Knowing When to Critique: Task-Adaptive Metacognitive Regulation for Reliable LLM Reasoning

Large language models (LLMs) reason fluently but do not regulate their reasoning: they apply uniform scrutiny to every input, which leaves them vulnerable to adversarial and counterfactual prompts, while indiscriminate critique over-corrects answers that were already sound. We propose MetaCrit, a mu