Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text
- URL: http://arxiv.org/abs/2605.24546v1
- Date: Sat, 23 May 2026 12:28:07 GMT
- Title: Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text
- Abstract summary: We introduce a resource-aware generation pipeline that produces formal BPMN 2.0 collaboration diagrams from natural-language descriptions.<n>Experiments on ten business processes with nine LLMs show strong resource discovery while preserving control-flow quality and adding only marginal runtime overhead.
- Score: 46.26852058384475
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Process modeling is a sub-domain of Business Process Management (BPM) focused on the translation of process artifacts into formal models. This task traditionally requires extensive human input and domain expertise in both BPM notations and the specific business context. While Large Language Models (LLMs) can now automate much of this manual work, current text-to-model approaches focus predominantly on the control-flow perspective-ordering activities without considering the collaborative aspect of the processes. In this paper, we introduce a resource-aware generation pipeline that produces formal BPMN 2.0 collaboration diagrams from natural-language descriptions. Rather than solely prompting an LLM for raw XML, we describe a compact, executable intermediate language with mandatory resource details defining both the organization (pool) and the role (lane). Cross-organization dependencies are materialized using the standard formal notation for such interactions-message events-while an orthogonal layout routine automatically handles the spatial arrangement of elements within pools and lanes. Experiments on ten business processes with nine LLMs show strong resource discovery while preserving control-flow quality and adding only marginal runtime overhead. This approach moves generative modeling toward a more comprehensive, multi-collaborative representation of business operations.
Related papers
- PolyWorkBench: Benchmarking Multilingual Long-Horizon LLM Agents [72.96251271825038]
Large language model (LLM) agents have shown strong performance in long-horizon tasks that require planning, tool use, and interaction with external environments.<n>Most existing benchmarks implicitly assume a monolingual setting, where the entire execution process is conducted within a single language.<n>We introduce PolyWorkBench, a benchmark for evaluating agents on multilingual long-horizon workplace work.
arXiv Detail & Related papers (2026-07-07T08:50:09Z) - Pragmos: A Process Agentic Modeling System [0.0]
Large Language Models (LLMs) are now being explored as tools to derive process models directly from textual descriptions.<n>We envision modeling as an open-ended conversational activity, best supported by an interactive, iterative process involving both humans and LLM.<n>We present our research agenda and introduce Pragmos, a prototype system that operationalizes this vision.
arXiv Detail & Related papers (2026-04-30T01:49:19Z) - ContextNav: Towards Agentic Multimodal In-Context Learning [85.05420047017513]
ContextNav is an agentic framework that integrates the scalability of automated retrieval with the quality and adaptiveness of human-like curation.<n>It builds a resource-aware multimodal embedding pipeline, maintains a retrievable vector database, and applies agentic retrieval and structural alignment to construct noise-resilient contexts.<n> Experimental results demonstrate that ContextNav achieves state-of-the-art performance across various datasets.
arXiv Detail & Related papers (2025-10-06T07:49:52Z) - Collaborative and Proactive Management of Task-Oriented Conversations [12.363852182404285]
Task oriented dialogue systems (TODs) complete tasks based on user preferences across natural language interactions.<n>While proactive planning is crucial for task completion, many existing TODs overlook effective goal-aware planning.<n>This paper creates a model for managing task-oriented conversations, conceptualized centered on the information state approach to dialogue management.
arXiv Detail & Related papers (2025-09-26T04:18:13Z) - Leveraging Machine Learning and Enhanced Parallelism Detection for BPMN Model Generation from Text [75.77648333476776]
This paper introduces an automated pipeline for extracting BPMN models from text.<n>A key contribution of this work is the introduction of a newly annotated dataset.<n>We augment the dataset with 15 newly annotated documents containing 32 parallel gateways for model training.
arXiv Detail & Related papers (2025-07-11T07:25:55Z) - Beyond Formal Semantics for Capabilities and Skills: Model Context Protocol in Manufacturing [0.12289361708127876]
We present an alternative approach based on the recently introduced Model Context Protocol (MCP)<n>MCP allows systems to expose functionality through a standardized interface that is directly consumable by LLM-based agents.
arXiv Detail & Related papers (2025-06-12T13:02:16Z) - Core Context Aware Transformers for Long Context Language Modeling [50.774702091154204]
We propose a plug-and-play Core Context Aware (CCA) Attention for efficient long-context modeling.<n>Our method automatically focuses and strengthens core context while diminishing redundancy during the learning process.<n>Our method is able to replace the self-attention module in existing Large Language Models with minimal fine-tuning cost.
arXiv Detail & Related papers (2024-12-17T01:54:08Z) - From Dialogue to Diagram: Task and Relationship Extraction from Natural
Language for Accelerated Business Process Prototyping [0.0]
This paper introduces a contemporary solution, where central to our approach, is the use of dependency parsing and Named Entity Recognition (NER)
We utilize Subject-Verb-Object (SVO) constructs for identifying action relationships and integrate semantic analysis tools, including WordNet, for enriched contextual understanding.
The system adeptly handles data transformation and visualization, converting verbose extracted information into BPMN (Business Process Model and Notation) diagrams.
arXiv Detail & Related papers (2023-12-16T12:35:28Z) - Concepts and Algorithms for Agent-based Decentralized and Integrated
Scheduling of Production and Auxiliary Processes [78.120734120667]
This paper describes an agent-based decentralized and integrated scheduling approach.
Part of the requirements is to develop a linearly scaling communication architecture.
The approach is explained using an example based on industrial requirements.
arXiv Detail & Related papers (2022-05-06T18:44:29Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.