标题为英语Which Tokens Should SFT Actually Learn? A Token-Trimming Perspective on Mathematical Reasoning
arXiv:2609.09707v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) applies a uniform cross-entropy loss to all target tokens, even though different tokens provide unequal learning signals for mathematical reasoning. This uniform treatment can over-sharpen already…
AI 摘要：要点
- arXiv:2609.09707v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) applies a uniform cross-entropy loss to all target tokens, even though different tokens provide unequal learning signals for mathematical reasoning
- This uniform treatment can over-sharpen already…
Which Tokens Should SFT Actually Learn? A Token-Trimming Perspective on Mathematical Reasoning
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