Certified Mechanistic Interpretability: Lifting Single-Input Findings to Bounded Neighbourhoods

arXiv:2609.26112 · cs.LG, cs.AI · Submitted 2026-08-17 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-08-17

Updated: 2026-08-17

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Verification — 54× in this paper · explained in 2 episodes
• Transformer — 52× in this paper · explained in 2 episodes
• Pruning — 39× in this paper · explained in 4 episodes
• Accuracy — 26× in this paper · explained in 1 episode
• Interpretability — 20× in this paper · explained in 15 episodes
• Robustness — 15× in this paper · explained in 5 episodes
• Ablation — 11× in this paper · explained in 1 episode
• Attention Entropy — 8× in this paper · explained in 2 episodes
• Core — 5× in this paper · explained in 2 episodes
• Verifier — 5× in this paper · explained in 2 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Calibration — 4× in this paper · explained in 7 episodes
• In Computer Aided Verification — 3× in this paper
• Activation Function — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Hybrid System — 2× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Adversarial Robustness — 1× in this paper · explained in 3 episodes
• Adversarial Training — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Error Decomposition — 1× in this paper · explained in 3 episodes
• Formal Methods — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• SMT solver — 1× in this paper · explained in 2 episodes

Sources

• On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models
• In-context Learning and Induction Heads
• Data-Driven Nonconvex Reachability Analysis using Exact Set Propagation

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