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Paper Citation Record · LEDGER

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift

As of 7 August 2026, this Paper Citation Record lists 100 of 113 outbound references and 0 inbound Pith citation observations for arXiv:2607.18072.

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

pith.paper-citation-record.v1
2607.18072 v1

Coverage vector

measured 100 of 113 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T16:19:07.949272Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

100 of 113 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved99
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9d74ff59-9ef2-43ef-9ff8-a42fd1067001 · outbound

This paper cites SIGKDD , pages =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift SIGKDD , pages =

Reference 1

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source=arxiv_source observed=2026-08-01T16:18:02.313724Z digest=sha256:b0c87cce07a5ce90cc8951f6fdf2db57d0cd8df6be97372b59b9c6d0a4d61ea7

Observation a82a5623-1593-4607-a675-05accb38543e · outbound

This paper cites Towards Concise Models of Grid Stability , booktitle =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Towards Concise Models of Grid Stability , booktitle =

Reference 2

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source=arxiv_source observed=2026-08-01T16:19:07.397336Z digest=sha256:9c709285c791a0b5f747b91c04803589fd5a003045d75d33c9e9462d2117054c

Observation 0675f8e6-fa26-4318-b944-905ec9ea4780 · outbound

This paper cites Multiclass classification of dry beans using computer vision and machine learning techniques , journal =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Multiclass classification of dry beans using computer vision and machine learning techniques , journal =

Reference 3

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Observation 459ff116-f627-40ae-abe1-99aae57fde4a · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-01T16:19:07.458056Z digest=sha256:29b69d47e6d59f2cf9616bffa11eb87384252afb514b9bb712897610450004c5

Observation 781a0c26-c068-46ae-9240-38c36f7b2949 · outbound

This paper cites Challenges in benchmarking stream learning algorithms with real-world data , journal =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Challenges in benchmarking stream learning algorithms with real-world data , journal =

Reference 5

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source=arxiv_source observed=2026-08-01T16:19:07.479295Z digest=sha256:d79e6fb871c19448fb5adcd0bef7c2db1198171f431b538868f206a4f59f165c

Observation f86379eb-6080-4428-a6a7-f47b41b53fe5 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 6

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source=arxiv_source observed=2026-08-01T16:19:07.484311Z digest=sha256:37e68b30ecdcdfac78ed19d1b1848f16fd463b65605fa158e0f7ff2072eb93bf

Observation 3bf07703-63c6-4186-94bf-8dd2e1ecac03 · outbound

This paper cites Single-Domain Generalization in Medical Image Segmentation via Test-Time Adaptation from Shape Dictionary , booktitle =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Single-Domain Generalization in Medical Image Segmentation via Test-Time Adaptation from Shape Dictionary , booktitle =

Reference 7

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source=arxiv_source observed=2026-08-01T16:19:07.492250Z digest=sha256:b54f2a4eb70ef28411386c808c10f083632a49bd0882792cf0b68cf772603c07

Observation 3dd339f7-3291-436a-a281-09cb5ee8d30b · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-01T16:19:07.498761Z digest=sha256:7d17fb9c700014afdb49b76571ad89682d16569f67aafbbf803cd1597d9c35a6

Observation 5216f18d-baf1-4bf7-82a6-c47edb823ece · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 9

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source=arxiv_source observed=2026-08-01T16:19:07.505340Z digest=sha256:25cbe10ca02f921d23b3c4eb8f503bb06fb52d1a3daaeed398dd2fa280933e92

Observation 440e6634-5cc0-4761-bd39-c426f4e128c5 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 10

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source=arxiv_source observed=2026-08-01T16:19:07.511826Z digest=sha256:c117ec94d5e12be9935796d28592eb0834816cf61638f4e43b2a56a5738689ce

Observation 53f3d4c0-f4ed-4534-8de4-173d266abc01 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 11

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source=arxiv_source observed=2026-08-01T16:19:07.517788Z digest=sha256:60b885361c7577f2679ea8b234a84490c033dbc2128627ad2df4237c4e7ffb96

Observation 2ae73b5f-6df5-408a-ab6d-a24037d726b9 · outbound

This paper cites Modeling Tabular data using Conditional.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Modeling Tabular data using Conditional

Reference 12

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source=arxiv_source observed=2026-08-01T16:19:07.526682Z digest=sha256:3709d90ef523f9d8769fe8b7b03570bf4e11af7c54f1ecbaa57bfbc48faf70e6

Observation e0d1b6ed-4278-4e46-95c6-298d16a4358f · outbound

This paper cites Conditional.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Conditional

Reference 13

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source=arxiv_source observed=2026-08-01T16:19:07.536507Z digest=sha256:a352774d8c741c0750064ee37d8201e2a1c2d0cff043dfcca144b6c88fbff6e1

