Paper Citation Record · LEDGER

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality

As of 18 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 1 inbound Pith citation observation for arXiv:2509.09375.

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

pith.paper-citation-record.v1
2509.09375 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:14:15.684603Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:14:14.265834Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

verified exact0
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 78babe50-e5de-45e7-8924-13ff3a852884 · outbound

This paper cites Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:14.265834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d82c4cd-cbf7-4aad-8ca9-6f55cf79af12 · outbound

This paper cites an unresolved cited work.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:14.411911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82fd2dd2-492a-41c2-a860-a19495c63ad3 · outbound

This paper cites Implementation Details:We use ViT-Base/14 with DINOv2-R pre-trained weights [14] as the default encoder.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Implementation Details:We use ViT-Base/14 with DINOv2-R pre-trained weights [14] as the default encoder

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:14.519296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 927e40b1-9eb9-4650-8237-e620ac9b9e28 · outbound

This paper cites A learnable normal information extractor distills stable and representative features of normal regions.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality A learnable normal information extractor distills stable and representative features of normal regions

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:14.665021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f6f4370-4886-4981-bdeb-c9c902ec2b04 · outbound

This paper cites Musc: Zero-shot industrial anomaly classification and segmentation with mutual scoring of the unlabeled im- ages,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Musc: Zero-shot industrial anomaly classification and segmentation with mutual scoring of the unlabeled im- ages,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:14.742718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b98a190-038f-413a-8b58-5c8190afbcb1 · outbound

This paper cites Winclip: Zero-/few-shot anomaly classification and segmentation,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Winclip: Zero-/few-shot anomaly classification and segmentation,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:14.879655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e531eec2-4492-446a-b4f8-12cb14cd2ef4 · outbound

This paper cites A reconstruction-based feature adaptation for anomaly detection with self-supervised multi-scale ag- gregation,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality A reconstruction-based feature adaptation for anomaly detection with self-supervised multi-scale ag- gregation,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.022686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5676f35e-0b24-4308-b739-88aca86ca591 · outbound

This paper cites Transfusion–a transparency-based diffusion model for anomaly detection,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Transfusion–a transparency-based diffusion model for anomaly detection,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.129285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e0362bc-854a-4479-bba2-f44680edb491 · outbound

This paper cites Glad: Towards better reconstruction with global and local adaptive diffusion models for unsupervised anomaly detection,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Glad: Towards better reconstruction with global and local adaptive diffusion models for unsupervised anomaly detection,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.184771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3323371d-69cb-47a9-94e2-d4d7b783729a · outbound

This paper cites A diffusion-based framework for multi-class anomaly detection,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality A diffusion-based framework for multi-class anomaly detection,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.217805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e131b0c-3a6e-4cad-9cd8-905c6bd3f490 · outbound

This paper cites Aa-clip: Enhancing zero-shot anomaly detection via anomaly-aware clip,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Aa-clip: Enhancing zero-shot anomaly detection via anomaly-aware clip,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.272735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59211ba7-3c55-4d8c-acad-64af54c55680 · outbound

This paper cites Anomalygpt: Detecting industrial anomalies using large vision-language mod- els,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Anomalygpt: Detecting industrial anomalies using large vision-language mod- els,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.321038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f92926ed-2263-41ff-87e3-c1b34e7bb8b9 · outbound

This paper cites Promp- tad: Learning prompts with only normal samples for few-shot anomaly detection,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Promp- tad: Learning prompts with only normal samples for few-shot anomaly detection,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.375155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8712c310-590f-42c0-976c-657140f4b683 · outbound

This paper cites A masked autoencoder-based approach for de- fect classification in semiconductor manufacturing,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality A masked autoencoder-based approach for de- fect classification in semiconductor manufacturing,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.418115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec2c219a-851e-44ff-b589-cf182d002d4c · outbound

This paper cites A novel joint segmentation approach for wafer surface defect classification based on blended net- work structure,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality A novel joint segmentation approach for wafer surface defect classification based on blended net- work structure,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.486056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd23d297-1ba3-4f1f-b78e-e30915598215 · outbound

This paper cites Deepsem-net: Enhancing sem defect analy- sis in semiconductor manufacturing with a dual-branch cnn-transformer architecture,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Deepsem-net: Enhancing sem defect analy- sis in semiconductor manufacturing with a dual-branch cnn-transformer architecture,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.533452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04d58b4e-4ece-48a3-b420-7ee19505e531 · outbound

This paper cites Fabgpt: An efficient large multimodal model for complex wafer defect knowledge queries,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Fabgpt: An efficient large multimodal model for complex wafer defect knowledge queries,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.588669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 074847cd-7d7e-4632-90ab-04f6897547da · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality DINOv2: Learning Robust Visual Features without Supervision

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.636242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9262f8c-fb68-4a43-b4c7-47d6b743b0b3 · outbound

This paper cites Anomalyclip: Object-agnostic prompt learning for zero-shot anomaly detection,.

Unsupervised Integrated-Circuit Defect Segmentation via Image-Intrinsic Normality Anomalyclip: Object-agnostic prompt learning for zero-shot anomaly detection,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T19:14:15.684603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 78babe50-e5de-45e7-8924-13ff3a852884 · inbound