exploring simple siamese rep- resentation learning.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Exploring simple siamese rep- resentation learning

Reference 8

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Observation 7cb62eaf-b8e7-40eb-b23e-d0e8ceabff93 · outbound

This paper cites Eyepacs: an adapt- able telemedicine system for diabetic retinopathy screening.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Eyepacs: an adapt- able telemedicine system for diabetic retinopathy screening

Reference 9

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Observation 3273463f-bc18-48f5-9b85-419bbb0af697 · outbound

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

ACE: Anatomically Consistent Embeddings in Composition and Decomposition An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

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Observation 833c6477-2908-4947-98f5-b3dfd40001f0 · outbound

This paper cites Anatomy-aware con- trastive representation learning for fetal ultrasound.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Anatomy-aware con- trastive representation learning for fetal ultrasound

Reference 11

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Observation 9cbcfb5d-1dfe-4c27-b14f-50bc49a63490 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Bootstrap your own latent-a new approach to self-supervised learning

Reference 12

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Observation 40cb591f-08ad-4946-bb51-5371148d0cb5 · outbound

This paper cites Discriminative, restorative, and adversarial learning: Stepwise incremental pretraining.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Discriminative, restorative, and adversarial learning: Stepwise incremental pretraining

Reference 13

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This paper cites Stepwise incremental pretraining for integrating discriminative, restorative, and adversarial learning.Medical Image Analysis, 95:103159, 2024.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Stepwise incremental pretraining for integrating discriminative, restorative, and adversarial learning.Medical Image Analysis, 95:103159, 2024

Reference 14

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Observation 384379b3-3f4d-40b0-a6dc-79de508c6563 · outbound

This paper cites Learning semantics-enriched representation via self- discovery, self-classification, and self-restoration.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Learning semantics-enriched representation via self- discovery, self-classification, and self-restoration

Reference 15

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Observation 761bb732-3b28-4f5e-b833-9b2ec71f345c · outbound

This paper cites Dira: Discrimina- tive, restorative, and adversarial learning for self-supervised medical image analysis.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Dira: Discrimina- tive, restorative, and adversarial learning for self-supervised medical image analysis

Reference 16

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Observation fdce9dcd-fca6-42f4-b757-186f67f8d9e8 · outbound

This paper cites Self-supervised learning for medical image analysis: Discriminative, restora- tive, or adversarial? Medical Image Analysis , 94:103086,.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Self-supervised learning for medical image analysis: Discriminative, restora- tive, or adversarial? Medical Image Analysis , 94:103086,

Reference 17

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Observation 3f6db956-f724-49eb-8e88-68a7eeb0623c · outbound

This paper cites Transferable visual words: Exploiting the semantics of anatomical patterns for self-supervised learning.IEEE trans- actions on medical imaging, 40(10):2857–2868, 2021.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Transferable visual words: Exploiting the semantics of anatomical patterns for self-supervised learning.IEEE trans- actions on medical imaging, 40(10):2857–2868, 2021

Reference 18

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Observation a1d93458-36e0-4bd7-b995-c9e273e64e08 · outbound

This paper cites Momentum contrast for unsupervised visual rep- resentation learning.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Momentum contrast for unsupervised visual rep- resentation learning

Reference 19

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Observation fd3cec14-689c-4669-96af-09b1b29cf7ec · outbound

This paper cites Deep residual learning for image recognition.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Deep residual learning for image recognition

Reference 20

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Observation 41ddb59c-3878-481b-b8cc-a58e2727fb08 · outbound

This paper cites Fire: fundus image registration dataset.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Fire: fundus image registration dataset

Reference 21

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Observation 5b501451-7f1a-4523-a6cd-c153a13911cd · outbound

This paper cites How to represent part-whole hierarchies in a neural network.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition How to represent part-whole hierarchies in a neural network

Reference 22

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Observation 88017e19-9675-48da-ac4c-3783f6d839b5 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Distilling the Knowledge in a Neural Network

Reference 23

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Observation cdb4b242-7d0c-4b8f-bc79-391a63b2d56d · outbound

This paper cites Towards foundation models learned from anatomy in medical imaging via self-supervision.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Towards foundation models learned from anatomy in medical imaging via self-supervision

Reference 24

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Observation db97b1ae-b4c4-4e3a-bb25-0a00bb00b5eb · outbound

This paper cites Anatomy-aware self-supervised learn- ing for aligned multi-modal medical data.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Anatomy-aware self-supervised learn- ing for aligned multi-modal medical data

Reference 25

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Observation d0727c4e-648a-436e-ae61-eef30e67e1c3 · outbound

