ABSTRACT
The article emphasizes the critical importance of language generation today, particularly focusing on three key aspects: Multitasking, Multilinguality, and Multimodality, which are pivotal for the Natural Language Generation community. It delves into the activities conducted within the Multi3Generation COST Action (CA18231) and discusses current trends and future perspectives in language generation.
The Multi3Generation COST Action is a collaborative project that brings together researchers from various fields, all centered around Natural Language Generation. Natural Language Generation involves using computers to generate human-like language for tasks such as translation, summarization, question-answering, and dialogue interaction, among others. The Action addresses common challenges including efficient information representation, advanced machine learning techniques, managing uncertainty in human-Natural Language Generation interactions, and using structured knowledge from diverse sources like databases, images, and videos. Its overarching goal is to make NLG beneficial to society and widely accessible by fostering collaboration between industry and academic experts. Structured into five working groups, the Action focuses on specific aspects of Natural Language Generation, such as understanding and generating different types of information, developing efficient machine learning algorithms, enhancing dialogue and conversational language generation using knowledge bases, and fostering industry collaboration and end-user engagement. With over 133 scientists from 34 countries involved, spanning disciplines from computer science to linguistics, the project promotes diversity and inclusivity, with 60% male and 40% female participants. Relevant businesses like Unbabel and JabberBrain and other AI stakeholders like the Center for Responsible AI contribute to the Action, aiming to have a broader European impact. The Multi3Generation Action prioritizes three main areas: Multitasking, Multilinguality, and Multimodality, aiming to enhance language generation in these domains to support underrepresented languages and meet diverse user needs. The article provides insights into the initiatives and planned activities of Multi3Generation, offering valuable information for those interested in NLG and shedding light on future perspectives in this field.
ABSTRACT
This work presents a digital-twin-based framework focused on orchestrating human-centered processes toward Industry 5.0. By including workers and their digital replicas in the loop of the digital twin, the proposed framework extends the traditional model of the factory's digital twin, which instead does not adequately consider the human component. The overall goal of the authors is to provide a reference architecture to manufacturing companies for a digital-twin-based platform that promotes harmonization and orchestration between humans and (physical and virtual) machines through the monitoring, simulation, and optimization of their interactions. In addition, the platform enhances the interactions of the stakeholders with the digital twin, considering that the latter cannot always be fully autonomous, and it can require human intervention. The paper also presents an implemented scenario adhering to the proposed framework's specifications, which is also validated with a real case study set in a factory plant that produces wooden furniture, thus demonstrating the validity of the overall proposed approach.
