2025
Authors
Pajón-Sanmartín, A; De Arriba-Pérez, F; García-Méndez, S; Leal, F; Malheiro, B; Burguillo-Rial, JC;
Publication
IEEE ACCESS
Abstract
Transformer models have significantly advanced the field of emotion recognition. However, there are still open challenges when exploring open-ended queries for Large Language Models (llms). Although current models offer good results, automatic emotion analysis in open texts presents significant challenges, such as contextual ambiguity, linguistic variability, and difficulty interpreting complex emotional expressions. These limitations make the direct application of generalist models difficult. Accordingly, this work compares the effectiveness of fine-tuning and prompt engineering in emotion detection in three distinct scenarios: (i) performance of fine-tuned pre-trained models and general-purpose llms using simple prompts; (ii) effectiveness of different emotion prompt designs with llms; and (iii) impact of emotion grouping techniques on these models. Experimental tests attain metrics above 70% with a fine-tuned pre-trained model for emotion recognition. Moreover, the findings highlight that llms require structured prompt engineering and emotion grouping to enhance their performance. These advancements improve sentiment analysis, human-computer interaction, and understanding of user behavior across various domains.
2025
Authors
Méndez, SG; Arriba Pérez, Fd; Leal, F; Veloso, B; Malheiro, B; Burguillo Rial, JC;
Publication
CoRR
Abstract
2025
Authors
Donner, RV; Barbosa, SM;
Publication
Abstract
2025
Authors
Barbosa, S; Chambers, S;
Publication
Abstract
2025
Authors
Barbosa, S; Chambers, S; Pawlak, W; Fortuniak, K; Paatero, J; Röttger, A; Röttger, S; Chen, X; Melintescu, AM; Martin, D; Kikaj, D; Wenger, A; Stanley, K; Ramos, JB; Hatakka, J; Anttila, T; Aaltonen, H; Dias, N; Silva, ME; Castro, JA; Lappalainen, K; Azevedo, E; Kulmala, M;
Publication
EPJ Nuclear Sciences and Technologies
Abstract
Project NuClim (Nuclear observations to improve Climate research and GHG emission estimates) aims to use high-quality measurements of atmospheric radon activity concentration and ambient radioactivity to advance climate science and improve radiation protection and nuclear surveillance capabilities. It is supported by new metrological capabilities developed in the EMPIR project 19ENV01 traceRadon. This work reviews the scientific objectives of project NuClim in terms of both climate science and radiological protection, and provides an overview of the NuClim field campaign and the various nuclear measurements being implemented within the scope of the project. © S. Barbosa et al., Published by EDP Sciences, 2025.
2025
Authors
Costa, L; Barbosa, S; Cunha, J;
Publication
JOURNAL OF COMPUTER LANGUAGES
Abstract
User studies are paramount for advancing research in software engineering, particularly when evaluating tools and techniques involving programmers. However, researchers face several barriers when performing them despite the existence of supporting tools. We base our study on a set of tools and researcher-reported barriers identified in prior work on user studies in software engineering. In this work, we study how existing tools and their features cope with previously identified barriers. Moreover, we propose new features for the barriers that lack support. We validated our proposal with 102 researchers, achieving statistically significant positive support for all but one feature. We study the current gap between tools and barriers, using features as the bridge. We show there is a significant lack of support for several barriers, as some have no single tool to support them.
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