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西
西娅
西娅：最近DeepSeek R1大火，我发现AI的推理能力虽然增强了，但是对于提示词的遵循能力却变差了。我在写DeepSeek攻略的时候就深有体会。一篇论文指出，使用KeyAlt推理后，大多数模型的执行准确率反而下降，原因是模型对于任务关键限制的注意力降低了。论文还提出了四种提升指令遵循效果的方案，其中Classifier Selected Reasoning最有效，但是成本也比较高。我认为，真正强大的智能应该懂得聚焦，有思考的分寸感。
Deep Dive
The DeepSeek R1 model showed improved AI reasoning but suffered from decreased instruction-following accuracy. A Harvard, Amazon, and NYU study explored this trade-off, identifying a decline in attention to crucial task constraints after using key-word reasoning. Solutions for improving instruction-following were proposed, emphasizing the importance of focused, mindful intelligence.
- Improved AI reasoning capabilities of DeepSeek R1 came at the cost of reduced instruction-following accuracy.
- Study found that post key-word reasoning, the model's attention to crucial task constraints decreased.
- Four solutions proposed to improve instruction-following, with Classifier Selected Reasoning being the most effective but costly.
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