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Paper Citation Record · LEDGER

On the Domain Robustness of Contrastive Vision-Language Models

As of 9 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.23663.

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

pith.paper-citation-record.v1
2506.23663 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:41:38.324060Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

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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

44 of 44 outbound references displayed

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External citation measurements

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Outbound references

Observation 2d4118b1-375b-410d-ac89-ac2bc42775af · outbound

This paper cites Data in brief28, 104863 (2020).

On the Domain Robustness of Contrastive Vision-Language Models Data in brief28, 104863 (2020)

Reference 1

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Observation 87f44c36-a1d4-4292-b2fc-ba34d1fc414e · outbound

This paper cites In: International conference on software engineering advances (ICSEA).

On the Domain Robustness of Contrastive Vision-Language Models In: International conference on software engineering advances (ICSEA)

Reference 2

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This paper cites In: 2017 International conference of electronics, communication and aerospace tech- nology (ICECA).

On the Domain Robustness of Contrastive Vision-Language Models In: 2017 International conference of electronics, communication and aerospace tech- nology (ICECA)

Reference 3

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Observation 37bec92c-2abe-40a0-8346-cf3bff3f6428 · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

On the Domain Robustness of Contrastive Vision-Language Models In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 4

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Observation 6f312a3b-483c-4526-a10e-eeb556606138 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

On the Domain Robustness of Contrastive Vision-Language Models On the Opportunities and Risks of Foundation Models

Reference 5

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This paper cites In: Computer vision–ECCV 2014: 13th European conference, zurich, Switzerland, September 6-12, 2014, proceedings, part VI 13.

On the Domain Robustness of Contrastive Vision-Language Models In: Computer vision–ECCV 2014: 13th European conference, zurich, Switzerland, September 6-12, 2014, proceedings, part VI 13

Reference 6

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This paper cites Ad- vances in neural information processing systems13 (2000).

On the Domain Robustness of Contrastive Vision-Language Models Ad- vances in neural information processing systems13 (2000)

Reference 7

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Observation c0d6a6c6-8ca8-47ac-98d9-7613e05a0a2f · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition.

On the Domain Robustness of Contrastive Vision-Language Models In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition

Reference 8

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Observation 9f089809-40f0-4e8d-a037-6d1656a8b0f7 · outbound

This paper cites RobustBench: a standardized adversarial robustness benchmark.

On the Domain Robustness of Contrastive Vision-Language Models RobustBench: a standardized adversarial robustness benchmark

Reference 9

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This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

On the Domain Robustness of Contrastive Vision-Language Models In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 10

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Observation 54c04d2a-6da6-47d4-b5b1-710d8afd6e90 · outbound

This paper cites Under review2(1) (2019).

On the Domain Robustness of Contrastive Vision-Language Models Under review2(1) (2019)

Reference 11

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Observation 633bf66b-97e1-4f53-b499-d3c7e05b4d54 · outbound

This paper cites In: International Conference on Machine Learning.

On the Domain Robustness of Contrastive Vision-Language Models In: International Conference on Machine Learning

Reference 12

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On the Domain Robustness of Contrastive Vision-Language Models In: International Confer- ence on Machine Learning

Reference 13

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This paper cites In: 2012 IEEE conference on computer vision and pattern recognition.

On the Domain Robustness of Contrastive Vision-Language Models In: 2012 IEEE conference on computer vision and pattern recognition

Reference 14

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This paper cites In: Neural information pro- cessing: 20th international conference, ICONIP 2013, daegu, korea, november 3-7,.

On the Domain Robustness of Contrastive Vision-Language Models In: Neural information pro- cessing: 20th international conference, ICONIP 2013, daegu, korea, november 3-7,

Reference 15

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Observation 6720d15a-7d1e-4789-9658-16b68fa1ef33 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

On the Domain Robustness of Contrastive Vision-Language Models Explaining and Harnessing Adversarial Examples

Reference 16

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Observation 3d7883b4-7b58-4224-ae69-2173f42059a6 · outbound

This paper cites Radiology290(2), 498–503 (2019).

On the Domain Robustness of Contrastive Vision-Language Models Radiology290(2), 498–503 (2019)

Reference 17

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Observation ce78ea6e-e2fe-48ee-a477-ce4be0786b07 · outbound

This paper cites Machine Learning 114(3), 1–19 (2025).

On the Domain Robustness of Contrastive Vision-Language Models Machine Learning 114(3), 1–19 (2025)

Reference 18

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Observation de7776b3-7736-4987-bb12-4d9d1758b475 · outbound

This paper cites Proceedings of the International Conference on Learning Representations (2019).

On the Domain Robustness of Contrastive Vision-Language Models Proceedings of the International Conference on Learning Representations (2019)

Reference 19

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On the Domain Robustness of Contrastive Vision-Language Models In: International Conference on Machine Learning

Reference 20

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This paper cites IEEE Access11, 9920–9930 (2023).

On the Domain Robustness of Contrastive Vision-Language Models IEEE Access11, 9920–9930 (2023)

Reference 21

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On the Domain Robustness of Contrastive Vision-Language Models In: European Conference on Computer Vision

Reference 22

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This paper cites In: International conference on machine learning.

On the Domain Robustness of Contrastive Vision-Language Models In: International conference on machine learning

Reference 23

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This paper cites Scientific data4(1), 1–9 (2017).

