1 citations · 1 across the 3 of their papers we have counts for
6 papers
Understanding LLMs in Title-Abstract Screening: From Disagreements to Recommendations
Mika Mäntylä, Patricia Matsubara, Katia Romero Felizardo +5
Several studies have examined the use of large language models (LLMs) for title-abstract screening in systematic reviews (SRs), reporting mixed accuracy. However, questions of reli…
AISysRev -- LLM-based Tool for Title-abstract Screening
Aleksi Huotala, Miikka Kuutila, Olli-Pekka Turtio +2
Conducting systematic reviews is laborious. In the screening or study selection phase, the number of papers can be overwhelming. Recent research has demonstrated that large languag…
Research Artifacts in Secondary Studies: A Systematic Mapping in Software Engineering
Aleksi Huotala, Miikka Kuutila, Mika Mäntylä
Context: Systematic reviews (SRs) summarize state-of-the-art evidence in science, including software engineering (SE). Objective: Our objective is to evaluate how SRs report resear…
SESR-Eval: Dataset for Evaluating LLMs in the Title-Abstract Screening of Systematic Reviews
Aleksi Huotala, Miikka Kuutila, Mika Mäntylä
Background: The use of large language models (LLMs) in the title-abstract screening process of systematic reviews (SRs) has shown promising results, but suffers from limited perfor…
Detection, Classification and Prevalence of Self-Admitted Aging Debt
Murali Sridharan, Mika Mäntylä, Leevi Rantala
Context: Previous research on software aging is limited with focus on dynamic runtime indicators like memory and performance, often neglecting evolutionary indicators like source c…
What Makes Programmers Laugh? Exploring the Submissions of the Subreddit r/ProgrammerHumor
Miikka Kuutila, Leevi Rantala, Junhao Li +2
Background: Humor is a fundamental part of human communication, with prior work linking positive humor in the workplace to positive outcomes, such as improved performance and job s…