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cs.AI2026
Seeing Through Circuits: Faithful Mechanistic Interpretability for Vision Transformers
Nina Żukowska, Wolfgang Stammer, Bernt Schiele +1
Transparency of neural networks' internal reasoning is at the heart of interpretability research, adding to trust, safety, and understanding of these models. The field of mechanist…
cs.AI2026
Certified Circuits: Stability Guarantees for Mechanistic Circuits
Alaa Anani, Tobias Lorenz, Bernt Schiele +2
Understanding how neural networks arrive at their predictions is essential for debugging, auditing, and deployment. Mechanistic interpretability pursues this goal by identifying ci…