MetaGPT Introduces "Atom of Thoughts": Can Atomic Thinking Boost 4o-mini Over Reasoning Models?
Discover AoT: Revolutionizing reasoning with atomic thinking, reducing computational dependency, and enhancing efficiency in AI models. Open-source and framework-compatible.
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From "Long-chain Reasoning" to "Atomic Thinking": The Birth of AoT
Large Language Models (LLMs) have achieved significant performance improvements in recent years through train-time scaling.
However, as bottlenecks in model size and data volume become apparent, test-time scaling has emerged as a new direction to further unlock potential.
Yet, whether it's prompt strategies and reasoning frameworks like Chain of Thought (CoT) and Tree of Thought (ToT), or reasoning models such as OpenAI's o1/o3 and DeepSeek-R1, they all excessively rely on complete historical information during inference, leading to wasted computational resources and interference from redundant information that hampers effective reasoning.