VFR-LLM combines small LLMs with symbolic verification and solving to reach 0.983 and 0.933 accuracy on precedence and logical deduction tasks using one model call versus lower results from self-consistency baselines.
State of the art and future directions of small language models: A systematic review.Big Data and Cognitive Computing, 9(7):189, 2025
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Resource-Aware Neuro-Symbolic Reasoning for Local Small Language Models
VFR-LLM combines small LLMs with symbolic verification and solving to reach 0.983 and 0.933 accuracy on precedence and logical deduction tasks using one model call versus lower results from self-consistency baselines.