2022/10/26 by Yara Rizk, Praveen Venkateswaran, Rizk, Yara +5 · 1 citation
Business, Management and Accounting · Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Business Process Modeling and Analysis #Data Quality and Management #FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE) #Semantic Web and Ontologies
paper · pdf · doi:10.48550/arxiv.2210.14739
openalex publication_date 2022/10/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The inception of large language models has helped advance state-of-the-art performance on numerous natural language tasks. This has also opened the door for the development of foundation models for other domains and data modalities such as images, code, and music. In this paper, we argue that business process data representations have unique characteristics that warrant the development of a new class of foundation models to handle tasks like process mining, optimization, and decision making. These models should also tackle the unique challenges of applying AI to business processes which include data scarcity, multi-modal representations, domain specific terminology, and privacy concerns.