DeepSolution: Boosting Complex Engineering Solution Design via Tree-based Exploration and Bi-point Thinking

Li Zhuoqun, Haiyang Yu, Xuanang Chen, Hongyu Lin, Yaojie Lu, Fei Huang, Xianpei Han, Yongbin Li, Le Sun

DeepSolution: Boosting Complex Engineering Solution Design via Tree-based Exploration and Bi-point Thinking: 38 upvotes on Hugging Face Daily Papers, #3 of 18 papers on 2025-03-03. Day-by-day upvote history.

Designing solutions for complex engineering challenges is crucial in human production activities. However, previous research in the retrieval-augmented generation (RAG) field has not sufficiently addressed tasks related to the design of complex engineering solutions. To fill this gap, we introduce a new benchmark, SolutionBench, to evaluate a system's ability to generate complete and feasible solutions for engineering problems with multiple complex constraints. To further advance the design of complex engineering solutions, we propose a novel system, SolutionRAG, that leverages the tree-based exploration and bi-point thinking mechanism to generate reliable solutions. Extensive experimental results demonstrate that SolutionRAG achieves state-of-the-art (SOTA) performance on the SolutionBench, highlighting its potential to enhance the automation and reliability of complex engineering solution design in real-world applications.

Paper page on Hugging Face · arXiv

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