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[2602.23248] Mitigating Legibility Tax with Decoupled Prover-Verifier Games
Summary
This paper presents a novel approach to mitigate the 'legibility tax' in large language models by decoupling the prover-verifier game, allowing for improved checkability of model outputs without sacrificing accuracy.
Why It Matters
As AI models grow more complex, ensuring their outputs are understandable and verifiable becomes crucial. This research addresses a significant challenge in AI transparency and reliability, potentially enhancing the usability of AI systems in various applications.
Key Takeaways
- Introduces the concept of 'legibility tax' affecting AI output checkability.
- Proposes a decoupled prover-verifier game to enhance model output verification.
- Suggests training a translator model to maintain accuracy while ensuring checkability.
- Addresses the balance between correctness and checkability in AI systems.
- Highlights the importance of transparency in AI for broader adoption and trust.
Computer Science > Artificial Intelligence arXiv:2602.23248 (cs) [Submitted on 26 Feb 2026] Title:Mitigating Legibility Tax with Decoupled Prover-Verifier Games Authors:Yegon Kim, Juho Lee View a PDF of the paper titled Mitigating Legibility Tax with Decoupled Prover-Verifier Games, by Yegon Kim and 1 other authors View PDF HTML (experimental) Abstract:As large language models become increasingly capable, it is critical that their outputs can be easily checked by less capable systems. Prover-verifier games can be used to improve checkability of model outputs, but display a degradation in accuracy compared to a baseline trained only to maximize correctness -- a phenonemon named legibility tax. We propose a solution by decoupling the correctness from the checkability condition and instead training a "translator" model that turns a fixed solver model's solution into a checkable form. This allows us to first train the solver to maximize correctness, and then train the translator to translate the solver into a checkable form while retaining the solver's answer. To accommodate this new objective of translation, we formulate a decoupled prover-verifier game where the equilibria correspond to faithful and checkable translators. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2602.23248 [cs.AI] (or arXiv:2602.23248v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2602.23248 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Yegon Kim [...