“我们是否已经遇到了瓶颈?” 什么是测试时计算(Test-time Compute) 增加训练时间计算的昂贵性质导致了对另一个重点的兴趣,即测试时计算。测试时计算允许模式在推理过程中“思考更长时间”, 而不是不断增加预训练的预算。 非推理型模型,通常只输出答案,省略“推理”步骤: 而推理型模型则会使用更多的 tokens,通过...
为了提升推理能力，研究者分成了两大门派：门派一：课后补习班（Post-training）门派二：考场现学现卖（Test-timeCompute）要检验模型的推理能力，需要设计“高难度考题”。论文列举了多类数据集：论文指出了几个关键方向：
回复@andyding: test-time compute对改善大模型的reasoning和准确性有帮助,把人类对AGI的探索又推进一步,但对实时性要求很高的无人驾驶帮助不大:$特斯拉(TSLA)$$比亚迪(SZ002594)$ 近年来,人工智能(AI)领域的巨头们正在意识到,单靠堆砌数据和计算能力已无法再推动模型的快速发展。随着AI扩展定律(scaling laws)的边...
总体而言,《Scaling up Test-Time Compute with Latent Reasoning》通过创新的架构设计和详实的实验,证明了在潜在空间进行递归推理的巨大潜力。它为提升AI模型推理能力开辟了新的途径:不再一味追求庞大模型规模,而是通过“让模型思考更久”来换取性能。在推理计算供给弹性越来越重要的背景下,该工作具有开创性意义和实用...
Our model works by iterating a recurrent block, thereby unrolling to arbitrary depth at test-time. This stands in contrast to mainstream reasoning models that scale up compute by producing more tokens. Unlike approaches based on chain-of-thought, our approach does not require any specialized ...
While current researches continue to explore the benefits of increasing test-time compute by extending the CoT lengths of Large Language Models (LLMs), we are concerned about a potential issue hidden behind the current pursuit of test-time scaling: Would excessively scaling the CoT length actually...
Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning 上传人:leo_wyoming·上传时间:2025-03-07 1/1 相关文档 正在加载文档列表,请稍候...
Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning Abstract Large Language Models (LLMs) have demonstrated remarkable abilities across various language tasks, but solving complex reasoning problems remains a significant challenge. While existing methods, such as Chain-of-Thought (Co...
Additionally, we introduce a dynamic self-correction strategy that enables real-time error correction and learning from past mistakes, as well as consensus-guided decision making strategies to optimize correctness and computational resources. Experimental results demonstrate that the FoT framework, combined ...
Test-time (inference) scaling:same — more labs can now build reasoning models, so we will seemoreinference scaling across the industry and, therefore,moreinference compute utilization. So take heart! DeepSeekdoes not negatethese three scaling laws for datacenter training and inference. ...