Paper Citation Record · LEDGER

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography

As of 8 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2607.22740.

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

pith.paper-citation-record.v1
2607.22740 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T09:41:37.066548Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

28 of 28 outbound references displayed

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unresolved28
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External citation measurements

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Outbound references

Observation 286fad6f-61b0-449a-929f-9e3eaaed9d1b · outbound

This paper cites Learning deep features for discriminative localization,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Learning deep features for discriminative localization,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:34.024266Z

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Observation 14b05651-7e07-46db-b899-f87d98586782 · outbound

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

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:34.162007Z

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Observation 27ba1097-a009-4b57-b057-3819406fe99f · outbound

This paper cites Neural discrete representation learning,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Neural discrete representation learning,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:34.308111Z

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Observation 78b0cb98-7675-4343-b1f8-825c13c59626 · outbound

This paper cites Diffusion models for medical image analysis: A comprehensive survey,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Diffusion models for medical image analysis: A comprehensive survey,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:34.443319Z

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Observation 7050e788-ca66-4c99-9734-5f2fd717d9b1 · outbound

This paper cites Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:34.580437Z

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Observation 65c18102-2e87-4e7c-be87-bf991353874e · outbound

This paper cites Breast cancer survival rates.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Breast cancer survival rates

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:34.700960Z

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Observation 75efc89a-6268-4840-af55-3c3e366495ac · outbound

This paper cites Why we still miss breast cancers: Strategies for improving mammography interpretation,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Why we still miss breast cancers: Strategies for improving mammography interpretation,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:34.813838Z

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Observation 8699ce14-2a9d-41a6-9d18-37dc14069fcc · outbound

This paper cites Taming transformers for high- resolution image synthesis,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Taming transformers for high- resolution image synthesis,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:34.922064Z

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Observation 3ebb1b60-acff-4f88-b282-e54157e386d0 · outbound

This paper cites Autoencoding beyond pixels using a learned similarity metric,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Autoencoding beyond pixels using a learned similarity metric,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.042214Z

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Observation 36481c2e-5697-4db7-a08f-6d7eafc40c2a · outbound

This paper cites SDEdit: Guided image synthesis and editing with stochastic differential equations,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography SDEdit: Guided image synthesis and editing with stochastic differential equations,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.165959Z

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Observation 6fa8a171-347a-4680-bbfd-bf6ac16e30c4 · outbound

This paper cites Deep learning to improve breast cancer detection on screening mammography,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Deep learning to improve breast cancer detection on screening mammography,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.322470Z

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Observation 31666368-00b3-4ca6-a3c1-c917a5b00177 · outbound

This paper cites Breast cancer detection in mammography using a convolu- tional neural network,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Breast cancer detection in mammography using a convolu- tional neural network,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.460094Z

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Observation 92318b87-3b15-4d02-95a7-bebec7a4b432 · outbound

This paper cites Patient-specific mri super-resolution via implicit neural representations,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Patient-specific mri super-resolution via implicit neural representations,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.637731Z

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Observation 3899d830-df63-4138-ab93-3d99345f626d · outbound

This paper cites Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.719607Z

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Observation 30782ad8-3218-45f7-94fe-0691216f99db · outbound

This paper cites Grad-CAM++: Generalized gradient-based visual explanations for deep convolutional networks,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Grad-CAM++: Generalized gradient-based visual explanations for deep convolutional networks,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.788809Z

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Observation e5062ef2-d20c-402b-8ac6-25c71572a5dc · outbound

This paper cites On calibration of modern neural networks,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography On calibration of modern neural networks,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.874762Z

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Observation f210d509-a5d1-4bc0-90a1-af62c4ed5bdd · outbound

This paper cites Beyond temperature scaling: Ob- taining well-calibrated multiclass probabilities with dirichlet calibration,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Beyond temperature scaling: Ob- taining well-calibrated multiclass probabilities with dirichlet calibration,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:35.956720Z

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Observation ae3467f3-2a54-4df2-b726-01b354a7b1b5 · outbound

This paper cites A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.066293Z

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Observation 9f005bd7-e990-443f-9718-a566564f393c · outbound

This paper cites Cmt-unet: Leveraging stage-wise hybrid framework for enhanced accuracy and efficiency in medical image segmentation,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Cmt-unet: Leveraging stage-wise hybrid framework for enhanced accuracy and efficiency in medical image segmentation,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.146326Z

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Observation c945483e-2a31-4db4-b1a1-aa32a139b63d · outbound

This paper cites Sanity checks for saliency maps,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Sanity checks for saliency maps,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.230187Z

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Observation 01c0df76-e076-402f-ba33-e4856e1d391c · outbound

This paper cites Deep residual learning for image recognition,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Deep residual learning for image recognition,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.291425Z

Source-reported events for the cited work

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Observation 447abbc4-b896-4ac7-b50f-2855ac287dfb · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography The unreasonable effectiveness of deep features as a perceptual metric,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.379248Z

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Observation 683feb26-942a-49bd-a31b-9b27f2978153 · outbound

This paper cites A curated mammography data set for use in computer-aided detection and diagnosis research,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography A curated mammography data set for use in computer-aided detection and diagnosis research,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.458137Z

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Observation e3809ba7-8c84-4b54-8916-aa7825023405 · outbound

This paper cites Inbreast: Toward a full-field digital mammographic database,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Inbreast: Toward a full-field digital mammographic database,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.519074Z

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Observation 8bdcfec3-3687-4aeb-895a-045076c5bbc7 · outbound

This paper cites Vindr-mammo: A large-scale benchmark dataset for computer- aided diagnosis in full-field digital mammography,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Vindr-mammo: A large-scale benchmark dataset for computer- aided diagnosis in full-field digital mammography,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.628177Z

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Observation 1e373445-9157-49c0-afd0-8443a90a5435 · outbound

This paper cites RISE: Randomized input sampling for explanation of black-box models,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography RISE: Randomized input sampling for explanation of black-box models,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.763224Z

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Observation b688934a-8454-4d55-a604-511e319e632e · outbound

This paper cites Visualizing and understanding convolutional networks,.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Visualizing and understanding convolutional networks,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:36.925247Z

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Observation b424efad-4f1b-48ca-9339-b4f94e4996c7 · outbound

This paper cites Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (TCA V),.

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (TCA V),

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T09:41:37.066548Z

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Pith citing papers

No inbound Pith citation observations are available.