Natural language processing (NLP) has played an important role in several computer science areas, and requirements engineering (RE) is not an exception. For over 25 years, several works were published on the application of NLP techniques to address RE specific problems, such as traceability, categorisation, defect detection, model generation, and more. In the last few years, the advent of massive and heterogeneous natural language RE-relevant sources, like tweets and app reviews, has attracted even more interest from the RE community in NLP. Furthermore, we witness the novel golden age of NLP technologies, driven by advancements in Large Language Models (LLMs), which have significantly enhanced the accuracy of various NLP tasks. The current document is a preface to the proceedings of the 8th Workshop on Natural Language Processing for Requirements Engineering (NLP4RE'25, https://nlp4re.github.io/2025/), co-located with the 31st International Working Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2025) held in Barcelona, Spain. The workshop features two exciting keynotes: one keynote from Eric Knauss (Chalmers, University of Gothenburg, Sweden) and one keynote from Ramon Ferrer (Universitat Politècnica de Catalunya, Spain). This year, the NLP4RE workshop received 9 submissions. Each paper was independently reviewed by three program committee members. Based on these evaluations, five papers were accepted: 2 long research papers, 2 short research papers and 1 project report. Additionaly, the workshop features a special presentation of the Handbook on Natural Language Processing for Requirements Engineering, by Alessio Ferrari and Gouri Ginde (Eds.), a comprehensive guide on how natural language processing (NLP) can be leveraged to enhance various aspects of requirements engineering (RE).
2. Papers presented at NLP4RE’25
• Rrezarta Krasniqi. Open Challenges in NLP for NFRs: A Focus on Semantics, Generalization, and
Interpretability • Vibhashree Hippargi, Erik Kamsties and Jürgen Naumann. Evaluating the Capabilities of LLMs in
Traceability Maintenance for Automotive System and Software Requirements
We warmly thank all the reviewers of our Program Committee (PC), who helped in the selection of the papers by providing timely and accurate reviews. The PC members of NLP4RE’25 are: