AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization | Paper Citation Record

Observation 8a34dff8-cd4b-45e4-ad39-07fd2fb7221a · outbound

This paper cites Reducing the dimensionality of data with neural networks,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Reducing the dimensionality of data with neural networks,

Reference 1

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Observation 10daabd1-1d3c-4e50-a8a1-54cc21ed98e9 · outbound

This paper cites Reconstruction by inpainting for visual anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Reconstruction by inpainting for visual anomaly detection,

Reference 2

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Observation 5d785d57-d137-4af1-b4fa-114debc618b6 · outbound

This paper cites Multi-category decom- position editing network for the accurate visual inspection of texture defects,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Multi-category decom- position editing network for the accurate visual inspection of texture defects,

Reference 3

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Observation a2ee13b7-817b-4c7e-9059-779eff317a6b · outbound

This paper cites Defect classification and detection using a multitask deep one-class cnn,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Defect classification and detection using a multitask deep one-class cnn,

Reference 4

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Observation de0421e9-0bd6-4770-a08b-d0c8efb8c9c4 · outbound

This paper cites Visual anomaly detection via partition memory bank module and error estimation,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Visual anomaly detection via partition memory bank module and error estimation,

Reference 5

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Observation 9cddb9d0-f2dc-4849-8c57-db6374bb11eb · outbound

This paper cites Pga-net: Pyramid feature fusion and global context attention network for automated surface defect detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Pga-net: Pyramid feature fusion and global context attention network for automated surface defect detection,

Reference 6

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Observation 75289bb6-0645-4417-9a9b-7a0747bb9a3b · outbound

This paper cites A-net: An a-shape lightweight neural network for real-time surface defect segmentation,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization A-net: An a-shape lightweight neural network for real-time surface defect segmentation,

Reference 7

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Observation eb26e5d4-2e80-4d91-975c-34fc3d7a5134 · outbound

This paper cites Normal reference attention and defective feature perception network for surface defect detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Normal reference attention and defective feature perception network for surface defect detection,

Reference 8

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Observation cbae7bf4-9385-434d-be48-1edfbc52d075 · outbound

This paper cites A feature memory rearrangement network for visual inspection of textured surface defects toward edge intelligent manufacturing,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization A feature memory rearrangement network for visual inspection of textured surface defects toward edge intelligent manufacturing,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.889557Z

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Observation f08a793a-0ffa-4a3a-8cb2-8808c942e088 · outbound

This paper cites Unsupervised defect segmentation via forgetting-inputting-based feature fusion and multiple hierarchical feature difference,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Unsupervised defect segmentation via forgetting-inputting-based feature fusion and multiple hierarchical feature difference,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.879742Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 083b2990-8e58-4b92-b8a1-6b2f307c040f · outbound

This paper cites Self-supervised masking for unsupervised anomaly detection and localization,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Self-supervised masking for unsupervised anomaly detection and localization,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.823492Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 57f290a5-a2ce-4af3-8b73-1af527be9010 · outbound

This paper cites Masked swin transformer unet for industrial anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Masked swin transformer unet for industrial anomaly detection,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.614786Z

Source-reported events for the cited work

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Observation 0dd3be5a-ce1c-435a-a8d4-b5deac6e5c6e · outbound

This paper cites Mvtec ad — a comprehensive real-world dataset for unsupervised anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Mvtec ad — a comprehensive real-world dataset for unsupervised anomaly detection,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.541317Z

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Observation b382f9bf-4c94-467d-a81c-e3ac2deb0a48 · outbound

This paper cites Vt- adl: A vision transformer network for image anomaly detection and localization,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Vt- adl: A vision transformer network for image anomaly detection and localization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.531765Z

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Observation 306b62ab-6b94-4ca1-8552-7cc553232e40 · outbound

This paper cites Memorizing normality to detect anomaly: Memory- augmented deep autoencoder for unsupervised anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Memorizing normality to detect anomaly: Memory- augmented deep autoencoder for unsupervised anomaly detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.522110Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dafdf1e4-bd39-4f89-a7e3-6eb19e1133ce · outbound

This paper cites Trustmae: A noise-resilient defect classification framework using memory-augmented auto-encoders with trust regions,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Trustmae: A noise-resilient defect classification framework using memory-augmented auto-encoders with trust regions,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.511519Z