Observation 7c253889-9003-45f1-baa8-7feafdeaef20 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 14

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source=arxiv_source observed=2026-08-01T16:19:07.547502Z digest=sha256:50e874aaec24ce27f62bc8b96c6cca73f1182b13600c920a337a4475f7ec5d4d

Observation 459c54f7-354d-4741-b688-693eca2c5291 · outbound

This paper cites Classification Accuracy Score for Conditional Generative Models.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Classification Accuracy Score for Conditional Generative Models

Reference 15

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source=arxiv_source observed=2026-08-01T16:19:07.559228Z digest=sha256:12525c960e285a9aa2da304cb1dd644ed3eb136ba336f106e438811ec3b93047

Observation d55dc45f-bbb7-4aef-bd3d-ad08444d47ed · outbound

This paper cites MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification

Reference 16

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source=arxiv_source observed=2026-08-01T16:19:07.566270Z digest=sha256:f230cf99d68c596718ef0b8698c38ccbc79abc01b3738cd92437c6bfcd4e5624

Observation 4f48a03f-d468-4992-838b-fa84ca2bdfd4 · outbound

This paper cites Skin lesion analysis toward melanoma detection 2018: A challenge hosted by the international skin imaging collaboration (.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Skin lesion analysis toward melanoma detection 2018: A challenge hosted by the international skin imaging collaboration (

Reference 17

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source=arxiv_source observed=2026-08-01T16:19:07.572638Z digest=sha256:c11172939d47f5cdbf7f058e7d799b046f1664bc57be0ed853469103bd8d3325

Observation 321a2d97-f4ff-42a1-ae2c-5982d1b356a5 · outbound

This paper cites 2020 , author =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift 2020 , author =

Reference 18

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source=arxiv_source observed=2026-08-01T16:19:07.576575Z digest=sha256:6b0c9020fa8bd823b7796fa4dd0fadac1f65c2d58d1ca6aeefe010b5d6742361

Observation 0299025a-a7d6-40d9-b510-93597a96b237 · outbound

This paper cites NeurIPS Workshop , year=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NeurIPS Workshop , year=

Reference 19

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source=arxiv_source observed=2026-08-01T16:19:07.582911Z digest=sha256:720719eaaddbddbed05f93a5d7a45dac66dbfc1a2f08000daec36a7ba933f07c

Observation a59230b8-7ee8-4824-9151-db4687715c8d · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 20

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source=arxiv_source observed=2026-08-01T16:19:07.588182Z digest=sha256:ce53d6a1bc26fae7fd1165cd298558945cf07a1f45270c40e7fb3852bcdee916

Observation 8522d7a6-f565-4835-94d4-d494c9e1d49c · outbound

This paper cites Proceedings of the IEEE , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Proceedings of the IEEE , volume=

Reference 21

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source=arxiv_source observed=2026-08-01T16:19:07.594494Z digest=sha256:48388f17df6cae04bd75e5d5a2c890dfcd481612278c8b6368ede70fe15375ba

Observation 65ed6979-1246-4117-be60-d7f74946749d · outbound

This paper cites Understanding the Limitations of Conditional Generative Models , booktitle =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Understanding the Limitations of Conditional Generative Models , booktitle =

Reference 22

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source=arxiv_source observed=2026-08-01T16:19:07.599201Z digest=sha256:ef5d227fbc03f150f7229fa999dc320d6acc8056c3af4c283f2578b4fee6679e

Observation c155ab55-34cb-4c2a-bcd2-2e0764695e90 · outbound

This paper cites SIGKDD , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift SIGKDD , pages=

Reference 23

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source=arxiv_source observed=2026-08-01T16:19:07.604917Z digest=sha256:edc1ff22a2f76eec0a49ae57cc033e0bd7eb35ff5e9d7b8fcbfa3793c6e2f0df

Observation 55ada273-c216-4e63-98ed-594d3523eb92 · outbound

This paper cites Neurocomputing , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Neurocomputing , volume=

Reference 24

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source=arxiv_source observed=2026-08-01T16:19:07.612180Z digest=sha256:68184ed34279f763cd613f2df5ef55a47e1eef3a6a4e075f700c8c23b50249d4

Observation 3ed00e07-4067-4829-84c6-ba51d6b7125e · outbound

This paper cites ICCV , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICCV , pages=

Reference 25

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source=arxiv_source observed=2026-08-01T16:19:07.617985Z digest=sha256:f84bc68107c845946fab6d8bcb1724f5dfadfdea75f5986461300382e3145ac0