On the Domain Robustness of Contrastive Vision-Language Models Scientific data4(1), 1–9 (2017)

Reference 24

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Observation d329c1aa-ab8b-45de-817c-6cf866bca35c · outbound

This paper cites In: 2022 International Joint Conference on Neural Networks (IJCNN).

On the Domain Robustness of Contrastive Vision-Language Models In: 2022 International Joint Conference on Neural Networks (IJCNN)

Reference 25

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This paper cites Advances in neural information processing systems32 (2019).

On the Domain Robustness of Contrastive Vision-Language Models Advances in neural information processing systems32 (2019)

Reference 26

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On the Domain Robustness of Contrastive Vision-Language Models In: International Conference on Learning Representations (2018)

Reference 27

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This paper cites $\texttt{BATCLIP}$: Bimodal Online Test-Time Adaptation for CLIP.

On the Domain Robustness of Contrastive Vision-Language Models $\texttt{BATCLIP}$: Bimodal Online Test-Time Adaptation for CLIP

Reference 28

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On the Domain Robustness of Contrastive Vision-Language Models https://openai.com/research/gpt-4 (2023), ac- cessed: 2025-01-09

Reference 29

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On the Domain Robustness of Contrastive Vision-Language Models In: International Conference on Machine Learning

Reference 30

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This paper cites International Journal of Computational Intelligence Systems17(1), 241 (2024) 24 Koddenbrock et al.

On the Domain Robustness of Contrastive Vision-Language Models International Journal of Computational Intelligence Systems17(1), 241 (2024) 24 Koddenbrock et al

Reference 31

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This paper cites Advances in Neural Information Processing Systems (NeurIPS)33, 18583–18599 (2020).

On the Domain Robustness of Contrastive Vision-Language Models Advances in Neural Information Processing Systems (NeurIPS)33, 18583–18599 (2020)

Reference 32

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This paper cites Springer Science & Business Media (1999).

On the Domain Robustness of Contrastive Vision-Language Models Springer Science & Business Media (1999)

Reference 33

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This paper cites IEEE transactions on neural networks 10(5), 988–999 (1999).

On the Domain Robustness of Contrastive Vision-Language Models IEEE transactions on neural networks 10(5), 988–999 (1999)

Reference 34

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This paper cites Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis.

On the Domain Robustness of Contrastive Vision-Language Models Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 741c2cf4-4ecb-47e0-a396-e4489f7732f9 · outbound

This paper cites A Sober Look at the Robustness of CLIPs to Spurious Features.

On the Domain Robustness of Contrastive Vision-Language Models A Sober Look at the Robustness of CLIPs to Spurious Features

Reference 36

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b2987965-cb58-4585-8a5b-04e4e6f95e52 · outbound

This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

On the Domain Robustness of Contrastive Vision-Language Models In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T21:41:37.823521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 384a7f47-059e-468e-9a2d-88bf310731bf · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

On the Domain Robustness of Contrastive Vision-Language Models HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T21:41:37.882901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:41:37.882901Z digest=sha256:b8a32777a0bbafc00e8971d6ec844c89938fb5d589d56a398b8b858f2c01394a

Observation 1cedf07e-899a-433c-b345-a28393c2abb2 · outbound

This paper cites IEEE Transactions on Geoscience and Remote Sensing55(7), 3965–3981 (2017).

On the Domain Robustness of Contrastive Vision-Language Models IEEE Transactions on Geoscience and Remote Sensing55(7), 3965–3981 (2017)

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T21:41:37.948432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:41:37.948432Z digest=sha256:09572c98907d34901ed93ec8ff0e2beb843e5aa44767870b02abb02342d67ac5

Observation ab6a159b-fc4a-40f0-85a8-16ce1812f0e8 · outbound

This paper cites In: 12th Interna- tional Conference on Learning Representations, ICLR 2024 (2024).

On the Domain Robustness of Contrastive Vision-Language Models In: 12th Interna- tional Conference on Learning Representations, ICLR 2024 (2024)

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:41:39.192995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:41:38.035366Z digest=sha256:b77a076c682190ac0809a14aeede418265a1efaa402ed4d4271a165eaf57180f

Observation c2f9d3e4-18db-421e-b918-a69c2c29f607 · outbound

This paper cites Advances in Neural Information Processing Systems 32 (2019).

On the Domain Robustness of Contrastive Vision-Language Models Advances in Neural Information Processing Systems 32 (2019)

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:41:38.931167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:41:38.108789Z digest=sha256:f46517067e0144cd4c6299164c2233173bcc415a79a889abf4220facac454ff9

Observation c99048cd-fb8b-4f2b-9609-e2b3c8f83e8c · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

On the Domain Robustness of Contrastive Vision-Language Models In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T21:41:38.219068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 04bfb4ec-5eb0-4b44-9d58-6fbd2f04368a · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

On the Domain Robustness of Contrastive Vision-Language Models In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:41:38.778436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:41:38.324060Z digest=sha256:ab9143cb933748343b86d79d5640713c1686c6cbfa7a3adfa931e862c060b7e2

Observation 73e154fe-c58e-47b4-91d3-e3df0dc06bf1 · outbound

This paper cites an unresolved cited work.

On the Domain Robustness of Contrastive Vision-Language Models Unresolved cited work

Reference 2013

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:41:41.900046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.