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Notes on metacognition
3 notes
Metacognition in LLMs: Foundations, Progress, and Opportunities
This paper provides a comprehensive overview of metacognition in Large Language Models (LLMs), highlighting the importance of this aspect for effective learning, problem solving, and communication. It discusses recent…
Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs
Researchers have developed two new mechanisms - Reinforcement Learning with Metacognitive Feedback (RLMF) and Metacognitive Data Selection - to improve the performance of Language Models (LLMs). The goal is to make…
Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts
The authors present a framework for analyzing dialogue during collaborative problem-solving involving humans, AI, or multiple agents. The framework is designed to address limitations in current analytical approaches…
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