✨SCALE: Selective Resource Allocation for Overcoming Performance Bottlenecks in Mathematical Test-time Scaling

📝 Summary:
SCALE improves LLM math reasoning by selectively allocating resources based on sub-problem difficulty. It addresses uniform allocation bottlenecks, boosting accuracy up to 13.75% and cutting costs by 33-53% compared to uniform scaling.

🔹 Publication Date: Published on Nov 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.00466
• PDF: https://arxiv.org/pdf/2512.00466
• Github: https://github.com/XiaoYang66/DualThinking

✨ Datasets citing this paper:
• https://huggingface.co/datasets/YangXiao-nlp/DualThinking

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#LLM #AI #MachineLearning #PerformanceOptimization #MathReasoning