CeProAgents: A Hierarchical Agents System for Automated Chemical Process Development
On the map: LLM agents and tool use → Medical and scientific domain agents
Abstract (arXiv)
The development of chemical processes, a cornerstone of chemical engineering, presents formidable challenges due to its multi-faceted nature, integrating specialized knowledge, conceptual design, and parametric simulation. Capitalizing on this, we propose CeProAgents, a hierarchical multi-agent system designed to automate the development of chemical process through collaborative division of labor. Our architecture comprises three specialized agent cohorts focused on knowledge, concept, and parameter respectively. To effectively adapt to the inherent complexity of chemical tasks, each cohort employs a novel hybrid architecture that integrates dynamic agent chatgroups with structured agentic workflows. To rigorously evaluate the system, we establish CeProBench, a multi-dimensional benchmark structured around three core pillars of chemical engineering. We design six distinct types of tasks across these dimensions to holistically assess the comprehensive capabilities of the system in chemical process development. The results not only confirm the effectiveness and superiority of our proposed approach but also reveal the transformative potential as well as the current boundaries of Large Language Models (LLMs) for industrial chemical engineering.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 15 of its 51 references that are in the map. First posted on arXiv 2 Mar 2026.
Builds on
15 of 51 references.
Closest ancestors · 3
Same direction, newest first
- 2025Multi-agent systems for chemical engineering: A review and perspective11 Aug
- 2025LLM-guided Chemical Process Optimization with a Multi-Agent Approach26 Jun
- 2024Accelerating Manufacturing Scale-Up from Material Discovery Using Agentic Web Navigation and Retrieval-Augmented AI for Process Engineering Schematics Design8 Dec
Other references · 12
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- 2024What Large Language Models Know and What People Think They Knowcited by 110
- 2025SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integrationcited by 43
- 2024An Agentic Approach to Automatic Creation of P&ID Diagrams from Natural Language Descriptionscited by 12
- 2024A multi-modal vision-language model for generalizable annotation-free pathology localizationcited by 7
Built on by
Citing papers per year: 2026: 2.
2 papers.
Similar, not cited
Close in wording, no citation either way
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