UNBOX: Unveiling Black-box visual models with Natural-language | ScienceToStartup | ScienceToStartup

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References (42)

[1]

DEXTER: Diffusion-Guided EXplanations with TExtual Reasoning for Vision Models

2025Simone Carnemolla, M. Pennisi et al.

[2]

Error Slice Discovery via Manifold Compactness

2025Han Yu, Jiashuo Liu et al.

[3]

A concept-aware explainability method for convolutional neural networks

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"UNBOX provides a framework for understanding black-box visual models using natural language, enabling auditing and bias detection without requiring internal access."

Explainable AI•Score: 7•View PDF ↗

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UNBOX: Unveiling Black-box visual models with Natural-language

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References (42)

Founder's Pitch

"UNBOX provides a framework for understanding black-box visual models using natural language, enabling auditing and bias detection without requiring internal access."

Commercial Viability Breakdown

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UNBOX: Unveiling Black-box visual models with Natural-language

BUILDER'S SANDBOX

Build This Paper

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Startup Essentials

References (42)

Founder's Pitch

"UNBOX provides a framework for understanding black-box visual models using natural language, enabling auditing and bias detection without requiring internal access."

Commercial Viability Breakdown

Related Papers

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