A new research paper proposes "Recursive Capability Composition" to enhance the coordination and management of complex LLM-based agentic applications. The approach combines Business Process Model and Notation (BPMN) with agents and enterprise knowledge, transforming explicit BPMN models into executable workflows. This method aims to make multi-agent systems more understandable and manageable by providing developers with a shared view of workflow structures and execution progress, while also integrating organization-specific context through process models and knowledge graphs. AI
IMPACT Enhances manageability and understandability of complex LLM agent systems, potentially improving enterprise adoption.
RANK_REASON The cluster contains a research paper detailing a new methodology for agentic workflows.
Read on arXiv cs.MA (Multiagent) →
- Agentic Workflows
- alphaXiv
- arXiv
- Business Process Model and Notation
- CatalyzeX
- DagsHub
- Gotit.pub
- Hugging Face
- knowledge graph
- langgraph
- ontology
- Pregel
- Recursive Capability Composition
- ScienceCast
- SemTalk
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