According to God of Prompt on Twitter, a new paper from Beihang University and ByteDance finds that overthinking in reasoning models like DeepSeek R1 and Qwen3 stems from sampling, not training, and a stopping-aware decoding method reduces token usage by 44% while improving accuracy; as reported by the tweet, this implies businesses can lower inference costs and latency without retraining by adapting sampling to let models stop when confident.