Unverified50% confidenceFactExact time
A carefully curated and deduplicated high-quality dataset can train a model of equal or even superior capability using far fewer tokens than the original scale.
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Long-term
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9/11/2026
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Partially VerifiedThe quality of fine-tuning data is far more important than quantity; typically, a few hundred to a few thousand high-quality annotated data samples can significantly improve a model's performance on a specific task.72% similarUnverifiedDuring diffusion model inference, sampler algorithms typically require only 20 to 30 iterations to obtain high-quality image generation results, far fewer than the 1,000 steps used during training.70% similarUnverifiedThe 2023 Microsoft Research paper 'LIMA: Less Is More for Alignment' showed that using only 1,000 carefully curated high-quality samples can enable a base model to exhibit conversational capabilities comparable to fine-tuning on tens of thousands of samples.69% similarUnverified该测试样本规模相对有限（5个模型、13个代码库），结论有待更大规模验证69% similarUnverifiedMoE架构每次推理仅激活少数专家，训练成本相对同等能力稠密模型大幅降低，10B激活1B相比10B稠密模型训练成本低10倍且推理更快69% similar
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