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

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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.

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measured 0 of 1 external citation measurements

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Reference resolution

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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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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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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

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

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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

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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)

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

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

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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

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

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

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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

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

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

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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,

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This paper cites Explaining and Harnessing Adversarial Examples.

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

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

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

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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)

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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)

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

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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)

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

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

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

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

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

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

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

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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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Pith citing papers

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