Can Aha Moments Be Fake? Identifying True and Decorative Thinking Steps in Chain-of-Thought

ArXi:2510.24941v3 Announce Type: replace Large language models can generate long chain-of-thought (CoT) reasoning, but it remains unclear whether the verbalized steps reflect the models' internal thinking. In this work, we propose a True Thinking Score (TTS) to quantify the causal contribution of each step in CoT to the model's final prediction. Our experiments show that LLMs often interleave between true-thinking steps (which are genuinely used to compute the final output) and decorative-thinking steps (which give the appearance of reasoning but have minimal causal influence.