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    An automated approach to identify sarcasm in low-resource language. by Shumaila Khan, Iqbal Qasim, Wahab Khan, Aurangzeb Khan, Javed Ali Khan, Ayman Qahmash, Yazeed Yasin Ghadi

    Published 2024-01-01
    “…While fewer studies identifying sarcasm have focused on low-resource languages, most of the work is in English. This research addresses the gap by exploring the efficacy of diverse machine learning (ML) algorithms in identifying sarcasm in Urdu. …”
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  5. 145

    A survey on privacy risks and protection in large language models by Kang Chen, Xiuze Zhou, Yuanguo Lin, Shibo Feng, Li Shen, Pengcheng Wu

    Published 2025-08-01
    “…Next, we review existing privacy protection against such risks, such as inference detection, federated learning, backdoor mitigation, and confidential computing, and assess their effectiveness in preventing privacy leakage. …”
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  6. 146

    Evaluating DL Model Scaling Trade-Offs During Inference via an Empirical Benchmark Analysis by Demetris Trihinas, Panagiotis Michael, Moysis Symeonides

    Published 2024-12-01
    “…This work presents a benchmarking framework designed to assess DL model scaling across three key performance axes during model inference: classification accuracy, computational overhead, and latency. …”
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  7. 147

    Exploring Perspectives on Student Engagement and Learning Outcomes in Online-Offline English Teaching: A Structured Assessment Using SuperHyperSoft and PSI Methods by Dongqiao Chu

    Published 2025-05-01
    “…By assessing key criteria such as participation levels, content retention, and interaction quality, this study aims to provide insights into the most effective teaching methodologies for enhancing language acquisition and student performance in university English courses. …”
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  8. 148

    Exploring the Impact of Computer-Supported Input Enhancement on Enhancing Parallel Structures in EFL Learners' Writing: A Comparative Study in Flipped Online and Face-to-Face Highe... by Mehri Farzaneh, Farzaneh Khodabandeh, Ehsan Rezvani

    Published 2024-06-01
    “…These results offer empirical evidence supporting the effectiveness of input enhancement techniques and underscore the significance of explicit instruction and practice in language learning. The integration of these techniques by language instructors and curriculum developers holds promise for enhancing the acquisition and application of parallel structures in language learning settings.…”
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    The Ethical Significance of Brain-Computer Interfaces as Enablers of Communication by Toma Gruica

    Published 2025-08-01
    “…Barriers to and mediators of brain-computer interface user acceptance: Focus group findings. …”
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    Enhancing Computational Thinking of Deaf Students Using STEAM Approach by Saowaluck Kaewkamnerd, Alisa Suwannarat

    Published 2025-05-01
    “…To help Deaf students (those with hearing loss and using sign language for communication) enhance their CT, a STEAM learning program using a physical computing tool is proposed. …”
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    A segment-based framework for explainability in animal affective computing by Tali Boneh-Shitrit, Lauren Finka, Daniel S. Mills, Stelio P. Luna, Emanuella Dalla Costa, Anna Zamansky, Annika Bremhorst

    Published 2025-04-01
    “…This scoring system allows for systematic, measurable comparisons of different pipelines in terms of their visual explanations within animal affective computing. Such a metric can serve as a quality indicator when developing classifiers for known biologically relevant segments or help researchers assess whether a classifier is using expected meaningful regions when exploring new potential indicators. …”
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