The optimization and automation of process deployment operations play a key role in enhancing efficiency and adaptability in Business Process Management. This paper presents NL2ProcessOps, a novel approach leveraging Large Language Models (LLMs) and concepts such as Retrieval Augmented Generation (...
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This paper introduces a microservices-based architecture de- signed for executing complex linguistic tasks using Large Language Mod- els (LLMs) and Knowledge Graphs (KGs). It has been conceived by fo- cusing on the legal domain, and it integrates Domain-specific KGs and Constraint KGs to address...
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Recent years have witnessed an ever-growing use of Large Language Models (LLMs) to lower the technical barrier for several tasks, ranging from coding to querying relational databases to composing services. In this work, we focus on using LLMs to simplify access to data in the industrial scenario,...
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In the field of digital humanities, the mode of information consumption constitutes a fundamental factor in the quality of research. The structuring of data into knowledge graphs provides a valuable tool for navigating concepts and exploring new ideas. However, the information are often spread...
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In the last years’ digitalization process, the creation and management of documents in various domains, particularly in Public Administration (PA), have become increasingly complex and diverse. This complexity arises from the need to handle a wide range of document types, often characterized by...
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This study introduces ARTIS, an AI-powered interface aimed at enhancing text comprehension in children with language and learning disorders and deficits. Leveraging neuro-psycholinguistic models, ARTIS offers personalized practice at varying difficulty levels, targeting specific linguistic...
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The integration of digital technology and AI systems has prompted extensive inquiries into their ethical design and im-plementation. Trustworthy AI, essential for fairness, robustness, safety, and transparency, is recognized as fundamental,transcending pure technological interaction. This is...
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The problem of multi-object tracking (MOT) consists in detecting and tracking all the objects in a video sequence while keeping a unique identifier for each object. It is a challenging and fundamental problem for robotics. In precision agriculture the challenge of achieving a satisfactory solution...
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Large Language Models (LLMs) and Visual Language Models (VLMs) are attracting increasing interest due to their improving performance and applications across various domains and tasks. However, LLMs and VLMs can produce erroneous results, especially when a deep understanding of the problem domain is...
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In precision agriculture, the scarcity of labeled data and significant covariate shifts pose unique challenges for training machine learning models. This scarcity is particularly problematic due to the dynamic nature of the environment and the evolving appearance of agricultural subjects as living...