arXiv：cs.AI· Miao Xie, Xiao Zhang, Yuan Wang, Ruixin Zhu, Chunli Lv·· 6 小时前AI 评分33
ShanLiangRen：面向个性化每日膳食规划的 AI 营养智能体
ShanLiangRen: A Nutrition Agent for Personalized Daily Meal Planning
AI 导读
研究团队提出个性化全量化多目标膳食规划问题（MDP），并开发营养智能体 ShanLiangRen，通过精确 RAG 方法从大规模食材与食谱空间中缩小候选集，再由 LLM 在确定性营养计算与约束校验反馈下按 Pareto 原则迭代优化方案，输出含明确食材与分量的全量化膳食计划及营养合规报告。该系统已以微信小程序形式上线。
正文
Abstract:Dietary nutrition planning plays an important role in chronic disease management and maintaining a healthy body. In applications, it must simultaneously satisfy personalized constraints and reasonable multidimensional nutritional goals. These two aspects often conflict, and user constraints evolve with feedback, resulting in a substantial gap between generic guidelines and executable plans. To bridge this gap, we first propose the personalized fully quantified multiobjective dietary planning problem (MDP). To tackle MDP, we develop a nutrition agent, ShanLiangRen. The system first transforms dietary specifications, nutrient data, user attributes and natural language requirements into an individualized constrained planning instance. It then employs an exact retrieval-augmented generation method to shrink the feasible candidate set from a large scale ingredient and recipe space. Finally, it adopts a refinement guided by Pareto principles, where an LLM iteratively revises candidate plans under deterministic nutrition computation and feedback from constraint verification. The system outputs fully quantified meal plans with explicit ingredients and portion sizes, together with reports on nutrition compliance that show constraint satisfaction and nutrient interval attainment. We have released the system online as a WeChat Program, ShanLiangRen. A demo video is available at this https URL.
| Subjects: | Artificial Intelligence (cs.AI); Information Retrieval (cs.IR) |
| Cite as: | arXiv:2610.07886 [cs.AI] |
| (or arXiv:2610.07886v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.07886 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Xiao Zhang [view email]
[v1]
Tue, 6 Oct 2026 07:32:50 UTC (4,246 KB)
来源：arXiv：cs.AI · arxiv.org