Real World Office Workflow
Real-world office workflow research focuses on automating and optimizing complex tasks through AI-powered systems, aiming to improve efficiency and productivity. Current research emphasizes the development of adaptable workflows using large language models (LLMs) and other machine learning techniques, often incorporating prompt engineering and workflow orchestration to handle diverse tasks and data types. This work is significant because it addresses the limitations of traditional, monolithic AI approaches by creating more flexible and robust solutions for various applications, ranging from medical diagnosis to business process management. The resulting improvements in efficiency and accuracy have the potential to significantly impact both scientific research and practical applications across numerous industries.
Papers
ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation
Rinon Gal, Adi Haviv, Yuval Alaluf, Amit H. Bermano, Daniel Cohen-Or, Gal Chechik
A versatile machine learning workflow for high-throughput analysis of supported metal catalyst particles
Arda Genc, Justin Marlowe, Anika Jalil, Libor Kovarik, Phillip Christopher