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Paper Citation Record · LEDGER

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis

As of 22 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 2 inbound Pith citation observations for arXiv:2412.06510.

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

pith.paper-citation-record.v1
2412.06510 v4

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:39:54.853057Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:47:34.394511Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T18:42:13.189314Z

Reference resolution

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy28
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 38c68c50-aaa7-4d84-850a-c15445b81090 · outbound

This paper cites write newline.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis write newline

Reference 1

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no resolver link, observed 2026-08-11T19:39:54.696138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.696138Z digest=sha256:862d8b9e00f34f767bc93c07b7a7f1ec11895485d9c736471f56a44a92cb4574

Observation 01215222-5ffe-42d6-bb7a-e7f2c3257d8e · outbound

This paper cites Blended latent diffusion.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Blended latent diffusion

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.315829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.701499Z digest=sha256:430e77c271f4cc02b3f46646c97d80a975ec18099cf73dd45a50eb83d89878f0

Observation 4f3b9dfa-4885-4217-8ae8-41c82fb1631f · outbound

This paper cites eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

Reference 3

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no resolver link, observed 2026-08-11T19:39:54.705992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.705992Z digest=sha256:425c209e278bc1f138eae8711084d36e25b5ff5e20138a6bd1c3beb8e04258c9

Observation 13c4d83e-3a14-4f15-94eb-5c3836bd5d9c · outbound

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

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Mvtec ad--a comprehensive real-world dataset for unsupervised anomaly detection

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.304004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.711454Z digest=sha256:b33b68931ff8c30c8879b5289373565f4266430d547e44c832c3f5fb427f4b27

Observation 3a1666ff-31e5-465f-a4f3-7c066c0c9c16 · outbound

This paper cites The mvtec anomaly detection dataset: a comprehensive real-world dataset for unsupervised anomaly detection.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis The mvtec anomaly detection dataset: a comprehensive real-world dataset for unsupervised anomaly detection

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.291957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.715392Z digest=sha256:3c3443bc1efd1706632f6a190436bf05cf56df20cc49147bf5348c19569b41f3

Observation fb576be1-e2be-47e2-b4db-7a6ec4f83b72 · outbound

This paper cites Demystifying MMD GANs.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Demystifying MMD GANs

Reference 6

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no resolver link, observed 2026-08-11T19:39:54.719898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.719898Z digest=sha256:49ba0c595e4b5fcb7480b5c53a36a2fa81f35df6e09d9b40fdb5975cf9cdb8eb

Observation ddef9a8c-f46e-42c9-aa29-fcc49a9aed8c · outbound

This paper cites Training-free layout control with cross-attention guidance.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Training-free layout control with cross-attention guidance

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.278200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.724848Z digest=sha256:3bac06a1d279e1f53084daac8e6436fe367fe629d209175bb90a8de84a80ec3d

Observation ea69ade1-69b6-40f4-beff-96c9ddcc29dc · outbound

This paper cites Easynet: An easy network for 3d industrial anomaly detection.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Easynet: An easy network for 3d industrial anomaly detection

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.266421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.728838Z digest=sha256:70de953dcdef3d1b1a1dee539972d1d5f13d1335136037ffd3a1f82fb98c6cc3

Observation 5f76ece7-8d71-4310-b6ee-44e705fb042c · outbound

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

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Few-shot defect image generation via defect-aware feature manipulation

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.255165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.732562Z digest=sha256:f04736a01f4cf154c24824f50c95f9a7fecede7a3ec384f9436424cdd50a02fa

Observation 6a145a20-d354-4e6f-9824-4d9a90f5e802 · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 10

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no resolver link, observed 2026-08-11T19:39:54.736167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.736167Z digest=sha256:d38e184590c1f8bf3349a55ed4889d207fd001e74ad7b3b12df6905c1910ba8b

