相关论文: Beyond Self-Promotion: How Software Engineering Re…
Software engineering (SE) conferences are vital for knowledge exchange and collaboration, yet can also involve significant barriers for researchers in geographically distant regions such as New Zealand. We identify barriers such as high…
Over the past few years, deep learning methods have been applied for a wide range of Software Engineering (SE) tasks, including in particular for the important task of automatically predicting and localizing faults in software. With the…
Semantic search with large language models (LLMs) enables retrieval by meaning rather than keyword overlap, but scaling it requires major inference efficiency advances. We present LinkedIn's LLM-based semantic search framework for AI Job…
Keeping up with the research literature plays an important role in the workflow of scientists - allowing them to understand a field, formulate the problems they focus on, and develop the solutions that they contribute, which in turn shape…
Nowadays, the quality of responses generated by different modern large language models (LLMs) is hard to evaluate and compare automatically. Recent studies suggest and predominantly use LLMs for reference-free evaluation of open-ended…
Scientific collaboration in almost every discipline is mainly driven by the need of sharing knowledge, expertise, and pooled resources. Science is becoming more complex which has encouraged scientists to involve more in collaborative…
Each year, significant investment of time and resources is made to improve diversity within engineering across a range of federal and state agencies, private/not-for-profit organizations, and foundations. In spite of decades of investments,…
As the number of accepted papers at AI and ML conferences reaches into the thousands, it has become unclear how researchers access and read research publications. In this paper, we investigate the role of social media influencers in…
LLM-based agents have shown promising capabilities in a growing range of software engineering (SWE) tasks. However, advancing this field faces two critical challenges. First, high-quality training data is scarce, especially data that…
With the advent of open source software, a veritable treasure trove of previously proprietary software development data was made available. This opened the field of empirical software engineering research to anyone in academia. Data that is…
The networking field has recently started to incorporate artificial intelligence (AI), machine learning (ML), big data analytics combined with advances in networking (such as software-defined networks, network functions virtualization, and…
Collaboration is crucial in Software Engineering (SE), yet factors like gender bias can shape team dynamics and behaviours. This study examines an eight-week project involving 39 SE students across eight teams contributing to GitHub…
In recent years supervised representation learning has provided state of the art or close to the state of the art results in semantic analysis tasks including ranking and information retrieval. The core idea is to learn how to embed items…
The way practitioners perform maintenance tasks in practice is little known by researchers. In turn, practitioners are not always up to date with the proposals provided by the research community. This work investigates the gap between…
Glass published the first report on the assessment of systems and software engineering scholars and institutions two decades ago. The ongoing, annual survey of publications in this field provides fund managers, young scholars, graduate…
As software engineering research becomes more concerned with the psychological, sociological and managerial aspects of software development, relevant theories from reference disciplines are increasingly important for understanding the…
As a newly designated professional title, research software engineers (RSEs) link the two worlds of software engineering and research science. They lack clear development and training opportunities, particularly in the realm of mentoring.…
Several recent initiatives have proposed new directions for research practices and their operations in the computer science community, from updated codes of conduct that clarify the use of AI-assisted tools to the inclusion of ethical…
Talent search and recommendation systems at LinkedIn strive to match the potential candidates to the hiring needs of a recruiter or a hiring manager expressed in terms of a search query or a job posting. Recent work in this domain has…
The increasing adoption and commercialization of generalized Large Language Models (LLMs) have profoundly impacted various aspects of our daily lives. Initially embraced by the computer science community, the versatility of LLMs has found…