Related papers: Agile Information System Development Organizations…
Generative, ML-driven interactive systems have the potential to change how people interact with computers in creative processes - turning tools into co-creators. However, it is still unclear how we might achieve effective human-AI…
Deep Learning (DL) has had an immense success in the recent past, leading to state-of-the-art results in various domains such as image recognition and natural language processing. One of the reasons for this success is the increasing size…
Knowledge Distillation (KD) transfers knowledge from large models to small models and has recently achieved remarkable success. However, the reliability of existing KD methods in real-world applications, especially under distribution shift,…
Collective intelligence among gig workers yields considerable advantages, including improved information exchange, deeper social bonds, and stronger advocacy for better labor conditions. Especially as it enables workers to collaboratively…
Large language models (LLM) are advanced AI systems trained on extensive textual data, leveraging deep learning techniques to understand and generate human-like language. Today's LLMs with billions of parameters are so huge that hardly any…
Large language models (LLMs) offer strong capabilities but raise cost and privacy concerns, whereas small language models (SLMs) facilitate efficient and private local inference yet suffer from limited capacity. To synergize the…
Collaborative learning has emerged as a key paradigm in large-scale intelligent systems, enabling distributed agents to cooperatively train their models while addressing their privacy concerns. Central to this paradigm is knowledge…
The rise of sixth generation (6G) wireless networks promises to deliver ultra-reliable, low-latency, and energy-efficient communications, sensing, and computing. However, traditional centralized artificial intelligence (AI) paradigms are…
Addressing global societal challenges necessitates insights and expertise that transcend the boundaries of individual disciplines. In recent decades, interdisciplinary collaboration has been recognised as a vital driver of innovation and…
Work must be reshaped in the upcoming new era characterized by new challenges and the presence of new technologies and computational tools. Over-automation seems to be the driver of the digitalization process. Substitution is the paradigm…
According to socio-constructivism approach, collective situations are promoted to favor learning in classroom, at a distance or in a blended educational context. So, many Information and Communication Technologies (ICT) are provided to…
One factor of success in software development companies is their ability to deliver good quality products, fast. For this, they need to improve their software development practices. We work with a medium-sized company modernizing its…
This paper presents an empirical study on how self- organized software teams could attain high performance using agile and lean practices. In particular, the paper qualitatively examines characteristics of high performance and self-…
In an increasing number of AI scenarios, collaborations among different organizations or agents (e.g., human and robots, mobile units) are often essential to accomplish an organization-specific mission. However, to avoid leaking useful and…
We study the structural properties of large scale collaboration in online communities of innovation and the role that position in the community plays in determining knowledge contribution. Contrary to previous research, we argue for a more…
This research, focused on small work groups, proposes to examine the role of the leader in the appropriation of collaborative information systems. It is based on a three-year action research conducted during the implementation of the…
The rapid rise of Large Language Models (LLMs) has revolutionized various artificial intelligence (AI) applications, from natural language processing to code generation. However, the computational demands of these models, particularly in…
In agile software development, breaking down user stories into actionable tasks is a critical yet time-consuming process. This paper investigates the potential of Generative AI tools to assist in task splitting, aiming to enhance planning…
Effective leadership is one of the key drivers of business and project success, and one of the most active areas of management research. But how does leadership work in agile software development, which emphasizes self-management and…
Context: In the light of the swift and iterative nature of Agile Software Development (ASD) practices, establishing deeper insights into capability measurement within the context of team formation is crucial, as the capability of…