Observation 031da804-ca9f-4dfc-8ec9-ebdd72812cd4 · outbound

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

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.244747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.740095Z digest=sha256:8bfe2f3d97ba5ff49ff25065acf40e49f4f49e0af2bf906a4a4d1390e4e5342a

Observation 8fd7bfc5-8316-4ac0-8d0e-78c8ea917146 · outbound

This paper cites Classifier-Free Diffusion Guidance.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Classifier-Free Diffusion Guidance

Reference 12

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no resolver link, observed 2026-08-11T19:39:54.743560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.743560Z digest=sha256:60822c0755c0c22ca93e26e83c8640ba38fd55acab24cd767633f32407e8f8bb

Observation ad95921e-c569-427b-8b9a-cbd4b989c1da · outbound

This paper cites AnomalyXFusion: Multi-modal Anomaly Synthesis with Diffusion.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis AnomalyXFusion: Multi-modal Anomaly Synthesis with Diffusion

Reference 13

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unresolved
no resolver link, observed 2026-08-11T19:39:54.747362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.747362Z digest=sha256:51b8374bf68da0f95878daf721f3c90a8a6969d44f2e66d2b928f20d64bdda59

Observation 10580814-1668-4cd4-a3ce-98928dd5a9e5 · outbound

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

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Anomalydiffusion: Few-shot anomaly image generation with diffusion model

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.233202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.751269Z digest=sha256:19e8d59b25dde66431a9cad7eb1e694ed95f3d4b0b261d82b9c1a98b1e448893

Observation f17be3d2-2aa4-4d6f-bba6-cbdcc7c8406f · outbound

This paper cites Adapting visual-language models for generalizable anomaly detection in medical images.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Adapting visual-language models for generalizable anomaly detection in medical images

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.222268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.754806Z digest=sha256:dc0e2e3bc87997cd13c056839da3a79e290b7c73ca022a1ebcb746417e8413f8

Observation ba6b43a2-5efd-488b-b6c9-9d5912712cf4 · outbound

This paper cites Auto-Encoding Variational Bayes.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Auto-Encoding Variational Bayes

Reference 16

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no resolver link, observed 2026-08-11T19:39:54.758304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.758304Z digest=sha256:f345f61ee5a07d760adf50fc009aa598e21f4a9e6b84ed7211e03c6967a21292

Observation c2063db1-94ba-41cd-8617-bba312eb9ee1 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.761811Z digest=sha256:bb4e9524670d25de2d4899894ca2a56d2d6873bee6b212184992b4bafe60caaf

Observation 295cf5a7-943c-4cbf-8230-3f398d38ed26 · outbound

This paper cites Deep industrial image anomaly detection: A survey.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Deep industrial image anomaly detection: A survey

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.199966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.765303Z digest=sha256:3e95ff752af9c3e45e1e91f464e987aa896b36e024ecf795fe8fdc361b3e3a22

Observation 6b57d535-99d3-41b7-93bc-d86bd1a9efe0 · outbound

This paper cites Decoupled Weight Decay Regularization.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Decoupled Weight Decay Regularization

Reference 19

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no resolver link, observed 2026-08-11T19:39:54.769297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.769297Z digest=sha256:6fbb8a32447f43b59ed4edee3e4f3598f3602ca32ea42d53547ad565d1bf0386

Observation c7556d83-a232-41cb-9687-ae09e662ca6c · outbound

This paper cites T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.189514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.773196Z digest=sha256:d903a8e993ada9650d8af8a1ebbf4217035de7b86c07dfba91fe63da612ed442

Observation e85f7adc-020e-4e9f-94fb-ce4c132ea748 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 21

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no resolver link, observed 2026-08-11T19:39:54.776819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.776819Z digest=sha256:2306fe6e665ed87959a367a2d1f61f46ee8b72e2be282615e2121e4e985de0ca

Observation 571047e0-c1e0-4c23-b1f9-9e11c8140f90 · outbound

This paper cites Defect image sample generation with gan for improving defect recognition.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Defect image sample generation with gan for improving defect recognition

