ROM is on arXiv. We frame overthinking in large reasoning models as a latent productive-to-redundant transition that surfaces in hidden states around first-correct-solution (FCS) boundaries, and propose ROM, a model-agnostic streaming framework that monitors a frozen LRM with a lightweight hidden-state detector and intervenes at well-formed reasoning boundaries. Our Counterfactual Self-Correction (CSC) augmentation preserves useful pre-FCS self-correction while labeling only post-FCS continuation as redundant. On Qwen3-8B and DeepSeek-R1-Distill-Qwen-32B across MATH500, GSM8K, AIME25, and MMLU-Pro, ROM improves the accuracy–length tradeoff (e.g., Qwen3-8B: 4262 → 3107 tokens with slightly higher accuracy), stacks with L1 for another ~21% token reduction at zero accuracy loss, and cuts wall-clock latency by 46.5%. Check out our project page, code, and dataset.