视觉语言模型在测试时也能通过缩放计算量提升性能，这篇论文揭示了新的缩放规律。
arXiv:2606.28864v1 Announce Type: new Abstract: Test-time scaling is a paradigm where large models use additional compute at inference to achieve bett…
新方法REVES通过修订与验证增强训练，破解LLM测试时缩放与多步推理的错位难题。
arXiv:2606.18910v1 Announce Type: new Abstract: Test-time scaling via sequential revision has emerged as a powerful paradigm for enhancing Large Langu…
自适应世界模型如何在视觉空间推理中决定何时想象、想象多少？这项研究提出测试时动态缩放策略，让AI智能分配计算资源，提升效率与准确性。
arXiv:2602.08236v2 Announce Type: replace-cross Abstract: Despite rapid progress in MLLMs, visual spatial reasoning remains unreliable when correct an…
让大模型自主决定测试时计算如何分配，突破固定预算与策略的局限。
arXiv:2606.01667v1 Announce Type: new Abstract: Test-time scaling has become a major way to improve large language model reasoning, but its orchestrat…