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English(EN) JigShape: Evaluating Visual-Geometric Reasoning in VLMs through Jigsaw Puzzles

新基准揭示多模态大语言模型在多步空间推理方面存在困难

作者 PulseAugur 编辑部 · [3 个来源] ·

一个名为 LEGO-Puzzles 的新基准已被开发出来，用于评估多模态大语言模型（MLLMs）的多步空间推理能力。研究人员发现，即使是最先进的 MLLMs 在基本空间理解和规划任务上也表现不佳，其表现远逊于人类。随着空间推理所需复杂性和步骤的增加，这些模型的性能会迅速下降，凸显了它们当前能力的重大局限性。 AI

影响 凸显了当前 MLLMs 在空间推理方面的重大局限性，表明需要架构上的进步来处理复杂的多步任务。

排序理由 该集群包含两篇学术论文，介绍了用于评估多模态大语言模型空间推理能力的新基准。

在 Hugging Face Daily Papers 阅读 →

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新基准揭示多模态大语言模型在多步空间推理方面存在困难

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该集群包含两篇学术论文，介绍了用于评估多模态大语言模型空间推理能力的新基准。
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报道来源 [3]

  1. Microsoft Research TIER_1 English(EN) · Yunfei Ge, Anbang Liu, Qineng Wang, Johnalbert Garnica, Zihan Wang, Reuben Tan, Jianfeng Gao, Ruohan Zhang, Yining Hong, Jiajun Wu, Manling Li ·

    MindTopo 揭示 VLMs 的空间推理能力

    <p>A path, a fence, a knot. MindTopo sets a new benchmark for testing how AI understands topological relationships and highlights new opportunities to strengthen spatial reasoning and planning.</p> <p>The post <a href="https://www.microsoft.com/en-us/research/blog/mindtopo-reveal…

  2. arXiv cs.AI TIER_1 English(EN) · Kexian Tang, Junyao Gao, Yanhong Zeng, Haodong Duan, Yanan Sun, Zhening Xing, Wenran Liu, Kai Chen, Kaifeng Lyu ·

    LEGO-Puzzles：MLLM在多步空间推理方面表现如何？

    arXiv:2503.19990v4 Announce Type: replace Abstract: Many real-world applications of spatial intelligence, such as robotic control, autonomous driving, and automated assembly, require spatial reasoning across multiple sequential steps. However, the extent to which current Multimod…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    JigShape：通过拼图评估视觉语言模型（VLMs）中的视觉几何推理能力

    A new jigsaw benchmark with interlocking pieces reveals that vision-language models fail at geometric reasoning and suffer a sharp performance drop as puzzle size increases.

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