arXiv cs.CL· Timo Oksanen, Julius Gun·· 12 小时前AI 评分24
基于 ISO 11783 网络的机器可读操作手册，支持离线多语言 LLM 辅助
Machine-Readable Operator Manuals over the ISO 11783 Network for Offline, Multilingual LLM Assistance
AI 导读
研究在 ISO 11783 CAN 总线上同步农机操作手册，让拖拉机端助手的本地知识库与所连接机具的手册保持一致。完整手册经物理 ISO 11783 网络传输耗时 31 至 89 秒，Markdown 文件最小，多数模型在三种格式下问答表现相当。配合 RAG，本地运行的 7B、8B 模型在英文手册上多数问题答对且不逊于最大模型，但其他五种语言版本表现较差，关键词检索跨语言失效而语义检索有效。
正文 · 原文
Abstract:If agricultural machinery is to support intelligent, offline assistance, then the system must access technical documentation dynamically. In this paper, the Semantic Synchronization of operator manuals over ISO 11783-based CAN buses is analyzed, defined as the process that brings the local knowledge base of a tractor-side assistant into agreement with the operator manual of the connected implement. Data transfer performance was benchmarked using Markdown, JSON, and XML; various open-weight Large Language Models (LLMs) were also evaluated in cross-lingual query tasks. The automatic evaluation of the answers was validated against four human raters. A complete manual was transferred over a physical ISO 11783 network in 31 to 89 s, depending on format and transport settings, which is comparable to the object pool upload that operators already wait for at the first coupling of an implement. Markdown produced the smallest files, while the question-answering performance was comparable across the three formats for most models. With retrieval-augmented generation, locally run models answered most questions on the English manual correctly, with no advantage of the largest model over 7B and 8B models, but performed worse on the five other language editions. Keyword retrieval failed across languages, whereas semantic retrieval provided the cross-lingual capability. The exchange requires only a new parameter group that uses the existing request and transport mechanisms of ISO 11783, which makes it a candidate for standardization. The study is a proof of concept with inference on PC-grade hardware; deployment on embedded agricultural hardware remains future work.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Information Retrieval (cs.IR) |
| Cite as: | arXiv:2610.31863 [cs.CL] |
| (or arXiv:2610.31863v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.31863 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Timo Oksanen [view email]
[v1]
Thu, 22 Oct 2026 19:52:26 UTC (1,730 KB)
来源：arXiv cs.CL · arxiv.org