Observation 7fb2a79d-6561-45c9-ae41-52159958ef68 · outbound

This paper cites ICCV , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICCV , pages=

Reference 26

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source=arxiv_source observed=2026-08-01T16:19:07.622617Z digest=sha256:8eb19936d698ebb86cbcc735611e9de3aaa4ce492b937635d0564cbb668d6352

Observation e42b29ba-ebb1-4ecf-ac91-a87aa644fede · outbound

This paper cites NIPS 2016 Tutorial: Generative Adversarial Networks.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NIPS 2016 Tutorial: Generative Adversarial Networks

Reference 27

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source=arxiv_source observed=2026-08-01T16:19:07.628406Z digest=sha256:2a21b9695a85014d125d51a291e9ac91ecb0a6e5caf7fef41c0f9a9f12387d68

Observation 48249d86-490f-4069-9b36-86d7de3a5262 · outbound

This paper cites Survey of Generative Methods for Social Media Analysis.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Survey of Generative Methods for Social Media Analysis

Reference 28

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source=arxiv_source observed=2026-08-01T16:19:07.635533Z digest=sha256:d2c2e70cb3e84c341f4077d70d796f36bd03bae9756f161008fe0ab956265214

Observation ab8f53c8-a8ad-4f20-81f3-ca00f7ca4a1b · outbound

This paper cites ACM Computing Surveys , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ACM Computing Surveys , volume=

Reference 29

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source=arxiv_source observed=2026-08-01T16:19:07.642074Z digest=sha256:68172fa45df232a287c38746f2068172b68705f70cc93cc5c145bf6c36c67197

Observation 319d555b-091c-4ff8-9efa-c7ae3334515e · outbound

This paper cites ISCV , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ISCV , pages=

Reference 30

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source=arxiv_source observed=2026-08-01T16:19:07.651908Z digest=sha256:2376975d949c81868857db00460658388a6823d90c48801f929059fa0ab084b9

Observation 92f45f02-f9cb-4f5c-bf9a-7bc22bb169c9 · outbound

This paper cites AI EDAM , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift AI EDAM , volume=

Reference 31

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source=arxiv_source observed=2026-08-01T16:19:07.661248Z digest=sha256:1e9c12dac40735fe142137bdce1f436ac6c7f0b128330f1e394c5c911dfc85fb

Observation a70de847-4b5c-4ec6-822b-a92ad3bad037 · outbound

This paper cites ImageNet Classification with Deep Convolutional Neural Networks , volume =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ImageNet Classification with Deep Convolutional Neural Networks , volume =

Reference 32

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source=arxiv_source observed=2026-08-01T16:19:07.675803Z digest=sha256:f727f598fdd0de4c2545cb9d3fdeee68909ffed0ab5427e9506f86c0fbe42438

Observation 12f5bbbc-933e-455c-96f2-748db19a8f6e · outbound

This paper cites and Karypis, G.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift and Karypis, G

Reference 33

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source=arxiv_source observed=2026-08-01T16:19:07.682063Z digest=sha256:3debe19a64afcaadc3ba88b5c925d4792d61f9f6eda4bada9adc1fa618f93c5a

Observation cf0d3729-5b8f-426c-b444-eb2cd6d57b1d · outbound

This paper cites Journal of the American Statistical association , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Journal of the American Statistical association , volume=

Reference 34

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source=arxiv_source observed=2026-08-01T16:19:07.686392Z digest=sha256:f8d037b5b0c0098cfec37fa25f5939737e9f9ffba30894e31cc3afcf446770f9

Observation f982a269-508f-48ac-85f4-3f96714297fd · outbound

This paper cites NIPS , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NIPS , pages=

Reference 35

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source=arxiv_source observed=2026-08-01T16:19:07.691313Z digest=sha256:7f2edf180fddd7726654dde25091b9586ee8659e7eb10e60f33dcabfd986a824

Observation 42fd0795-f69c-4b71-a2c3-4ad5c064d35d · outbound

This paper cites Self-Tuning Spectral Clustering , booktitle =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Self-Tuning Spectral Clustering , booktitle =

Reference 36

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source=arxiv_source observed=2026-08-01T16:19:07.696261Z digest=sha256:0f41061d9e81e1a22bc0bdd187a2b3d1ce843e8ab209793a3d8db1e090c8a06a

Observation 24131f7c-ccea-4978-8e77-9f08ae5f2e68 · outbound

This paper cites Cohen , title =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Cohen , title =

Reference 37

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source=arxiv_source observed=2026-08-01T16:19:07.701958Z digest=sha256:0e0034c5a3cf94accaf9e25c68084f4b89c22a06ac8f795bf5008a4a3e8e383a

