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Articles

[2507.02169] Statistical Inference for Responsiveness Verification

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By Seung Dam Hyun, Meredith Stewart, Bogdan Kulynych, Tsui-Wei Weng
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (484) Issue with article?

VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance

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By Ge Yan, Tsui-Wei Weng
| arxiv.org
[Submitted on 18 Jul 2024 ( v1 ), last revised 16 Jan 2025 (this version, v3)] Title:VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance View a PDF of the paper titled VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance, by Divyansh Srivastava and 2 other authors View PDF HTML (experimental) Abstract:Concept Bottleneck Models (CBMs) provide interpretable prediction by introducing an intermediate Concept Bottleneck Layer (CBL), which encodes...
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Prediction without Preclusion: Recourse Verification with Reachable Sets

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By Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (634) Issue with article?
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