Paper

VFEAgent: A Multimodal Agent Framework for End-to-End Automated Finite Element Analysis

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arXiv:2605. 28978v1 Announce Type: new Abstract: Finite Element Analysis (FEA) serves as the cornerstone of modern engineering design.

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Authors: Jiachen Zhang (Peking University, China Agricultural University), Junyi Lao (Peking University), Chenghao Liu (Peking University), Siyuan Liu (Peking University), Shixin Wu (Peking University), Linsen Zhang (Peking University), Boyu Wang (Peking University), Songfang Huang (Peking University)
Released: 2026-05-29 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because VFEAgent: A Multimodal Agent Framework for End-to-End Automated Finite Element Analysis overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, rect, correct, eval, line, rate, language, model. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2605.28978

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