Observation f959821b-0931-4712-9fbb-e6c0e4482490 · outbound

This paper cites 2012 , school=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift 2012 , school=

Reference 38

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source=arxiv_source observed=2026-08-01T16:19:07.708330Z digest=sha256:bf5b3d96ee073cf069e0464755c965e1b42a995490ed5161044f9fa20808c6fa

Observation 4633ead6-fe68-48e0-a403-dd10e7fec128 · outbound

This paper cites Applied intelligence , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Applied intelligence , volume=

Reference 39

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source=arxiv_source observed=2026-08-01T16:19:07.716297Z digest=sha256:4ca4d535f0468e3cb1374d115ae8dae528943885e6abec07aa72c2532b042ab3

Observation 60878753-74fd-4baf-8616-d41ec8e8daac · outbound

This paper cites WWW , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift WWW , pages=

Reference 40

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source=arxiv_source observed=2026-08-01T16:19:07.731159Z digest=sha256:87466ac6962dc501aa43a52b667dbe3bc328ecda72948d77b3f924620c7d0e72

Observation c719bfaa-b5df-4b34-b60d-ba096c3fd3a7 · outbound

This paper cites SIGKDD , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift SIGKDD , pages=

Reference 41

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source=arxiv_source observed=2026-08-01T16:19:07.737273Z digest=sha256:9f4ef124c0d8eac94dc58486fe81d6937b48387eae96572b24d2fdfde542488e

Observation bfb23bf6-950b-4daa-b181-9ce7e3d84d7f · outbound

This paper cites IEEE Transactions on pattern analysis and machine intelligence , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift IEEE Transactions on pattern analysis and machine intelligence , volume=

Reference 42

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source=arxiv_source observed=2026-08-01T16:19:07.744244Z digest=sha256:f39291effa1dfe22420aa6fc7201dd57d566483e1a2f447aa0bfc935259622bd

Observation 705de297-8f92-43ea-89b4-eb7216e43fbb · outbound

This paper cites NIPS , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NIPS , pages=

Reference 43

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source=arxiv_source observed=2026-08-01T16:19:07.749180Z digest=sha256:61fe18f0ce6e4ef8e50ccec7ed2dded530ab521e87c613f56af38008482e3023

Observation 665be2fd-637b-4f37-bbb0-0b4735ef0e24 · outbound

This paper cites ICDM , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICDM , pages=

Reference 44

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source=arxiv_source observed=2026-08-01T16:19:07.755328Z digest=sha256:ab888a140203cecf44e8e803970d3962f6e642478b9ec4c57368ee8f527c6e3e

Observation 24daa3ce-e3e9-40ed-9ae7-cc39713910e1 · outbound

This paper cites SIGKDD , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift SIGKDD , pages=

Reference 45

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source=arxiv_source observed=2026-08-01T16:19:07.760612Z digest=sha256:023b0ef103ec58b4b2ecbab3030c0be7d0a789e102def0f84a62cd21f13ac48f

Observation 721aff7a-436c-4d5c-9103-bb59a50ca4ed · outbound

This paper cites ICCV , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICCV , pages=

Reference 46

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source=arxiv_source observed=2026-08-01T16:19:07.774175Z digest=sha256:3e69c170ee70b71e43b7416124f6d3b1279905f4e3dbd873a2b4e41bb0399521

Observation f8b1e3a9-c8a6-47f7-bd6e-7b856be7632b · outbound

This paper cites CVPR , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift CVPR , pages=

Reference 47

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source=arxiv_source observed=2026-08-01T16:19:07.778759Z digest=sha256:bde5f1d21f872174a691f809c92739137f8b99d3e85ed97d3dcd02ca2e2c684e

Observation 71ccbd66-2631-4e99-9ec6-6d4115897a1c · outbound

This paper cites The Journal of Machine Learning Research , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift The Journal of Machine Learning Research , volume=

Reference 48

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source=arxiv_source observed=2026-08-01T16:19:07.781414Z digest=sha256:42a8fc4ec6d2cd6c17c5193a9e107c7344b69d5277d2e75248e59199b7985b15

Observation 44991c01-545b-468a-9dd0-0480c185fc78 · outbound

This paper cites , author=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift , author=

Reference 49

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source=arxiv_source observed=2026-08-01T16:19:07.784036Z digest=sha256:9b9e360942175d5c3c9ef9e4953db3a8fd305026b95960904908fc2b6fe668f6

Observation c1390421-bf91-481a-8625-6539d13379eb · outbound

This paper cites ICML , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICML , pages=

Reference 50

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source=arxiv_source observed=2026-08-01T16:19:07.786699Z digest=sha256:fb8866193a0d48d91289c8075a6bafb2b6cf0b5234160a7e1121f7e06e9a748e

