Reliable Reasoning with Large Language Models via Preference-Based Maximum Satisfiability 事件

Reliable Reasoning with Large Language Models via Preference-Based Maximum Satisfiability arXiv:2605.29687v1 Announce Type: new Abstract: Large Language Models (LLMs) excel at understanding natural language but struggle with optimisation tasks involving multiple constraints and user-defined preferences, which commonly arise in domains such as robotics. We propose a hybrid reasoning approach in which LLMs externalise reasoning through code generation. Given a natural language problem description