Workflow Composition

Workflow composition focuses on automating the design and execution of complex, multi-step processes, primarily using large language models (LLMs) to generate and optimize workflows represented as code or natural language instructions. Current research emphasizes LLM-based approaches, including prompt engineering, retrieval augmented generation (RAG), and reinforcement learning, to create adaptable workflows tailored to specific tasks and data. This field is significant for improving efficiency and scalability in diverse domains, from scientific research and robotic process automation to healthcare and data analysis, by enabling the seamless integration of various tools and models.