Paper Citation Record · LEDGER

Background-Aware Defect Generation for Robust Industrial Anomaly Detection

As of 13 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2411.16767.

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

pith.paper-citation-record.v1
2411.16767 v2

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:39:56.246445Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

verified exact0
verified fuzzy15
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e87f1df7-9321-429f-838b-1f92f0191512 · outbound

This paper cites write newline.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.121791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 122a80b0-2450-4ffb-9e3d-438d2558786f · outbound

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

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Mvtec ad--a comprehensive real-world dataset for unsupervised anomaly detection

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.127530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4730b9ea-fd9f-445f-b9a4-1d60cc458755 · outbound

This paper cites Beyond dents and scratches: Logical constraints in unsupervised anomaly detection and localization.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Beyond dents and scratches: Logical constraints in unsupervised anomaly detection and localization

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.626792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 92063b95-949e-4b23-9b06-101059673807 · outbound

This paper cites Sub-Image Anomaly Detection with Deep Pyramid Correspondences.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Sub-Image Anomaly Detection with Deep Pyramid Correspondences

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.136148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d67ecce-6926-437b-881a-4a90b62d5722 · outbound

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

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Padim: a patch distribution modeling framework for anomaly detection and localization

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.612625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 83f4d8cc-7cab-4896-932d-4586dba698c4 · outbound

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

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Anomaly detection via reverse distillation from one-class embedding

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.600179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 92bcedee-c99f-4d0e-88a7-5ba7bc0cc7d7 · outbound

This paper cites Few-shot defect image generation via defect-aware feature manipulation.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Few-shot defect image generation via defect-aware feature manipulation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.580750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7c305aa7-5969-4dae-ad56-830226b1df4f · outbound

This paper cites Prompt-to-prompt image editing with cross-attention control.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Prompt-to-prompt image editing with cross-attention control

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.567996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 509fc2c3-9e43-4d77-a8d0-fbaa06bf4e0e · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.159701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d29dd8d9-2479-455c-86dd-8b626e5f1145 · outbound

This paper cites Denoising diffusion probabilistic models, 2020.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Denoising diffusion probabilistic models, 2020

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.163911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76038534-d412-4aa1-807e-882131c1f1d9 · outbound

This paper cites Anomalydiffusion: Few-shot anomaly image generation with diffusion model.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Anomalydiffusion: Few-shot anomaly image generation with diffusion model

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.534046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 091aad3a-4e6b-4fba-8d9f-9cab8991ee42 · outbound

This paper cites Fantastic Generalization Measures and Where to Find Them.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Fantastic Generalization Measures and Where to Find Them

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.172288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fead4640-af36-43d8-871c-4613d8358c96 · outbound

This paper cites Analyzing and improving the image quality of stylegan.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Analyzing and improving the image quality of stylegan

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.518812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ca601bd4-85f7-44f1-8790-ac31ee08f08c · outbound

This paper cites Saal: sharpness-aware active learning.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Saal: sharpness-aware active learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.502729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 252221a7-180c-45fe-9529-eabd7b81a2b8 · outbound

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

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Cutpaste: Self-supervised learning for anomaly detection and localization

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.487203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a8c28ab2-9f8b-4a3c-8047-ba85dbf82c45 · outbound

This paper cites Visualizing the loss landscape of neural nets.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Visualizing the loss landscape of neural nets

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.189446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74287493-946e-4af4-99f9-3a9e13a6c0ca · outbound

This paper cites Few-Shot Defect Segmentation Leveraging Abundant Normal Training Samples Through Normal Background Regularization and Crop-and-Paste Operation.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Few-Shot Defect Segmentation Leveraging Abundant Normal Training Samples Through Normal Background Regularization and Crop-and-Paste Operation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.193694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0969fbf2-0fc6-40ea-a960-5420cf1fd80f · outbound

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

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Simplenet: A simple network for image anomaly detection and localization

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.461705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3f3b1e04-8395-4728-b810-b8c1983d24ea · outbound

This paper cites Null-text inversion for editing real images using guided diffusion models.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Null-text inversion for editing real images using guided diffusion models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.447542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dce6b07c-9f06-4974-bd15-7898aa3c91e0 · outbound

This paper cites Shape-guided diffusion with inside-outside attention.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Shape-guided diffusion with inside-outside attention

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.430741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1cd13993-8dd3-4165-8ba2-8cda9c6d27c5 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection High-resolution image synthesis with latent diffusion models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.414546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5f67cd6b-3317-4b22-9afd-19b7f91e1a50 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection High-resolution image synthesis with latent diffusion models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.220172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1bb1d4b-0229-4681-ada5-2a3ea6d2a933 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection U-net: Convolutional networks for biomedical image segmentation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.224957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92c9c232-597f-4f9b-b8cf-8ec586c9b6ba · outbound

This paper cites Towards total recall in industrial anomaly detection.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Towards total recall in industrial anomaly detection

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.228837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20f1d13f-07cc-4da1-99b3-ef13c8d74099 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.372791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7a6a79a9-3fb9-4023-92dd-566fc55ab14a · outbound

This paper cites Denoising diffusion implicit models.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Denoising diffusion implicit models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:39:56.358498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ab9a005d-eebe-4569-88ef-0c279c227189 · outbound

This paper cites Score-based generative modeling through stochastic differential equations.

Background-Aware Defect Generation for Robust Industrial Anomaly Detection Score-based generative modeling through stochastic differential equations

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.242102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9204360d-edfe-41eb-b763-b2ae1c88d76b · outbound

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

Background-Aware Defect Generation for Robust Industrial Anomaly Detection The unreasonable effectiveness of deep features as a perceptual metric

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:56.246445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.