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.178326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.780552Z digest=sha256:f34f2081b7779da149cfe72075afaa23c88e0345e4a967c790bbf039a1847c71

Observation 2d2e40fd-2154-4b6e-9e38-70adfdffc59c · outbound

This paper cites Few-shot image generation via cross-domain correspondence.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Few-shot image generation via cross-domain correspondence

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.165963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.784059Z digest=sha256:b90ece97ddc9d0a841602048623b5c267835d304b79f633ac25e65715273a945

Observation 73fe28a3-a0f0-49ce-a57f-b1e382ac0b90 · outbound

This paper cites Few-shot image generation via cross-domain correspondence.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Few-shot image generation via cross-domain correspondence

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.154026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.787405Z digest=sha256:5e6f3288ca4992ce835e59ca3825465ad7f8eaf229fa436638213b40b053220a

Observation 8ecc032c-4506-44fa-b168-38f5929b7052 · outbound

This paper cites Diffusers: State-of-the-art diffusion models.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Diffusers: State-of-the-art diffusion models

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.142066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.791099Z digest=sha256:ec137f87eadefba8003c1e8b3ee64dcab8ce61d1bbf8231ffd54b501cb8bf4fc

Observation 5bdd81bf-395d-4696-b35a-3e3b7c5788fe · outbound

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

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Learning transferable visual models from natural language supervision

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.130165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.794490Z digest=sha256:73264966d06353a7046a0bb10e769cef35fd127ba2f1731531b46aac4c98efd6

Observation e0443dbb-9cae-4f4b-ba08-ac7820bdde0a · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 27

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no resolver link, observed 2026-08-11T19:39:54.798623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.798623Z digest=sha256:fcb913ba2291c828a96cb95af21dedf97d32f49f129b56a79b2ba2ee699fd6b9

Observation ab1fb8ad-c1df-455f-8b14-118394ec92a7 · outbound

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

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis High-resolution image synthesis with latent diffusion models

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.119141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.802805Z digest=sha256:d8189686ddeb0e7e25701b7ca4109c47cb14a9a481b36e510b85d2baff163cf3

Observation f194e955-e8c3-424a-89e4-c5217a30121b · outbound

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

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis U-net: Convolutional networks for biomedical image segmentation

Reference 29

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raw_fallback, observed 2026-08-11T19:39:55.108212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.806638Z digest=sha256:6674ca474541b5fa7d6f0d873e6caaed8a684ea2d3f95be9042e54ed4248077c

Observation 5cfc38ce-2ece-4aa0-854f-bda92433b692 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Photorealistic text-to-image diffusion models with deep language understanding

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.096875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.810039Z digest=sha256:1efaa27b84561b8aac3f6142b7519d5a1812d868decfd71aead4072ea1e3b7ba

Observation 78a593ba-c2a1-400f-9be9-c8f2fe584ae5 · outbound

This paper cites Improved techniques for training gans.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Improved techniques for training gans

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.084249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.813802Z digest=sha256:eb8c7e01de5f1dd6e0775339f643a1690e9c986be0eb19a15ca8904a7fc39f61

Observation ce2c9015-dccd-4949-89bf-be74595e08fd · outbound

This paper cites Unseen Visual Anomaly Generation.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Unseen Visual Anomaly Generation

Reference 32

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unresolved
no resolver link, observed 2026-08-11T19:39:54.817686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.817686Z digest=sha256:e374101f95dd0faed1036a371677ba2218c788cf242347ffc662a676e5a9a997

Observation d42ef13c-1d87-42d3-ae1b-c848db7cb40d · outbound

This paper cites Raphael: Text-to-image generation via large mixture of diffusion paths.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Raphael: Text-to-image generation via large mixture of diffusion paths

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.073367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.821510Z digest=sha256:41a5e376d680649143ee685a2538fa1f3807d33283b771c3a49cd99c58704643

