DeepSolution: Boosting Complex Engineering Solution Design via
  Tree-based Exploration and Bi-point Thinking
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.
67c514aba3d873e41624a082
Zhuoqun Li
claimed_verified
2025-03-03T08:07:26.218Z
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Li Zhuoqun
user
lzq2021
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Haiyang Yu
claimed_verified
2025-03-03T09:31:12.493Z
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Haiyang Yu
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yhycai
67c514aba3d873e41624a084
Xuanang Chen
admin_assigned
2025-03-03T09:29:31.384Z
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Xuanang Chen
user
xuanang
67c514aba3d873e41624a085
Hongyu Lin
admin_assigned
2025-03-03T09:28:09.791Z
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Hongyu  Lin
user
sanmusunrise
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Yaojie Lu
admin_assigned
2025-03-03T09:29:38.957Z
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Yaojie Lu
user
luyaojie
67c514aba3d873e41624a087
Fei Huang
67c514aba3d873e41624a088
Xianpei Han
admin_assigned
2025-03-03T09:29:51.007Z
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Xianpei Han
user
xphan
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Yongbin Li
admin_assigned
2025-03-03T09:29:57.561Z
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Yongbin Li
user
Yongbin-Li
67c514aba3d873e41624a08a
Le Sun
DeepSolution: Boosting Complex Engineering Solution Design via
  Tree-based Exploration and Bi-point Thinking
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.
SolutionRAG leverages tree-based exploration and bi-point thinking to achieve state-of-the-art performance on SolutionBench, a benchmark for generating complete and feasible engineering solutions.
retrieval-augmented generation RAG SolutionBench SolutionRAG tree-based exploration bi-point thinking