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Demystifying Long Chain-of-Thought Reasoning in LLMs by Edward Yeo, Yuxuan Tong, Morry Niu, Graham Neubig, Xiang Yue is a book available to read on EtoBox.

What is Demystifying Long Chain-of-Thought Reasoning in LLMs about?

demonstrated remarkable reasoning abilities in domains likearXiv:2502.03373v1 [cs.CL] 5 Feb 2025Scaling inference compute enhances reasoning inmathematics (Cobbe et al., 2021) and programming (Chenet al., 2021). A key technique for enabling reasoning abillarge language models (LLMs), with long chainsities in LLMs is chain-of-thought (CoT) prompting (Weiof-thought (CoTs) enabling strategies like backet al., 2022), which guides models to generate intermediatetracking and error correction. Reinforcementreasoning steps before arriving at a final answer.learning (RL) has emerged as a crucial method forDespite these advancements, LLMs still struggle with highlydeveloping these capabilities, yet the conditionscomplex reasoning tasks, such as mathematical competiunder which long CoTs emerge remain unclear,tions (Hendrycks et al., 2021), PhD-level scientific QAand RL training requires careful design choices.(Rein et al., 2024), and software engineering (Jimenez et al.,In this study, we systematically investigate the2024), even with CoT. Recently, OpenAI’s o1 models (Opemechanics of long CoT reasoning, identifyingnAI, 2024) have demonstrated significant breakthroughs inthe key factors t

Author

Edward Yeo, Yuxuan Tong, Morry Niu, Graham Neubig, Xiang Yue

Published

2025

Language

EN