30 citations · 36 across the 13 of their papers we have counts for
13 papers
Using Process Mining to Generate AI Agents from Software Engineering Process Records
Saimir Bala, Fabiana Fournier, Lior Limonad +1
Integrating AI agents into Software Engineering (SE) raises an important challenge: how can we specify and realize AI agents that work effectively alongside humans in hybrid SE tea…
A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO
Fabiana Fournier, Lior Limonad
We introduce the process harness, a new mechanism for uplifting legacy workflows into Agentic Business Process Management (Agentic BPM) without replacing the underlying workflow en…
Semantic Feature Analysis: Improving Agents Without Searching Over Rollouts
Roi Ben-Gigi, Yuval David, Fabiana Fournier +4
Ambiguity is an inherent property of natural-language agent specifications. When a system prompt leaves behaviour underdetermined, identical inputs follow divergent execution paths…
Agentic Business Process Management: A Research Manifesto
Diego Calvanese, Angelo Casciani, Giuseppe De Giacomo +15
This paper presents a manifesto that articulates the conceptual foundations of Agentic Business Process Management (APM), an extension of Business Process Management (BPM) for gove…
XABPs: Towards eXplainable Autonomous Business Processes
Peter Fettke, Fabiana Fournier, Lior Limonad +3
Autonomous business processes (ABPs), i.e., self-executing workflows leveraging AI/ML, have the potential to improve operational efficiency, reduce errors, lower costs, improve res…
The WHY in Business Processes: Unification of Causal Process Models
Yuval David, Fabiana Fournier, Lior Limonad +1
Causal reasoning is essential for business process interventions and improvement, requiring a clear understanding of causal relationships among activity execution times in an event…
Agentic AI Process Observability: Discovering Behavioral Variability
Fabiana Fournier, Lior Limonad, Yuval David
AI agents that leverage Large Language Models (LLMs) are increasingly becoming core building blocks of modern software systems. A wide range of frameworks is now available to suppo…
Selecting the Right LLM for eGov Explanations
Lior Limonad, Fabiana Fournier, Hadar Mulian +3
The perceived quality of the explanations accompanying e-government services is key to gaining trust in these institutions, consequently amplifying further usage of these services.…
Monetizing Currency Pair Sentiments through LLM Explainability
Lior Limonad, Fabiana Fournier, Juan Manuel Vera Díaz +3
Large language models (LLMs) play a vital role in almost every domain in today's organizations. In the context of this work, we highlight the use of LLMs for sentiment analysis (SA…
Towards a Benchmark for Causal Business Process Reasoning with LLMs
Fabiana Fournier, Lior Limonad, Inna Skarbovsky
Large Language Models (LLMs) are increasingly used for boosting organizational efficiency and automating tasks. While not originally designed for complex cognitive processes, recen…
How well can a large language model explain business processes as perceived by users?
Dirk Fahland, Fabiana Fournier, Lior Limonad +2
Large Language Models (LLMs) are trained on a vast amount of text to interpret and generate human-like textual content. They are becoming a vital vehicle in realizing the vision of…
Toward Methodical Discovery and Handling of Hidden Assumptions in Complex Systems and Models
David Harel, Uwe Aßmann, Fabiana Fournier +3
Methodologies for development of complex systems and models include external reviews by domain and technology experts. Among others, such reviews can uncover undocumented built-in…
The WHY in Business Processes: Discovery of Causal Execution Dependencies
Fabiana Fournier, Lior Limonad, Inna Skarbovsky +1
Unraveling the causal relationships among the execution of process activities is a crucial element in predicting the consequences of process interventions and making informed decis…