Observation e7fa528e-b4d5-4e2e-b897-81181c149580 · outbound

This paper cites Pattern Recognition , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Pattern Recognition , volume=

Reference 51

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source=arxiv_source observed=2026-08-01T16:19:07.789921Z digest=sha256:912c05fb563a36fdd113b6d8832f33c73077bf49deba29f316939be524af4f23

Observation c7ad4c8d-dea6-4df3-b328-2c2a015ce44e · outbound

This paper cites IEEE Transactions on Geoscience and Remote Sensing , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift IEEE Transactions on Geoscience and Remote Sensing , volume=

Reference 52

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source=arxiv_source observed=2026-08-01T16:19:07.793275Z digest=sha256:780045bec8bdcc6e9a66e58aae9665b974b7ba69c55c1c6fce42a06f1b63db5e

Observation 5ee37895-3a1b-418a-ba09-0253639d871d · outbound

This paper cites Neurocomputing , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Neurocomputing , volume=

Reference 53

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source=arxiv_source observed=2026-08-01T16:19:07.797010Z digest=sha256:1990a66987b35f9f44b1ef6245a80ee7984f4782694477c39e3597aad361cf59

Observation a7829834-6acd-47a6-b4cb-ff54137d5954 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 54

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source=arxiv_source observed=2026-08-01T16:19:07.799846Z digest=sha256:c259a017c86ccc399905f259d4acdd72499da7f97f0b2be8e4f2c5fff19af34c

Observation 627ca618-cef3-4c72-834e-65d1c9fffe89 · outbound

This paper cites CVPR , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift CVPR , pages=

Reference 55

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source=arxiv_source observed=2026-08-01T16:19:07.802595Z digest=sha256:4c8d922be4b65583fbf402de893377d12cb051f3888cd85109bb2f6080acdadb

Observation 53ec377b-4d69-467d-aae9-36765f7616c8 · outbound

This paper cites Instance-Conditioned.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Instance-Conditioned

Reference 56

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source=arxiv_source observed=2026-08-01T16:19:07.805369Z digest=sha256:deb690643e444ca1da100b5f1ce5a8994e16f8aa2f99ba426cf9bdfbac2b299d

Observation 740f05a8-eed1-4bcd-9062-049440ed0f90 · outbound

This paper cites CVPR , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift CVPR , pages=

Reference 57

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source=arxiv_source observed=2026-08-01T16:19:07.808182Z digest=sha256:36d56d51305394bcace95630d757abd4efe699a63a6030916951d313fdddad59

Observation fe98bf31-3d9d-47b4-af52-846173f333cc · outbound

This paper cites NIPS , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NIPS , volume=

Reference 58

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source=arxiv_source observed=2026-08-01T16:19:07.811273Z digest=sha256:720d08e3aa221b510bfbb5589c334bddd0cdf83e859087fabd28074616f15ac2

Observation ea7d18ae-06ac-4c89-84b0-a12275310240 · outbound

This paper cites ICML , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICML , pages=

Reference 59

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source=arxiv_source observed=2026-08-01T16:19:07.814175Z digest=sha256:6a40796b1e0170aa5719115edb4fd81ed7588ce7a1ac82c4479c07528ada6a27

Observation 7ef51de3-dfd4-4e64-be99-dbb6c4ba425f · outbound

This paper cites 2021 , isbn =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift 2021 , isbn =

Reference 60

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source=arxiv_source observed=2026-08-01T16:19:07.817027Z digest=sha256:0984de5be5c35365993417b948b9f1b4a609c5db173a7de53b41ea256611ed18

Observation 408f38c6-d463-4c17-97bb-a67f696f4757 · outbound

This paper cites NIPS , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NIPS , volume=

Reference 61

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source=arxiv_source observed=2026-08-01T16:19:07.820547Z digest=sha256:cdeaff799ceda2c9725708c446914ddf1dc9e0a856259f5569e3c205bf4d6cd9

Observation a0b7509d-c70a-42a9-8e2b-506824d2a9c6 · outbound

This paper cites Kingma and Max Welling , title =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Kingma and Max Welling , title =

Reference 62

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no resolver link, observed 2026-08-01T16:19:07.823440Z

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source=arxiv_source observed=2026-08-01T16:19:07.823440Z digest=sha256:5176173f54e92737cbe0d647926eab545aa13b2eb4ec005b4ec54e58c51472b8

Observation 9f7e036c-c7a5-401a-837a-756f99fef3b8 · outbound

This paper cites Conditional Generative Adversarial Nets.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Conditional Generative Adversarial Nets

