Large language models face a fundamental computational limit that causes undetected errors in complex tasks. Hybrid AI systems combining models with verification tools offer a practical solution.
Download PDF Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal ...
Abstract: This study investigates the structural characterization of the Middle Roman Domination Number for any caterpillar graph; a significant subclass of trees derived from a central spine by ...
Thinking Machines, the AI startup founded earlier this year by former OpenAI CTO Mira Murati, has launched its first product: Tinker, a Python-based API designed to make large language model (LLM) ...
Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...
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Abstract: Theorem proving demonstrates promising potential for verifying problems beyond the capabilities of SMT-solver-based verification tools. We explore and showcase the capability of Lean, an ...
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