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    TOLD LIKE IT IS! AN EVALUATION OF AN INTEGRATED ORAL DEVELOPMENT PILOT PROJECT by David Barr, Jonathan Leakey, Alexandre Ranchoux

    Published 2005-09-01
    “…Much established pedagogical and CALL (computer-assisted language learning) research advocates an integrated constructivist approach to the use of technology in language learning. …”
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    The impact of using DeepL Translator on Chinese EFL students’ story writing by Liang Lijin

    Published 2024-11-01
    “…This study highlights the role of AI-assisted tools in language learning and offers practical suggestions for language pedagogy and future research.…”
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    When Multimodal Large Language Models Meet Computer Vision: Progressive GPT Fine-Tuning and Stress Testing by Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios K. Nasiopoulos

    Published 2025-01-01
    “…The rapid evolution of Multimodal Large Language Models (LLMs) has redefined the landscape of artificial intelligence, with OpenAI’s GPT-4o representing a transformative leap in multimodal learning and processing. …”
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    A systematic review of the first year of publications on ChatGPT and language education: Examining research on ChatGPT’s use in language learning and teaching by Belle Li, Victoria L. Lowell, Chaoran Wang, Xiangning Li

    Published 2024-12-01
    “…Other findings include that ChatGPT plays multifaceted roles, supporting self-directed language learning, content generation, and teacher workflows. …”
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    Medium-sized protein language models perform well at transfer learning on realistic datasets by Luiz C. Vieira, Morgan L. Handojo, Claus O. Wilke

    Published 2025-07-01
    “…While larger models, such as the 15 billion parameter model ESM-2, promise to capture more complex patterns in sequence space, they also present practical challenges due to their high dimensionality and high computational cost. We systematically evaluated the performance of various ESM-style models across multiple biological datasets to assess the impact of model size on transfer learning via feature extraction. …”
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    Large language models predict cognition and education close to or better than genomics or expert assessment by Tobias Wolfram

    Published 2025-07-01
    “…Integrating various measures of computational linguistics and large language model-based embeddings within a SuperLearner framework trained on short aspirational essays written at age 11, we accurately predict cognition and non-cognitive traits at the same and later age to a similar degree as teacher assessments, and better than genomic data. …”
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