Reference 63

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source=arxiv_source observed=2026-08-01T16:19:07.826173Z digest=sha256:6ed88527e58f86d1d1da0517d2663de2951b25c8bc0b466355968bfcb293ab4f

Observation 2cf5de85-a9fe-4805-84e3-2171f5cf055c · outbound

This paper cites NIPS , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NIPS , volume=

Reference 64

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source=arxiv_source observed=2026-08-01T16:19:07.829875Z digest=sha256:8e4fd2011347a538dc5bb451df16ffdbc56e6f27ef4ab3c6ab368d1847c69135

Observation 09485423-54af-4744-be8f-c9fb72796a4a · outbound

This paper cites Xing , title =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Xing , title =

Reference 65

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source=arxiv_source observed=2026-08-01T16:19:07.832798Z digest=sha256:e97cc33667d1a920d59209f36f7c555cd6a55689b09b51eb60d1442d2b582ff3

Observation 508f450b-f20e-48f0-b573-ecb613c970cf · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 66

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source=arxiv_source observed=2026-08-01T16:19:07.836122Z digest=sha256:b0a1f83c165b3b5c96bcf391b913ed52aaf54c8cc1438bec0271e46e20557a61

Observation 08e8defc-007a-47a0-a445-09e82b5b1a41 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 67

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source=arxiv_source observed=2026-08-01T16:19:07.839350Z digest=sha256:1dd027d514b746c2ea395c0395ce2e181236974815c99da0ea135de090a7be90

Observation 682f4d88-cbd7-42db-a884-03afd1c73168 · outbound

This paper cites 2022 , issn =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift 2022 , issn =

Reference 68

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source=arxiv_source observed=2026-08-01T16:19:07.842621Z digest=sha256:c5ed6d92924522053a3bdfb9b56bb81d3d020b7cdbdb6ee632e75bbfdae63b2a

Observation a77b2e15-2be4-42ca-a8bf-9576b638fa39 · outbound

This paper cites Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data

Reference 69

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source=arxiv_source observed=2026-08-01T16:19:07.845938Z digest=sha256:f6de272e2a7f930e4842cef568cf2111bb88ad1610dd733af1909a3ed19581a5

Observation 2342bcd2-f866-4f21-9b57-7818d0edcff5 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 70

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source=arxiv_source observed=2026-08-01T16:19:07.849142Z digest=sha256:20128f3bd5e1ea2cf1669250733fe606b9fd1b33219ebd308359e3538d5d4198

Observation f2497e9e-4237-4cac-a9c7-587ae8c60434 · outbound

This paper cites ICML , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICML , pages=

Reference 71

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source=arxiv_source observed=2026-08-01T16:19:07.852342Z digest=sha256:b5940098b89265f6eeab67e3d124caf773de01aaba892dfec3bca3c2901999e2

Observation 9ad6c995-654a-4cdb-bf6b-9e3942916e79 · outbound

This paper cites ICML , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICML , pages=

Reference 72

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source=arxiv_source observed=2026-08-01T16:19:07.856240Z digest=sha256:6bfe89ef690c228c07aaeafde680f7f88a852f76104213827b553cf7374d779d

Observation 1e6cd242-7fd4-41f8-85c5-53caecf6d018 · outbound

This paper cites ICCV , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift ICCV , pages=

Reference 73

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source=arxiv_source observed=2026-08-01T16:19:07.859142Z digest=sha256:6363c6ca94cf19664f3ee341aff6a28510ea10df63755687ce5febd09dbe9035

Observation 37cf3616-9181-426e-8f5f-c1d0afeb1172 · outbound

This paper cites CVPR , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift CVPR , pages=

Reference 74

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source=arxiv_source observed=2026-08-01T16:19:07.862037Z digest=sha256:adbb71fc0cd27dfccbee5a4d8e9c950c273118fe30e738d7227b50f141f1cea3

Observation fcfa33bf-4dc6-416a-8d61-5d9803c08a0d · outbound

This paper cites WACV , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift WACV , pages=

Reference 75

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no resolver link, observed 2026-08-01T16:19:07.864894Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T16:19:07.864894Z digest=sha256:2e585661637ccf7f40a5c45f6a5efaf5daa223f5938f0dba1b6b994d2a6b3c16

Observation 3f653a7a-f895-4bf9-a2e8-991a546d2641 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 76

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:07.867852Z digest=sha256:78a6e87b6b21f63d2140a0a4ea1e4c414553d8a3eb404b068f06b242ad315825

Observation 26e18f16-508e-4dfc-a537-577328d7ebcb · outbound

This paper cites , author=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift , author=

