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Outputs (3144)

Designing a generative AI enabled learning environment for mathematics word problem solving in primary schools: Learning performance, attitudes and interaction (2025)
Journal Article
Liu, J., Sun, D., Sun, J., Wang, J., & Yu, P. L. H. (2025). Designing a generative AI enabled learning environment for mathematics word problem solving in primary schools: Learning performance, attitudes and interaction. Computers and Education: Artificial Intelligence, 9, Article 100438. https://doi.org/10.1016/j.caeai.2025.100438

Mathematics word problem solving is a critical component of elementary education, yet many students encounter persistent difficulties in this area due to the combined cognitive demands of linguistic comprehension and mathematical re... Read More about Designing a generative AI enabled learning environment for mathematics word problem solving in primary schools: Learning performance, attitudes and interaction.

Potential-driven Metal Cycling: JADES Census of Gas-phase Metallicity for Galaxies at 1 < z < 7 (2025)
Journal Article
Jia, C., Wang, E., Lyu, C., Ma, C., Song, J., Chen, Y., Wang, K., Yu, H., Chen, Z., Wang, J., Wang, Y., & Kong, X. (2025). Potential-driven Metal Cycling: JADES Census of Gas-phase Metallicity for Galaxies at 1 < z < 7. Astrophysical Journal Letters, 986(2), Article L24. https://doi.org/10.3847/2041-8213/addfd9

The gravitational potential is established as a critical determinant of gas-phase metallicity (12+log(O/H)) in low-redshift galaxies, whereas its influence remains unconfirmed at high redshifts. We investigate the correlation between gas-phase metall... Read More about Potential-driven Metal Cycling: JADES Census of Gas-phase Metallicity for Galaxies at 1 < z < 7.

A Deep Learning Approach for Paragraph-Level Paraphrase Generation for Plagiarism Detection (2025)
Journal Article
Saqaabi, A. A., Stewart, C., Akrida, E., & Cristea, A. I. (2025). A Deep Learning Approach for Paragraph-Level Paraphrase Generation for Plagiarism Detection. Neural Processing Letters, 57, 59. https://doi.org/10.1007/s11063-025-11771-9

Expressing information in different forms is an important skill that students should develop in school. This skill positively impacts academic reading and writing. However, it can also lead to negative consequences, such as plagiarism. Students may p... Read More about A Deep Learning Approach for Paragraph-Level Paraphrase Generation for Plagiarism Detection.

Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective (2025)
Journal Article
Shao, M., Wang, Z., Duan, H., Huang, Y., Zhai, B., Wang, S., Long, Y., & Zheng, Y. (online). Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective. IEEE Transactions on Medical Imaging, https://doi.org/10.1109/tmi.2025.3579213

Precise segmentation of brain tumors, particularly contrast-enhancing regions visible in post-contrast MRI (areas highlighted by contrast agent injection), is crucial for accurate clinical diagnosis and treatment planning but remains challenging. How... Read More about Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective.

Beyond Syntax: How Do LLMs Understand Code? (2025)
Presentation / Conference Contribution
North, M., Atapour-Abarghouei, A., & Bencomo, N. (2025, April). Beyond Syntax: How Do LLMs Understand Code?. Presented at 2025 IEEE/ACM International Conference on Software Engineering ICSE, Ottawa , Canada

Within software engineering research, Large Language Models (LLMs) are often treated as 'black boxes', with only their inputs and outputs being considered. In this paper, we take a machine interpretability approach to examine how LLMs internally repr... Read More about Beyond Syntax: How Do LLMs Understand Code?.

Development and Evaluation of Adaptive Learning Support System Based on Ontology of Multiple Programming Languages (2025)
Journal Article
Na Nongkhai, L., Wang, J., & Mendori, T. (2025). Development and Evaluation of Adaptive Learning Support System Based on Ontology of Multiple Programming Languages. Education Sciences, 15(6), Article 724

This paper introduces an ontology-based approach within an adaptive learning support system for computer programming. This system is designed to deliver personalized programming exercises that are tailored to individual learners’ skill levels. This p... Read More about Development and Evaluation of Adaptive Learning Support System Based on Ontology of Multiple Programming Languages.

CLPFusion: A Latent Diffusion Model Framework for Realistic Chinese Landscape Painting Style Transfer (2025)
Journal Article
Pan, J., Li, F. W. B., Yang, B., & Nan, F. (2025). CLPFusion: A Latent Diffusion Model Framework for Realistic Chinese Landscape Painting Style Transfer. Computer Animation and Virtual Worlds, 36(3), Article e70053. https://doi.org/10.1002/cav.70053

This study focuses on transforming real-world scenery into Chinese landscape painting masterpieces through style transfer. Traditional methods using convolutional neural networks (CNNs) and generative adversarial networks (GANs) often yield inconsist... Read More about CLPFusion: A Latent Diffusion Model Framework for Realistic Chinese Landscape Painting Style Transfer.

Surprise! Surprise! Learn and Adapt (2025)
Presentation / Conference Contribution
Samin, H., Walton, D., & Bencomo, N. (2025, May). Surprise! Surprise! Learn and Adapt. Presented at 24th International Conference on Autonomous Agents and Multiagent Systems, Detroit, Michigan, USA

Self-adaptive systems (SAS) adjust their behavior at runtime in response to environmental changes, which are often unpredictable at design time. SAS must make decisions under uncertainty, balancing trade-offs between quality attributes (e.g., cost mi... Read More about Surprise! Surprise! Learn and Adapt.