arXiv AI

PolyBridgeBench: Benchmarking Multimodal LLMs for Physics-Grounded Bridge Design

arXiv AI
Aug 18

Large Language Models and their Awareness of Mechanics and Spatial Geometry

arXiv:2608. 14615v1 Announce Type: new Abstract: Large Language Models (LLMs) perform well on established code-generation and mathematical-reasoning benchmarks, but their capabilities in mechanics and spatial geometry, here denoted as mechanical engineering awareness, has not been quantified systematically.

By Johannes Gerstmayr, Sebastian Weyrer, Tobias M\"oltner, Peter Manzl, Michael Pieber
arXiv Computer Vision
Sep 16

MechReason: Benchmarking Multi-Image Multi-Hop Reasoning in Mechanical Engineering

MechReason is a new benchmark for multi-image, multi-hop reasoning in mechanical engineering, featuring 12,000 question-answer pairs with explicit reasoning chains and 21,000 visual items across nine evidence types. It covers eight task types—explanation, prediction, design, and diagnosis—within four reasoning dimensions, and is constructed through a four-stage pipeline that extracts engineering claims, generates verification-masked questions, and validates multimodal quality. Even state‑of‑the‑art models score only 62.89% on this dataset, highlighting its difficulty.

By Tengyue Wang, Kang An, Chenxu Du, Zhongyu Yang, Yuanchi Zhu, Xinqi Yang, Hebao Zhu, Ziliang Wang, FaQiang Qian, Yunli Yang, Qibing Ren
arXiv AI
Jul 17

StructureClaw: Traceable LLM Agents and an Executable Benchmark for Structural Engineering Workflows

arXiv:2607. 14896v1 Announce Type: cross Abstract: Addressing a structural-engineering request requires more than a single answer; it requires a chain of interdependent artifacts: interpreted requirements, a computable model, validation records, solver outputs, code-check records, and a final report.

By Sizhong Qin, Yi Gu, Yao Jiang, Ao Cai, Changjian Zhou, Shaoxuan Shuai, Jiachang Wang, Tianhao Shen, Yueqiang Li, Xinhao Li, Li Zeng, Yueshi Chen, Dachen Gao, Genrong Xu, Wenjie Liao, Xinzheng Lu
arXiv AI
Jun 2

Rethinking Scientific Modeling: Toward Physically Consistent and Simulation-Executable Programmatic Generation

arXiv:2602. 07083v2 Announce Type: replace-cross Abstract: Structural modeling is a fundamental component of computational engineering science, in which even minor physical inconsistencies or specification violations may invalidate downstream simulations.

By Yongqing Jiang, Jianze Wang, Zhiqi Shen, Zhenghong Lin, Jiayuan Wang, Yijian Yang, Kaoshan Dai, Haoran Luo