Reference 77

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no resolver link, observed 2026-08-01T16:19:07.871741Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:07.871741Z digest=sha256:9000a9ede3a737a26d5e5893b238b345a10b501dc39deb1b7842418ae7e88dda

Observation 442f682f-226f-4ce1-aee4-888d2aede1d9 · outbound

This paper cites IEEE TKDE , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift IEEE TKDE , volume=

Reference 78

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no resolver link, observed 2026-08-01T16:19:07.874575Z

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source=arxiv_source observed=2026-08-01T16:19:07.874575Z digest=sha256:a65dc548f43d18c1fc3e57bce5b92c61d58cbcbaec61e8250f014443d79a93e7

Observation 5ef0d9b1-b178-4b2b-8132-b9f4e04eb2ad · outbound

This paper cites Cell , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Cell , volume=

Reference 79

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no resolver link, observed 2026-08-01T16:19:07.877858Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T16:19:07.877858Z digest=sha256:0c465b1a00576265bff2e800bbb12f57d48090bbfa65ebdbdbab97d75dab4c7a

Observation 6a67db5f-b37f-4143-8550-322d1b0b23bf · outbound

This paper cites Cytometry Part A , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Cytometry Part A , volume=

Reference 80

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source=arxiv_source observed=2026-08-01T16:19:07.881223Z digest=sha256:f1000ad4f15187ffdb4fda1c766f083b9e27bb40c6e288493494158271443dec

Observation d1e1b004-98be-47a3-9026-62c7629df20c · outbound

This paper cites The 2nd diabetic retinopathy – grading and image quality estimation challenge , year =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift The 2nd diabetic retinopathy – grading and image quality estimation challenge , year =

Reference 81

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no resolver link, observed 2026-08-01T16:19:07.884734Z

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source=arxiv_source observed=2026-08-01T16:19:07.884734Z digest=sha256:459b0d221c2cbe46fefdefb6050bb2da49146b582c894b99f1efcf03ba662dab

Observation 3a5a395f-c8e1-4c4d-973b-7861f0472509 · outbound

This paper cites NeurIPS , year=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NeurIPS , year=

Reference 82

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no resolver link, observed 2026-08-01T16:19:07.888567Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:07.888567Z digest=sha256:1bd35ab770167be3c0fc6620fdfae764d48e26e16cb4c1a76e60f51829b11bfa

Observation 7665252b-ebb4-4b5e-8fe5-99f5eea9724e · outbound

This paper cites NeurIPS , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NeurIPS , volume=

Reference 83

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source=arxiv_source observed=2026-08-01T16:19:07.892332Z digest=sha256:42a4476aeed9a846afb8fe84a74b2810019f24a2eace2fbdc69b8d834406fd95

Observation 9654e287-c0df-45d9-9317-0485536b3fdd · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 84

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source=arxiv_source observed=2026-08-01T16:19:07.895984Z digest=sha256:fd3876e938873c2d042f3ad283bd788e2a92a65962e7d79dfe863fcbacd6c6e2

Observation af983d90-54ba-47f9-9dea-5f7ba9e9ff55 · outbound

This paper cites NeurIPS , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift NeurIPS , volume=

Reference 85

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source=arxiv_source observed=2026-08-01T16:19:07.899494Z digest=sha256:91a99c95c65b40af731a61ab0e26ea0fa82238ccd6b7e8f4b2f34f6fb8db716b

Observation ef655ee6-708c-4fdf-a32e-5787687fec44 · outbound

This paper cites IEEE Transactions on Biomedical Engineering , year=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift IEEE Transactions on Biomedical Engineering , year=

Reference 86

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no resolver link, observed 2026-08-01T16:19:07.902007Z

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source=arxiv_source observed=2026-08-01T16:19:07.902007Z digest=sha256:dd794727ec4ef7cd7aa7ecd3bc821dd56a951c71933728485bfd9af711a4f32e

Observation 1ade758c-19f3-4129-95c2-8982c1fb6461 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 87

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no resolver link, observed 2026-08-01T16:19:07.905147Z

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source=arxiv_source observed=2026-08-01T16:19:07.905147Z digest=sha256:56a89a1d686bc8162dd8931aae996cbca0a69583d7b8bacf6963514c7078baac

Observation e6c86891-4127-48a6-8e28-08361ba3c086 · outbound

This paper cites Clinical data sharing using Generative Adversarial Networks , volume =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Clinical data sharing using Generative Adversarial Networks , volume =

Reference 88

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source=arxiv_source observed=2026-08-01T16:19:07.909092Z digest=sha256:a34c7e97a46636a5361352b8b7c1a991a4a3882d5c9c34476804fe10d1f7d03d