Source-reported events for the cited work

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Observation 90b0337c-5c5f-412b-82c6-c5f5990bfccb · outbound

This paper cites Divide- and-assemble: Learning block-wise memory for unsupervised anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Divide- and-assemble: Learning block-wise memory for unsupervised anomaly detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.502654Z

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Observation 7b853fa3-c98a-4772-b856-e5c22972bb83 · outbound

This paper cites An unsupervised-learning-based approach for automated defect inspection on textured surfaces,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization An unsupervised-learning-based approach for automated defect inspection on textured surfaces,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.493401Z

Source-reported events for the cited work

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Observation 11b3ed27-2fa1-46ff-8631-8037514bdb7b · outbound

This paper cites Multiscale feature-clustering- based fully convolutional autoencoder for fast accurate visual inspection of texture surface defects,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Multiscale feature-clustering- based fully convolutional autoencoder for fast accurate visual inspection of texture surface defects,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.483755Z

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Observation 2ac39f30-54c4-491f-9af8-13377ba81616 · outbound

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

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization The unreasonable effectiveness of deep features as a perceptual metric,

Reference 20

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Observation 8d94a81d-8cc3-43cc-a9a2-575599dafb9a · outbound

This paper cites Cutpaste: Self-supervised learning for anomaly detection and localization,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Cutpaste: Self-supervised learning for anomaly detection and localization,

Reference 21

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Observation 70623d01-4dc7-488b-a77b-74fd2792b55d · outbound

This paper cites An anomaly feature-editing- based adversarial network for texture defect visual inspection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization An anomaly feature-editing- based adversarial network for texture defect visual inspection,

Reference 22

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Observation b2455d60-b456-40bf-8463-a24ee808c1e3 · outbound

This paper cites Draem-a discriminatively trained reconstruction embedding for surface anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Draem-a discriminatively trained reconstruction embedding for surface anomaly detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.402748Z

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Observation 139e4303-8836-4f6d-8d78-ce956e377872 · outbound

This paper cites Mldfr: A multilevel features restoration method based on damaged images for anomaly detection and localization,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Mldfr: A multilevel features restoration method based on damaged images for anomaly detection and localization,

Reference 24

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Observation 825581ac-495b-432d-a9e1-706a95b7240e · outbound

This paper cites Siamese Transition Masked Autoencoders as Uniform Unsupervised Visual Anomaly Detector.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Siamese Transition Masked Autoencoders as Uniform Unsupervised Visual Anomaly Detector

Reference 25

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Observation 9b756dd3-15ea-482b-836c-3d741aa5496f · outbound

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

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.124719Z

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Observation 81f9e6b0-af6a-43ad-ae4f-58719123133b · outbound

This paper cites Inpainting transformer for anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Inpainting transformer for anomaly detection,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.086267Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bcef2b94-2d00-4e95-be4c-bc1f32595643 · outbound

This paper cites Deep one-class classification,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Deep one-class classification,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.076347Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 810f66fd-22b6-4d9b-aa34-f573374a2319 · outbound

This paper cites Patch svdd: Patch-level svdd for anomaly detection and segmentation,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Patch svdd: Patch-level svdd for anomaly detection and segmentation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.066875Z

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This paper cites Panda: Adapting pretrained features for anomaly detection and segmentation,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Panda: Adapting pretrained features for anomaly detection and segmentation,

Reference 30

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 123c0dda-41dc-4e02-b345-fc7b17ec1e18 · outbound

This paper cites Towards total recall in industrial anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Towards total recall in industrial anomaly detection,

Reference 31

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Observation 857ba1c1-c55f-42bd-9274-95d705040ddf · outbound

This paper cites Industrial image anomaly localization based on gaussian clustering of pre-trained feature,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Industrial image anomaly localization based on gaussian clustering of pre-trained feature,

Reference 32

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Observation d89b48e2-40bf-49a0-8cfb-7af4f5477fc4 · outbound

This paper cites Anomaly detection via reverse distillation from one-class embedding,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Anomaly detection via reverse distillation from one-class embedding,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.027045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e21d54d1-d03e-44ff-9a25-376062f3ae5c · outbound

This paper cites Unsupervised image anomaly detection and segmentation based on pre-trained feature mapping,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Unsupervised image anomaly detection and segmentation based on pre-trained feature mapping,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.016684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cb016e9d-69d2-46a4-b8bb-5caea9481868 · outbound

