Sign inGet started
Paper · arXiv

MAGS: Multi-agent Auto-formalization Guarantees Safety for Agentic Outputs

LLM coding agents now generate complex programs at a scale that makes thorough human review increasingly difficult, raising the risk of safety and security failures. Common approaches, including fuzz testing, static analysis, and LLM-as-a-Verifier, can detect many failures but struggle to cover all possible edge cases. Formal verification addresses this by providing machine-checkable guarantees over specified properties, but traditionally demands substantial manual specification and proof engineering. We introduce a unified multi-agent framework, MAGS, that generates executable programs with formal safety guarantees, using Dafny as a verification-aware intermediate representation where sa...

AuthorsAlbert Wu, Nicholas Roberts, Tzu-Heng Huang et al.
Primary categorycs.AI
Published16 September 2026
Last updated at source16 September 2026
cs.AIcs.CRcs.SE
Embed this entry
<iframe src="https://silytics.si/embed/item/c5721717-0733-4d4d-8339-78b8f2b0abe9" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.