Showing 1 - 20 results of 3,356 for search '(( studies found decrease ) OR ( ai ((large decrease) OR (marked decrease)) ))', query time: 0.52s Refine Results
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    Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

    Published 2025
    “…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”
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    Study area. by Bao Zhou (20670850)

    Published 2025
    Subjects:
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    Quality appraisal of qualitative studies. by Sarah E. Janek (20570764)

    Published 2025
    “…Despite a high annual HIV incidence, extant literature has found BMSM to engage in fewer sexual risk behaviors than White and Hispanic/Latino men who have sex with men, resulting in a gap between risk behaviors and the inequity of HIV infection. …”
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    Quality appraisal of quantitative studies. by Sarah E. Janek (20570764)

    Published 2025
    “…Despite a high annual HIV incidence, extant literature has found BMSM to engage in fewer sexual risk behaviors than White and Hispanic/Latino men who have sex with men, resulting in a gap between risk behaviors and the inequity of HIV infection. …”
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    Presentation 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

    Published 2025
    “…We evaluate PLM-derived surprisals, the negative log-probabilities of a word or a sequence of words calculated by a PLM given its preceding context, as a continuous and interpretable measure of treatment-induced language change. We found that surprisal scores decreased following structural priming treatment, especially in participants with more severe sentence production impairments. …”
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    Data Sheet 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

    Published 2025
    “…We evaluate PLM-derived surprisals, the negative log-probabilities of a word or a sequence of words calculated by a PLM given its preceding context, as a continuous and interpretable measure of treatment-induced language change. We found that surprisal scores decreased following structural priming treatment, especially in participants with more severe sentence production impairments. …”
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