This paper cites Self- supervised learning with local contrastive loss for detec- tion and semantic segmentation.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Self- supervised learning with local contrastive loss for detec- tion and semantic segmentation

Reference 26

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Observation ca42a039-f2de-4a30-898e-9ee911388406 · outbound

This paper cites Two public chest x-ray datasets for computer-aided screening of pulmonary diseases.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Two public chest x-ray datasets for computer-aided screening of pulmonary diseases

Reference 27

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Observation a267dfef-0a97-4cfd-8e7e-7973a947ee0a · outbound

This paper cites Anatomical invariance modeling and semantic alignment for self-supervised learning in 3d medical image analysis.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Anatomical invariance modeling and semantic alignment for self-supervised learning in 3d medical image analysis

Reference 28

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Observation fe57e37a-e184-46ac-9f72-dacf741f2679 · outbound

This paper cites Self-supervised visual fea- ture learning with deep neural networks: A survey.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Self-supervised visual fea- ture learning with deep neural networks: A survey

Reference 29

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Observation 649b7a45-6a0f-48e3-aba9-e8b025a04150 · outbound

This paper cites Mimic-cxr, a de- identified publicly available database of chest radiographs with free-text reports.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Mimic-cxr, a de- identified publicly available database of chest radiographs with free-text reports

Reference 30

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Observation 38a77c21-610a-424e-8bd5-c97a7e18c008 · outbound

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

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Contrastive learning of global and local features for medical image segmentation with limited annotations

Reference 31

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Observation 66b9d5e4-e728-4d0f-b549-1dd6177cd552 · outbound

This paper cites Compressive visual representa- tions.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Compressive visual representa- tions

Reference 32

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This paper cites A structure-aware relation network for thoracic diseases detection and segmentation.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition A structure-aware relation network for thoracic diseases detection and segmentation

Reference 33

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This paper cites ChestX-Det10: Chest X-ray Dataset on Detection of Thoracic Abnormalities.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition ChestX-Det10: Chest X-ray Dataset on Detection of Thoracic Abnormalities

Reference 34

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

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Swin transformer: Hierarchical vision transformer using shifted windows

Reference 35

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Observation e075253d-f239-45e0-bee1-e9d81b0b71d9 · outbound

This paper cites DeViDe: Faceted medical knowledge for improved medical vision-language pre-training.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition DeViDe: Faceted medical knowledge for improved medical vision-language pre-training

Reference 36

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Observation d99a2ca4-cbe8-4609-a969-946c7e0787f6 · outbound

This paper cites Benchmarking and boosting transformers for medical image classification.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Benchmarking and boosting transformers for medical image classification

Reference 37

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Observation 440f817b-c6ba-4aa1-b619-d3a33a1cf955 · outbound

This paper cites Foundation ark: Accruing and reusing knowl- edge for superior and robust performance.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Foundation ark: Accruing and reusing knowl- edge for superior and robust performance

Reference 38

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Observation f6ef736b-af6b-4627-9a98-3a4b65b43da7 · outbound

This paper cites Lvm-med: Learning large- scale self-supervised vision models for medical imaging via second-order graph matching.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Lvm-med: Learning large- scale self-supervised vision models for medical imaging via second-order graph matching

Reference 39

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This paper cites Popar: Patch order prediction and appearance recovery for self-supervised medical image anal- ysis.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Popar: Patch order prediction and appearance recovery for self-supervised medical image anal- ysis

Reference 40

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This paper cites Asa: Learning anatomical con- sistency, sub-volume spatial relationships and fine-grained appearance for ct images.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Asa: Learning anatomical con- sistency, sub-volume spatial relationships and fine-grained appearance for ct images

Reference 41

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Observation e242cc79-f5f4-4fad-bef7-3cd7aac5ed2d · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Learning transferable visual models from natural language supervi- sion

Reference 42

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This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 43

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ACE: Anatomically Consistent Embeddings in Composition and Decomposition Unresolved cited work

Reference 44

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This paper cites Deep high-resolution representation learning for human pose es- timation.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Deep high-resolution representation learning for human pose es- timation

Reference 45

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This paper cites Representing part-whole hierarchies in foundation models by learning localizability composability and decomposability from anatomy via self supervision.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Representing part-whole hierarchies in foundation models by learning localizability composability and decomposability from anatomy via self supervision

Reference 46

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This paper cites Guest editorial annotation-efficient deep learning: the holy grail of medical imaging.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Guest editorial annotation-efficient deep learning: the holy grail of medical imaging

Reference 47

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Observation 1c252641-22f3-4ea3-b865-7f1d58768f28 · outbound

This paper cites Multimodal self-supervised learning for medical im- age analysis.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Multimodal self-supervised learning for medical im- age analysis

