Can Aha Moments Be Fake? Towards Quantifying Decorative and True Thinking in Chain-of-Thought

arXiv:2510.24941v4 Announce Type: replace Abstract: Large language models can generate long chain-of-thought (CoT) reasoning, yet prior work suggests that CoT can be post-hoc rationalization rather than a faithful reflection of the computation through explicitly designed settings. In this work, we go further and propose a True Thinking Score (TTS) to quantify the causal contribution of each step in CoT to the model's final prediction in realistic reasoning problems. Across eleven models ranging from 1.5B to 1.1T parameters on common reasoning benchmarks, we find that CoTs often interleave true

Source: arXiv cs.LG — read the full report at the original publisher.

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