arXiv:2509.22315v3 Announce Type: replace-cross 
Abstract: Inspired by the dual-process theory of human cognition from \textit{Thinking, Fast and Slow}, we introduce \textbf{PRIME} (Planning and Retrieval-Integrated Memory for Enhanced Reasoning), a multi-agent reasoning framework that dynamically integrates \textbf{System 1} (fast, intuitive thinking) and \textbf{System 2} (slow, deliberate thinking). PRIME first employs a Quick Thinking Agent (System 1) to generate a rapid answer; if uncertainty is detected, it then triggers a structured System 2 reasoning pipeline composed of specialized agents for \textit{planning}, \textit{hypothesis generation}, \textit{retrieval}, \textit{information integration}, and \textit{decision-making}. This multi-agent design faithfully mimics human cognitive processes and enhances both efficiency and accuracy. Experimental results with LLaMA 3 models demonstrate that PRIME enables open-source LLMs to perform competitively with state-of-the-art closed-source models like GPT-4 and GPT-4o on benchmarks requiring multi-hop and knowledge-grounded reasoning. This research establishes PRIME as a scalable solution for improving LLMs in domains requiring complex, knowledge-intensive reasoning.

إطار PRIME، الذي تم تقديمه في دراسة حديثة، يدمج العمليات المعرفية السريعة والبطيئة لتحسين التفكير في الذكاء الاصطناعي. من خلال استخدام نظام متعدد الوكلاء الذي يحاكي عمليات التفكير البشرية، يسمح PRIME لنماذج المصدر المفتوح مثل LLaMA 3 بالتنافس مع نماذج متقدمة مثل GPT-4. هذا التطور مهم لأنه يحسن من كفاءة ودقة الذكاء الاصطناعي في المهام المعقدة.

El marco PRIME, presentado en un estudio reciente, integra procesos cognitivos rápidos y lentos para mejorar el razonamiento en IA. Al emplear un sistema multiagente que imita los procesos de pensamiento humano, PRIME permite que modelos de código abierto como LLaMA 3 compitan con modelos avanzados como GPT-4. Este desarrollo es significativo ya que mejora la eficiencia y precisión de la IA en tareas complejas de razonamiento.

Le cadre PRIME, introduit dans une étude récente, intègre des processus cognitifs rapides et lents pour améliorer le raisonnement en IA. En utilisant un système multi-agents qui imite les processus de pensée humaine, PRIME permet à des modèles open-source comme LLaMA 3 de rivaliser avec des modèles avancés tels que GPT-4. Ce développement est significatif car il améliore l'efficacité et la précision de l'IA dans des tâches de raisonnement complexes.

The PRIME framework, introduced in a recent study, integrates fast and slow cognitive processes to enhance reasoning in AI. By employing a multi-agent system that mimics human thought processes, PRIME allows open-source models like LLaMA 3 to compete with advanced models such as GPT-4. This development is significant as it improves the efficiency and accuracy of AI in complex reasoning tasks.

PRIME: Planning and Retrieval-Integrated Memory for Enhanced Reasoning

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PRIME: Planning and Retrieval-Integrated Memory for Enhanced Reasoning

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