Reference 48

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Observation 33cf73eb-2dd8-46f4-8ab2-81a01b7d9685 · outbound

This paper cites Con- trastive multiview coding.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Con- trastive multiview coding

Reference 49

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This paper cites Expert-level detec- tion of pathologies from unannotated chest x-ray images via self-supervised learning.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Expert-level detec- tion of pathologies from unannotated chest x-ray images via self-supervised learning

Reference 50

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This paper cites Visualiz- ing data using t-sne.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Visualiz- ing data using t-sne

Reference 51

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Observation 35e9d777-ddaa-48fc-b28c-e658a956a1c6 · outbound

This paper cites DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions

Reference 52

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Observation 9c17d250-5962-4277-bf51-3bd1ef47fd74 · outbound

This paper cites Chestx- ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Chestx- ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases

Reference 53

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Observation 8ee5a51e-63ca-49fb-9d88-033c90e6dfd9 · outbound

This paper cites Dense contrastive learning for self-supervised visual pre-training.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Dense contrastive learning for self-supervised visual pre-training

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:27.232395Z

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Observation 5927b741-fd9a-43af-9dfb-ed90bcefe503 · outbound

This paper cites Unified perceptual parsing for scene understand- ing.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Unified perceptual parsing for scene understand- ing

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:27.210156Z

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Observation 9236828d-ef4b-4572-bf20-4990e9549bb5 · outbound

This paper cites Region similarity representation learn- ing.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Region similarity representation learn- ing

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:27.080423Z

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Observation 0f3a68de-fe6d-4bdb-bdbe-72af0598958e · outbound

This paper cites Propagate yourself: Exploring pixel-level consistency for unsupervised visual representation learning.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Propagate yourself: Exploring pixel-level consistency for unsupervised visual representation learning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.981745Z

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Observation be6de149-7877-4d7f-8c17-aac5ddb6e121 · outbound

This paper cites Sam: Self-supervised learning of pixel-wise anatom- ical embeddings in radiological images.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Sam: Self-supervised learning of pixel-wise anatom- ical embeddings in radiological images

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.963512Z

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Observation 8206eda5-048b-4332-902e-8aec448c7a4b · outbound

This paper cites DenseDINO: Boosting Dense Self-Supervised Learning with Token-Based Point-Level Consistency.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition DenseDINO: Boosting Dense Self-Supervised Learning with Token-Based Point-Level Consistency

Reference 59

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Observation 130e4c7a-79f1-4f15-9dc3-2259b3abab45 · outbound

This paper cites Patch-level representation learning for self-supervised vision transformers.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Patch-level representation learning for self-supervised vision transformers

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.930306Z

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Observation 638a25c7-e920-4caa-bbd1-cb0d7c3234b3 · outbound

This paper cites Barlow twins: Self-supervised learning via redundancy reduction.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Barlow twins: Self-supervised learning via redundancy reduction

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T19:28:25.686211Z

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This paper cites How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T19:28:25.704968Z

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Observation 5d60793f-4ad4-478d-be22-31cef3ce6985 · outbound

This paper cites Pre- cise location matching improves dense contrastive learning in digital pathology.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Pre- cise location matching improves dense contrastive learning in digital pathology

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.735304Z

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Observation ccc41a7f-f6be-47bc-bb79-edf460b13307 · outbound

This paper cites Leverage your local and global repre- sentations: A new self-supervised learning strategy.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Leverage your local and global repre- sentations: A new self-supervised learning strategy

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.683297Z

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Observation b4487b66-2fc1-4344-ba28-0faf6faf9b0b · outbound

This paper cites Knowledge-enhanced visual-language pre- training on chest radiology images.Nature Communications, 14(1):4542, 2023.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Knowledge-enhanced visual-language pre- training on chest radiology images.Nature Communications, 14(1):4542, 2023

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.638438Z

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Observation 38270dde-b50b-4aa1-805a-2fcccfb2113c · outbound

This paper cites Learning anatom- ically consistent embedding for chest radiography.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Learning anatom- ically consistent embedding for chest radiography

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.446721Z

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Observation fe615d1f-3c65-488f-899d-4957386f10e2 · outbound

This paper cites Fine-tuning convo- lutional neural networks for biomedical image analysis: ac- tively and incrementally.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Fine-tuning convo- lutional neural networks for biomedical image analysis: ac- tively and incrementally

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.424990Z

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Observation 8680df0a-7497-47c2-bcb0-ac28906e7a22 · outbound

This paper cites Models genesis: Generic autodidactic models for 3d medical image analysis.

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Models genesis: Generic autodidactic models for 3d medical image analysis

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:28:26.347993Z

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