LLMs generate verifiable MaxSAT encodings from natural language, achieving over 80% acceptance rates on preference tasks where direct LLM reasoning fails.
Mcp-solver: Integrating language models with constraint programming systems
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Reliable Reasoning with Large Language Models via Preference-Based Maximum Satisfiability
LLMs generate verifiable MaxSAT encodings from natural language, achieving over 80% acceptance rates on preference tasks where direct LLM reasoning fails.