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.
Large language models (LLMs): survey, technical frameworks, and future challenges
2 Pith papers cite this work. Polarity classification is still indexing.
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Teaching resists meaningful automation by AI due to its reliance on contextual human judgment, relational elements, and aspects of cognition that cannot be fully specified or modeled.
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Why teaching resists automation in an AI-inundated era: Human judgment, non-modular work, and the limits of delegation
Teaching resists meaningful automation by AI due to its reliance on contextual human judgment, relational elements, and aspects of cognition that cannot be fully specified or modeled.