ai.hackcv
论文精选 65arXiv

MindTopo: Can Foundation Models Reason in Topological Space?· MindTopo:大模型能否在拓扑空间中推理?

Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological relations that remain invariant under continuous deformation. Cognitive science identifies these relations as foundational to spatial understanding, yet foundation-model evaluations largely focus on metric or viewpoint-dependent relations. We introduce MindTopo, a benchmark of topological intuition across five properties grounded in cognitive science and formal topology: continuity, separation, order, enclosure, and knots. MindTopo evaluates each property at two cognitive levels. Reasoning asks a model to identify topological relations or infer how they change. Planning instantiates a foundation model as a closed-loop agent whose policy selects environment actions. MindTopo c

AI 解读论文

大模型在拓扑空间中的推理能力评估新基准

核心方法
设计MindTopo基准,包括五个基于认知科学和形式拓扑的属性,通过推理和规划任务评估大模型的拓扑理解能力
适合谁读
研究者
要解决的问题
现有大模型评估方法主要关注度量属性,缺乏对拓扑关系的系统性测试
关键实验
未提供
主要贡献
提出MindTopo评估基准,填补了大模型在拓扑空间推理能力测试上的空白
意义与局限
有助于理解大模型的空间推理能力,推动相关研究,但仅限于特定任务,难以全面衡量模型能力
领域:cs.AI作者:Yunfei Ge、Anbang Liu、Qineng Wang
相关推荐

本站内容由 LLM 精选聚合,原文版权归 arXiv 所有 · 摘录仅供参考