Observation 4c813f83-e56c-4701-9fe6-c6196826e714 · outbound

This paper cites CoRR , volume =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift CoRR , volume =

Reference 89

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source=arxiv_source observed=2026-08-01T16:19:07.912114Z digest=sha256:6eb0f11817d98cac50be4793562793644bc79908788afc72ae24b2931bc9a5e4

Observation 3e6b2d03-96cc-46a5-85a7-332aeeb4ff3a · outbound

This paper cites CoRR , volume =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift CoRR , volume =

Reference 90

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source=arxiv_source observed=2026-08-01T16:19:07.915091Z digest=sha256:0f52654d74a60d823f53838dffeb0c72ee58807a83822e292d85c9cd93dc6258

Observation f5a62eca-2ce7-4212-8ebd-ff8fae15f6f1 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 91

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no resolver link, observed 2026-08-01T16:19:07.918293Z

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source=arxiv_source observed=2026-08-01T16:19:07.918293Z digest=sha256:61a4a5614b916766bf74cb639419f17079894fb5c0ec893d4199662807dda2ce

Observation 176af5d2-26ed-41ee-bb6a-0e422fd642df · outbound

This paper cites Diffusion Models:.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Diffusion Models:

Reference 92

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source=arxiv_source observed=2026-08-01T16:19:07.921379Z digest=sha256:5107eecb0784a19ee2d2041fe97e8bb11407486dfec7f5391ad4f0eb08b07503

Observation 75bfdb0f-a8eb-4569-ae39-08bbbc800893 · outbound

This paper cites Denoising Diffusion Probabilistic Models , booktitle =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Denoising Diffusion Probabilistic Models , booktitle =

Reference 93

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source=arxiv_source observed=2026-08-01T16:19:07.924512Z digest=sha256:e785468883ea6c7a0e644136833b1190555c35d054098f1cd11b111434b8484c

Observation ad1ef5f6-ddf0-4d0e-8579-b7dc2ea3169a · outbound

This paper cites Artificial Intelligence Review , year=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Artificial Intelligence Review , year=

Reference 95

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source=arxiv_source observed=2026-08-01T16:19:07.930371Z digest=sha256:1e5a15bb1370214170affbb6574d4ae461616c546e22c5f7e36f9417cf2f7ccf

Observation 0a4b15d8-83d7-415d-9449-a3d77ae5dc79 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence , year=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift IEEE Transactions on Pattern Analysis and Machine Intelligence , year=

Reference 96

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source=arxiv_source observed=2026-08-01T16:19:07.933656Z digest=sha256:9d4d6ba2cbfd5df3b79d741a517bc70988f30d6d6725340c085a2bb98d5cf38f

Observation 3887747d-7871-4977-8acc-50d47b7651e9 · outbound

This paper cites Proceedings of the VLDB Endowment , volume=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Proceedings of the VLDB Endowment , volume=

Reference 97

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source=arxiv_source observed=2026-08-01T16:19:07.937027Z digest=sha256:8794b4ae942286491baa6074713ca0d2ad96bfe52e4a099adab7a501ac2935df

Observation e8ee8205-28f9-4948-8678-c248d0576a8b · outbound

This paper cites International Conference on Machine Learning , pages=.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift International Conference on Machine Learning , pages=

Reference 98

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source=arxiv_source observed=2026-08-01T16:19:07.940084Z digest=sha256:477a06f7255eb4a987120e53daeb5ba8717b5400f9c85b991c2c54a95a9eb2b9

Observation 25a159df-72a8-41f2-85e3-4423130d4252 · outbound

This paper cites Conditional GANs with Auxiliary Discriminative Classifier , booktitle =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Conditional GANs with Auxiliary Discriminative Classifier , booktitle =

Reference 99

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source=arxiv_source observed=2026-08-01T16:19:07.943092Z digest=sha256:b74318469594e68133d657d172da4f3b803562871baea6fdc823aaf2956b9d54

Observation 7a997e91-8cd3-4bd9-b477-c3008d2f1f3e · outbound

This paper cites 2023 , url =.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift 2023 , url =

Reference 100

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source=arxiv_source observed=2026-08-01T16:19:07.946247Z digest=sha256:6c7c3938d135a4f76b0387138f91cf19da56febb8df0f34c180ce612e4a8bcb0

Observation ccc96568-dfa3-4261-99b0-d2c39920fd18 · outbound

This paper cites an unresolved cited work.

SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift Unresolved cited work

Reference 101

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source=arxiv_source observed=2026-08-01T16:19:07.949272Z digest=sha256:f67797c1810515f2e69d9465075f779a8b18a75cecdf797cb942a58cf707b65f

Pith citing papers

No inbound Pith citation observations are available.