Paper Citation Record · LEDGER

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance

As of 12 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2512.00125.

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

pith.paper-citation-record.v1
2512.00125 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T19:41:16.250703Z

measured 39 of 39 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

39 of 39 outbound references displayed

verified exact0
verified fuzzy0
unresolved39
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 519fc6e6-7f8e-466f-b17c-5865df6e5316 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.121911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50309012-e74d-43d7-a708-0d3cff3b4da1 · outbound

This paper cites Physics-informed data-driven machine health monitoring for two-photon lithography.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Physics-informed data-driven machine health monitoring for two-photon lithography

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.126159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac165c7f-4dd3-4f96-8815-36878cf3a342 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.129884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7725eeaa-85ca-4a92-aa16-fc8e9d810060 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.133554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64d4f188-ac0a-498a-b551-d8a26fae8512 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.137128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b9872d8-b614-48eb-b79d-5a7a2a419df9 · outbound

This paper cites Canny, A computational approach to edge detection, IEEE Transactions on pattern analysis and machine intelligence (6) (2009) 679–698.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Canny, A computational approach to edge detection, IEEE Transactions on pattern analysis and machine intelligence (6) (2009) 679–698

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.141102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19f65d6e-e81d-45ad-abde-924295222a92 · outbound

This paper cites Archana, P.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Archana, P

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.144524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1265a08-2f9a-4b94-ac68-85cf05a01d83 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.147520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b8f451e-0ffa-4ec9-88be-890d54d36aef · outbound

This paper cites Chukwunweike, A.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Chukwunweike, A

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.150505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b6d0823-016f-4143-becf-825b9da6bd11 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.153518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 061399ed-24f3-41fe-b640-6ce5a4787557 · outbound

This paper cites Rauch, T.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Rauch, T

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.156611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db1c1a00-4496-4226-af9c-a46f96c09905 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.159623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8e9ed96-0192-487d-9fba-5bec0a9019e7 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.162499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 793cda07-8a13-4a97-bd1c-4e9cb8fa6f82 · outbound

This paper cites Sundaram, A.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Sundaram, A

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.165487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6561c66c-55cc-4361-b321-af644158bf84 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.168428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcc87e13-695a-48b5-a0b6-fc0a5f32060c · outbound

This paper cites Kodytek, A.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Kodytek, A

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.171311Z

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Unavailable: canonical work link unavailable.

Observation d4d0cdbd-be39-40c0-9c04-ca8fc19b82d3 · outbound

This paper cites Villalba-Diez, D.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Villalba-Diez, D

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.174047Z

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Unavailable: canonical work link unavailable.

Observation 6487256b-3391-4f20-96cf-7310bb8af468 · outbound

This paper cites Mehta, C.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Mehta, C

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.176860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e63110a8-ed2a-49b1-a3c8-ca73f7cbc82f · outbound

This paper cites Mehta, C.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Mehta, C

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.179673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3ab070f-9c00-4b14-b641-8e789c33930e · outbound

This paper cites Mehta, S.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Mehta, S

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.182547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 311e712b-f91d-472d-a44a-99a561ac1623 · outbound

This paper cites Bergmann, M.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Bergmann, M

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.185483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af473898-2070-4c90-8054-4f80325ba68b · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.189172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6aefdc5-b7ca-4a70-9f98-33a903b66d3f · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.192314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7bd5d6c-3c0b-4c7c-b9a5-33190526fbbb · outbound

This paper cites Buggineni, C.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Buggineni, C

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.195795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 638ab156-ac17-459b-aa66-e460403dc1dd · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.198995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 072360b3-0f7d-4ace-a734-0d6dd40f5131 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.202247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82d67d56-131b-4f79-bf18-98422f73c91e · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.207047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f9d6ca8-f66f-45a3-8b54-c35f194509a4 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.212526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 657db959-eafc-4f0f-9d1e-7774b7a1de03 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.217466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea033542-fd0f-466d-9fda-87551aa26ee6 · outbound

This paper cites Chen, et al., Dcgan-cnn with physical constraints for porosity prediction in laser metal deposition with unbalanced data, Manufacturing Letters 35 (2023) 1146–1154.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Chen, et al., Dcgan-cnn with physical constraints for porosity prediction in laser metal deposition with unbalanced data, Manufacturing Letters 35 (2023) 1146–1154

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.221120Z

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Unavailable: canonical work link unavailable.

Observation 70d6ea24-db39-4fa2-8d46-910ceb448d5e · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.224496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfc7027d-9f3f-4510-9008-a15e98af0ea2 · outbound

This paper cites Moonen, B.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Moonen, B

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.228026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 209e489a-cb73-48f7-bdb7-6c2ae22fc66a · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.231414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e22af107-5bbe-4382-84dd-8786bcaf0e34 · outbound

This paper cites Neunzig, D.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Neunzig, D

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.234884Z

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Unavailable: canonical work link unavailable.

Observation ffb7c652-32f1-4a31-a177-4d2d6b417a70 · outbound

This paper cites Salvato, G.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Salvato, G

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.237775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18453841-8906-4071-8504-b98fa748c7f7 · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.241110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91eb85d8-112a-446b-a820-e4220370ab68 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.244596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf02e9d4-4bd9-4764-9f94-a5c3350db592 · outbound

This paper cites Zhang, Z.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Zhang, Z

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.247749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f7c9a37-16c7-482d-ac64-038c3bde5da0 · outbound

This paper cites an unresolved cited work.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Unresolved cited work

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T19:41:16.250703Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.