Unverified50% confidenceFactExact time
When the attempt budget increases (e.g., pass@10, pass@100), the pass@k curves of stronger interventions such as model scaling or increased inference compute may overtake framework optimization.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/21/2026
First Seen
Valid until: 1/19/2027
Sources
Related Entities
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UnverifiedAs model capabilities improve, too many constraints and prompts waste the context budget and cause prompt drift, and reducing constraints actually works better.69% similarUnverifiedBy comparing the framework's pass@k curves before and after optimization, one can determine whether the performance gain comes from more stable single-attempt success (an overall shift of the curve) or from expanding the boundary of solvable tasks (the curve rising significantly at high k).67% similarUnverifiedComparing the merits of different interventions based on pass@1 alone may be misleading; a comprehensive judgment should combine performance under multiple attempt budgets.67% similarUnverified推理预算越高，模型响应延迟和 Token 消耗成倍增加，但在数学证明、复杂算法设计等场景表现显著提升66% similar
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