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This research investigates the application of Large Language Models (LLMs) to augment conversational agents in process mining, aiming to tackle its inherent complexity and diverse skill requirements. While LLM advancements present novel…

人工智能 · 计算机科学 2023-07-20 Urszula Jessen , Michal Sroka , Dirk Fahland

The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a…

The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the entire design and manufacturing workflow. Specifically, we…

The advent of Large Language Models (LLMs) has significantly transformed tasks across Software Engineering. In the context of Business Process Management, LLMs are now being explored as tools to derive process models directly from textual…

软件工程 · 计算机科学 2026-05-01 Pedro-Aarón Hernández-Ávalos , Luciano García-Bañuelos

Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability, and scalability of analyses by automatic parallelization on…

分布式、并行与集群计算 · 计算机科学 2024-07-09 Mario Sänger , Ninon De Mecquenem , Katarzyna Ewa Lewińska , Vasilis Bountris , Fabian Lehmann , Ulf Leser , Thomas Kosch

Large language models are deep learning models with a large number of parameters. The models made noticeable progress on a large number of tasks, and as a consequence allowing them to serve as valuable and versatile tools for a diverse…

软件工程 · 计算机科学 2023-04-11 Maxim Vidgof , Stefan Bachhofner , Jan Mendling

Large Language Models (LLMs) are capable of answering questions in natural language for various purposes. With recent advancements (such as GPT-4), LLMs perform at a level comparable to humans for many proficient tasks. The analysis of…

数据库 · 计算机科学 2023-07-17 Alessandro Berti , Daniel Schuster , Wil M. P. van der Aalst

How to best use Large Language Models (LLMs) for software engineering is covered in many publications in recent years. However, most of this work focuses on widely-used general purpose programming languages. The utility of LLMs for software…

软件工程 · 计算机科学 2025-11-17 Salim Fares , Steffen Herbold

Digital transformation (DX) has recently become a pressing issue for many companies as the latest digital technologies, such as artificial intelligence and the Internet of Things, can be easily utilized. However, devising new business…

其他计算机科学 · 计算机科学 2024-06-11 Masahiro Watanabe , Naoshi Uchihira

The role of large language models (LLMs) in enterprise modeling has recently started to shift from academic research to that of industrial applications. Thereby, LLMs represent a further building block for the machine-supported generation…

多智能体系统 · 计算机科学 2025-01-08 Benedikt Reitemeyer , Hans-Georg Fill

The use of large language models (LLMs) in natural language processing (NLP) tasks is rapidly increasing, leading to changes in how researchers approach problems in the field. To fully utilize these models' abilities, a better understanding…

计算与语言 · 计算机科学 2023-11-07 Bishal Santra , Sakya Basak , Abhinandan De , Manish Gupta , Pawan Goyal

In the realm of Business Process Management (BPM), process modeling plays a crucial role in translating complex process dynamics into comprehensible visual representations, facilitating the understanding, analysis, improvement, and…

软件工程 · 计算机科学 2024-07-01 Humam Kourani , Alessandro Berti , Daniel Schuster , Wil M. P. van der Aalst

Large language models (LLMs) have achieved remarkable performance in language understanding and generation tasks by leveraging vast amounts of online texts. Unlike conventional models, LLMs can adapt to new domains through prompt…

人工智能 · 计算机科学 2024-06-18 Ming Cheung

Business Process Management (BPM) aims to improve organizational activities and their outcomes by managing the underlying processes. To achieve this, it is often necessary to consider information from various sources, including unstructured…

计算与语言 · 计算机科学 2023-07-20 Michael Grohs , Luka Abb , Nourhan Elsayed , Jana-Rebecca Rehse

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

人工智能 · 计算机科学 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

A growing number of publications address the best practices to use Large Language Models (LLMs) for software engineering in recent years. However, most of this work focuses on widely-used general purpose programming languages like Python…

软件工程 · 计算机科学 2026-02-27 Salim Fares

The creation of Business Process Model and Notation (BPMN) models is a complex and time-consuming task requiring both domain knowledge and proficiency in modeling conventions. Recent advances in large language models (LLMs) have…

软件工程 · 计算机科学 2026-01-30 Chantale Lauer , Peter Pfeiffer , Alexander Rombach , Nijat Mehdiyev

Recently, Large Language Models~(LLMs) such as ChatGPT have showcased remarkable abilities in solving general tasks, demonstrating the potential for applications in recommender systems. To assess how effectively LLMs can be used in…

信息检索 · 计算机科学 2025-01-17 Lanling Xu , Junjie Zhang , Bingqian Li , Jinpeng Wang , Sheng Chen , Wayne Xin Zhao , Ji-Rong Wen

Large Language Models (LLMs), such as ChatGPT, exhibit advanced capabilities in generating text, images, and videos. However, their effective use remains constrained by challenges in prompt formulation, personalization, and opaque…

人机交互 · 计算机科学 2025-03-04 Si Thu , A. Baki Kocaballi

Large Language Models (LLMs) are rapidly transforming various fields, and their potential in Business Process Management (BPM) is substantial. This paper assesses the capabilities of LLMs on business process modeling using a framework for…

数据库 · 计算机科学 2024-12-03 Humam Kourani , Alessandro Berti , Daniel Schuster , Wil M. P. van der Aalst
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