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Arxiv
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On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs
- The study investigates biases in post-hoc approaches of concept-based explainable AI (C-XAI) in deep neural networks (DNNs).
- Existing approaches capture background biases, leading to performance degradation in certain scenarios.
- The study validates this on >50 concepts from 2 datasets and 7 DNN architectures.
- Even low-cost setups can provide valuable insights and improved background robustness.
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