Just Type It in Isabelle! AI Agents Drafting, Mechanizing, and Generalizing from Human Hints
For researchers using Isabelle, this work offers a formal foundation for type annotations and showcases a novel AI-assisted formalization workflow, though the core problem is incremental.
The paper provides a complete and minimal type annotation specification for rank-one polymorphic λ-calculus terms in Isabelle, formalized in Isabelle/HOL. It demonstrates that an LLM-powered AI agent can autoformalize human and AI-generated pen-and-paper proofs, with human hints refining and generalizing the development.
Type annotations are essential when printing terms in a way that preserves their meaning under reparsing and type inference. We study the problem of complete and minimal type annotations for rank-one polymorphic $λ$-calculus terms, as used in Isabelle. Building on prior work by Smolka, Blanchette et al., we give a metatheoretical account of the problem, with a full formal specification and proofs, and formalize it in Isabelle/HOL. Our development is a series of experiments featuring human-driven and AI-driven formalization workflows: a human and an LLM-powered AI agent independently produce pen-and-paper proofs, and the AI agent autoformalizes both in Isabelle, with further human-hinted AI interventions refining and generalizing the development.