Scope The challenges of human behavior recognition based on sensor data often require
addressing the needs of various new users in real-world situations, which leads to difficulties …

Natural Language Processing (NLP) for Requirements Engineering (RE)(NLP4RE) seeks to
apply NLP tools, techniques, and resources to the RE process to increase the quality of the …

Machine learning techniques have shown promising results in classifying non-functional
requirements (NFR). However, the lack of annotated training data in the domain of …

Retrained large language models (LLMs) have become extensively used across various sub-
disciplines of natural language processing (NLP). In NLP, text classification problems have …

Specifying legal requirements for software systems to ensure their compliance with the
applicable regulations is a major concern of requirements engineering. Personal data which …

Abstract [Context] Companies are increasingly recognizing the importance of automating
Requirements Engineering (RE) tasks due to their resource-intensive nature. The advent of …

Artificial intelligence (AI) has witnessed an exponential increase in use in various
applications. Recently, the academic community started to research and inject new AI-based …

Ambiguity means that a single reader can interpret the natural language (NL) software
requirement in more than one way or that multiple readers come to different interpretations …

The rapid emergence of large generative AI models has demonstrated their utility across a
multitude of tasks. Ensuring the quality and accuracy of the models' output is done in …

Allocation of requirements to different teams is a typical preliminary task in large-scale
system development projects. This critical activity is often performed manually and can …