Observation e619a39b-dc79-482b-afae-53c7d94c7556 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 34

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no resolver link, observed 2026-08-11T19:39:54.825172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.825172Z digest=sha256:ff4791e54eaf55a997172e337a9e2e6ca8726320d979579ee188aae82c60f599

Observation 1006d9eb-9b50-464b-961b-c8907f6a0481 · outbound

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

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Draem-a discriminatively trained reconstruction embedding for surface anomaly detection

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.062195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.828906Z digest=sha256:369f323a302ab4af63000e40ac10a0d7f975d4fb432042e3f81a753b89add8de

Observation 0ecd8123-6582-4657-a45e-dc66cc9164b4 · outbound

This paper cites Defect-gan: High-fidelity defect synthesis for automated defect inspection.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Defect-gan: High-fidelity defect synthesis for automated defect inspection

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.050488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.833880Z digest=sha256:c17574da63db2cadf3b1ed5a59ccba0d476fa5a37607e4ec0243c887538ee6b7

Observation 8decdf59-a3e0-445d-b4b6-4fe93ceeadfa · outbound

This paper cites Prototypical residual networks for anomaly detection and localization.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Prototypical residual networks for anomaly detection and localization

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.039036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.837433Z digest=sha256:6b6028ceced050e9388dee013258b56f88fd0882ae51ed0f9448cdd3e1f8caa4

Observation cd4ea5a9-090e-4623-942d-7689cf8e915b · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Adding conditional control to text-to-image diffusion models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T19:39:54.840992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:39:54.840992Z digest=sha256:964467d7a979c29a6dd4f81d2918c355f4ce3ae3c8f0b1e75dbb31456a69f3b4

Observation 39449f6c-aed9-42a9-a71e-696102deb6a5 · outbound

This paper cites Realnet: A feature selection network with realistic synthetic anomaly for anomaly detection.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Realnet: A feature selection network with realistic synthetic anomaly for anomaly detection

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.020675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.845530Z digest=sha256:5355aa3ab356d1b8b300131262ea16399d5aab04023b27ec6785dac70b90e2b0

Observation 1faaee1e-76a6-4341-b7f9-bf82cec8ea66 · outbound

This paper cites Differentiable augmentation for data-efficient gan training.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Differentiable augmentation for data-efficient gan training

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:39:55.008768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.849516Z digest=sha256:6a051d2ced588d80fcdced9e9d7cd9a70678ac7b00d3cf1fa894bfbfa1e76744

Observation e6237db0-f3a4-43d9-b457-d90a56c223db · outbound

This paper cites Uni-controlnet: All-in-one control to text-to-image diffusion models.

AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis Uni-controlnet: All-in-one control to text-to-image diffusion models

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:39:54.996661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-11T19:39:54.853057Z digest=sha256:2111bd5e1ef4f6625cced29183c632fb650a2f9a666e3c97ec2195dee6396903

Pith citing papers

Observation 2ff69af7-e013-4a8d-b46c-c4117ae11461 · inbound

NexViTAD: Few-shot Unsupervised Cross-Domain Defect Detection via Vision Foundation Models and Multi-Task Learning cites this paper.

NexViTAD: Few-shot Unsupervised Cross-Domain Defect Detection via Vision Foundation Models and Multi-Task Learning AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:42:13.264332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:42:09.040717Z digest=sha256:f2e66fda3fe1e7be401be2bb27692b408b2ca971d7fefe6a63e8773db37d30b3

Observation 565b206b-0920-4c00-b170-7564554cdbd6 · inbound

DeCo: Zero-Shot Industrial Anomaly Generation through Decoupling and Recoupling cites this paper.

DeCo: Zero-Shot Industrial Anomaly Generation through Decoupling and Recoupling AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T00:47:34.394511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:47:34.394511Z digest=sha256:bd7426841bbe07d5d034044ef85e3f841ab9ac18b8c11e31731e0b4c3e1dbdbf