I am looking for academic references or frameworks that provide a formal distinction between Large Reasoning Models (LRMs)—like DeepSeek-R1 or the OpenAI o-series—and standard instruction-following LLMs (e.g., GPT-4o, Qwen-2.5). While standard models can generate Chain-of-Thought (CoT) , recent research suggests that "true" reasoning is not just about response length or the presence of thinking tokens, but about the internal cognitive structure...
Originally asked by Humberto José Bortolossi on Stack Exchange (ai) (CC BY-SA 4.0).
