English(EN) Parse Before You Execute: Efficient Spatial Reasoning with Executable Primitives

新的 PEPS 范式提高了 VLMs 的空间推理能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员引入了 PEPS，这是一种新颖的代理范式，旨在增强视觉语言模型 (VLMs) 的空间推理能力。PEPS 遵循先解析后执行的原则，在任何计算发生之前，将每个查询提交给一组精确的可执行要求。这种方法旨在减少不必要的工具获取和迭代优化，从而实现更可靠、更高效的空间推理。 AI

影响这项研究可能带来更高效、更可靠的 AI 系统空间推理能力。

排序理由这是一篇详细介绍 VLM 空间推理新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Xiwei Liu, Yulong Li, Xinling Zhuang, Xuhui Li, Yichen Li, Haolin Yang, Zhixiang Lu, Yutong Xie · 2026-11-02 05:00

Parse Before You Execute: Efficient Spatial Reasoning with Executable Primitives

arXiv:2610.41389v1 Announce Type: new Abstract: Spatial reasoning in Vision-Language Models (VLMs) has increasingly benefited from tool-integrated pipelines that ground computation in explicit geometry. However, existing systems often compile queries into relatively open-ended ar…