Reasoning. Reasoning, underpinned by evidence and logic, is fundamental to human intellectual
endeavors, serving as the cornerstone for problem-solving, decision-making, and critical analysis
[241; 242; 243]. Deductive, inductive, and abductive are the primary forms of reasoning commonly
recognized in intellectual endeavor [244]. For LLM-based agents, like humans, reasoning capacity is
crucial for solving complex tasks [25].
Differing academic views exist regarding the reasoning capabilities of large language models. Some
argue language models possess reasoning during pre-training or fine-tuning [244], while others
believe it emerges after reaching a certain scale in size [26; 245]. Specifically, the representative
Chain-of-Thought (CoT) method [95; 96] has been demonstrated to elicit the reasoning capacities of
large language models by guiding LLMs to generate rationales before outputting the answer. Some
TheRiseandPotentialofLargeLanguageModel BasedAgents