Verifying the Linear Representation Hypothesis: How Interpretable Are Vision SAEs?
cs.CV
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/KempnerInstitute/overcomplete
Terminology
Sources
- Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions
- On the Robustness of Interpretability Methods
- Do Sparse Autoencoders Capture Concept Manifolds?
- Concept-SAE: A Controllable and Invertible Concept Interface for Sparse Autoencoders
- Toy Models of Superposition
- Causal Interpretation of Sparse Autoencoder Features in Vision
- Natural Language Descriptions of Deep Visual Features
- On the Robustness of Explanations of Deep Neural Network Models: A Survey
- Evaluating Adversarial Robustness of Concept Representations in Sparse Autoencoders
- GPT-4 Technical Report
- Interpretable and Testable Vision Features via Sparse Autoencoders
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