Metacognitive Behavioral Tuning of Large Language Models for Multi-Hop Question Answering
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Updated
May 13, 2026 - Shell
Metacognitive Behavioral Tuning of Large Language Models for Multi-Hop Question Answering
Cognition layer for autonomous agents — modular OSS packages for active-inference reasoning, thoughtseed competition, computational phenomenology, and workspace dynamics. Each adopts alone. Companion to elume (memory layer).
Universal metacognition instructions for OpenClaw bots - enables self-analysis and self-improvement
Metacognitive Behavioral Tuning of Large Language Models for Multi-Hop Question Answering
🤖 Enhance OpenClaw bots with this template for self-analysis, improvement, and adaptive learning, fostering smarter, more responsive interactions.
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