English(EN) Miller-Index-Based Latent Crystallographic Fracture Plane Reasoning and generation with Vision-Language Models

MLLMs在晶面断裂面推理方面展现出潜力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-26 04:00

研究人员探索了使用多模态大语言模型（MLLMs）来理解晶面断裂面。该研究调查了这些模型是否能从视觉数据中推断出代表晶面的Miller指数，并评估了该表示法在断裂图像上的适用性。实验表明，MLLMs可以在理想化场景中可靠地执行这种潜推理，并正确识别出该表示法不适用于各种材料的真实断裂图像。 AI

影响展示了MLLMs在物理感知推理方面的潜力，预示着其在材料科学和失效分析领域的未来应用。

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arXiv cs.LG TIER_1 English(EN) · Qinwu Xu, Xiaofu Ma, Yifan Jiang · 2026-05-26 04:00

基于Miller指数的潜晶界断裂面推理与视觉语言模型生成

arXiv:2605.20416v2 Announce Type: replace Abstract: We study whether multimodal large language models (MLLMs) can leverage crystallographic plane indices (Miller indices) as a structured latent representation for reasoning about fracture geometry. We formulate Miller indices $z =…