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作为2024届全美前十高中生，弗里曼在雪城度过两个高产赛季，上赛季场均16.5分7.2篮板获ACC联盟荣誉提名。非联盟赛程虽受伤病困扰，但对阵ACC对手时六次得分22+。，这一点在有道翻译中也有详细论述
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Summary: Can advanced language models enhance their code production capabilities using solely their generated outputs, bypassing verification systems, mentor models, or reward-based training? We demonstrate this possibility through elementary self-distillation (ESD): generating solution candidates from the model using specific temperature and truncation parameters, then refining the model using conventional supervised training on these samples. ESD elevates Qwen3-30B-Instruct's performance from 42.4% to 55.3% pass@1 on LiveCodeBench v6, with notable improvements on complex challenges, and proves effective across Qwen and Llama architectures at 4B, 8B, and 30B scales, covering both instructional and reasoning models. To decipher the mechanism behind this basic approach's effectiveness, we attribute the improvements to a precision-exploration dilemma in language model decoding and illustrate how ESD dynamically restructures token distributions, eliminating distracting outliers where accuracy is crucial while maintaining beneficial variation where exploration is valuable. Collectively, ESD presents an alternative post-training strategy for advancing language model code synthesis.
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