This paper cites Multiresolution knowledge distillation for anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Multiresolution knowledge distillation for anomaly detection,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:40.005902Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3f87492b-bdbd-4e98-b7ca-b8f48391160d · outbound

This paper cites Wide Residual Networks.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Wide Residual Networks

Reference 36

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This paper cites Imagenet large scale visual recognition challenge,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Imagenet large scale visual recognition challenge,

Reference 37

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Observation b82a20fe-6d48-4d83-86fc-fb7d9a34a606 · outbound

This paper cites Masked au- toencoders are scalable vision learners,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Masked au- toencoders are scalable vision learners,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.733592Z

Source-reported events for the cited work

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Observation a4210bcc-dbf1-422f-8047-a8d8c68b72d5 · outbound

This paper cites Anomaly composition and decompo- sition network for accurate visual inspection of texture defects,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Anomaly composition and decompo- sition network for accurate visual inspection of texture defects,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.680848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d6bdc7eb-cc31-4974-b913-e9de75ecf17b · outbound

This paper cites A unified model for multi-class anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization A unified model for multi-class anomaly detection,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.671566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 18faa730-ce6d-416c-92d3-0d00afe3d228 · outbound

This paper cites Pyramidflow: High-resolution defect contrastive localization using pyramid normalizing flow,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Pyramidflow: High-resolution defect contrastive localization using pyramid normalizing flow,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.660375Z

Source-reported events for the cited work

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Observation 9329d6d5-4a22-48ec-b00f-b20b2bda326a · outbound

This paper cites Revisiting reverse distillation for anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Revisiting reverse distillation for anomaly detection,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.650601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 38eea1c4-743f-4bf4-bc69-2fd7f1dcadab · outbound

This paper cites Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders

Reference 43

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Source-reported events for the cited work

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Observation 2b7753c0-a89a-4783-bfd7-d1d89f04a7ba · outbound

This paper cites Unsupervised anomaly segmentation via deep feature reconstruction,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Unsupervised anomaly segmentation via deep feature reconstruction,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.639784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 05af550d-7fd6-4a7d-9a47-c2603bc5c8a4 · outbound

This paper cites FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows

Reference 45

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Observation b3c4893f-c8b6-4768-b7a7-b04996efdf5c · outbound

This paper cites Cfa: Coupled-hypersphere-based fea- ture adaptation for target-oriented anomaly localization,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Cfa: Coupled-hypersphere-based fea- ture adaptation for target-oriented anomaly localization,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.628978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6b3ca598-f1fc-4a98-b040-8775d965e135 · outbound

This paper cites Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.618736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3f2e6e93-5ef0-4e05-b42e-a4182555fdac · outbound

This paper cites Padim: A patch distribution modeling framework for anomaly detection and localization,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Padim: A patch distribution modeling framework for anomaly detection and localization,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.608806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fc7d24a1-89ed-4c9e-87b8-1dc74adf153e · outbound

This paper cites Simplenet: A simple network for image anomaly detection and localization,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Simplenet: A simple network for image anomaly detection and localization,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.596759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d9198048-2dc7-4d8c-ae8f-167c6ff86ddb · outbound

This paper cites A hierarchical transformation- discriminating generative model for few shot anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization A hierarchical transformation- discriminating generative model for few shot anomaly detection,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.486711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cd9f5057-f679-49cd-8e6d-3ecc0ca3b0dd · outbound

This paper cites Same same but differnet: Semi-supervised defect detection with normalizing flows,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Same same but differnet: Semi-supervised defect detection with normalizing flows,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.427575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2f4f582d-0f30-4223-b1fb-26f8943edf46 · outbound

This paper cites Registration based few-shot anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Registration based few-shot anomaly detection,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.416937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f989690a-150c-4b4d-9b2e-2a6a553dcf9c · outbound

This paper cites Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T14:38:39.312050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4f797dc-dee8-482b-b770-b8996b5a3975 · outbound

This paper cites Explicit boundary guided semi-push-pull contrastive learning for supervised anomaly detection,.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Explicit boundary guided semi-push-pull contrastive learning for supervised anomaly detection,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:38:39.405814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 40d0a82e-6407-4cfc-a225-31582e189e29 · outbound

This paper cites an unresolved cited work.

AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization Unresolved cited work

Reference 2021

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:38:41.246804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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