Showing 1 - 20 results of 200,603 for search '(((( i large increases ) OR ( _ ((greater decrease) OR (_ decrease)) ))) OR ( ai large increases ))', query time: 0.77s Refine Results
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    Normalized synergy increased with greater recurrence and decreased with greater feedback. by Samantha P. Sherrill (11114128)

    Published 2021
    “…(C) Curves representing columns shown in A, plotted with errorbars computed across networks, show that synergy decreased as the number of feedback edges increased. …”
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    Receiver entropy decreased with greater recurrence and increased with greater feedback. by Samantha P. Sherrill (11114128)

    Published 2021
    “…<p>(A) Mean receiver entropy decreased with the number of recurrent edges and increased with the number of feedback edges in motifs. …”
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    AI-Enhanced Methods in Autonomous Systems: Large Language Models, DL Techniques, and Optimization Algorithms by I. de Zarza (17378452)

    Published 2024
    “…<p dir="ltr">Presentation for PhD thesis:</p><p dir="ltr">AI-Enhanced Methods in Autonomous Systems: Large Language Models, DL Techniques, and Optimization Algorithms https://doi.org/10.4995/Thesis/10251/202201</p><p dir="ltr">Abstract:</p><p dir="ltr">The proliferation of autonomous systems, and their increasing integration with day-to-day human life, have opened new frontiers of research and development. …”
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    TITAN decreaser diatom heatmap. by Brent J. Bellinger (21156150)

    Published 2025
    “…., <i>z-</i>) diatom taxa (y-axis) to at least one of the five stressors, in decreasing order of number of stressor responses. Blue-orange scale corresponds to the <i>z</i> score that indicates the magnitude of response to a stressor.…”
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    Identification and Description of Emotions by Current Large Language Models - Dataset by Suketu Patel (17748162)

    Published 2024
    “…However, recent advancements in large language models (LLMs) challenge this notion by demonstrating an increased capacity for understanding and generating human-like text. …”
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    The number of expected vaccinations decreases with the expected vaccination time, whereas the peak of infections increases. by Simon K. Schnyder (16632244)

    Published 2023
    “…Particularly high infection peaks are expected when the vaccination is certain to arrive outside of the expected duration of the epidemic, i.e. for large 〈<i>t</i><sub><i>v</i></sub>〉 and large <i>n</i>.…”
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    Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

    Published 2025
    “…CVLT-II ICC = 0.992; SDMT ICC = 1.000; BVMT-R ICC = 0.822–853), with minimal scoring discrepancies per test (CVLT = 1.05, SDMT = 0.05, BVMT-<i>R</i> = 1.05–1.19). …”
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    Strengthening assessment integrity in the era of generative AI: evidence from a large-scale study by Liz Hardie (22277602)

    Published 2025
    “…This large-scale empirical study at a UK university, based on 590 student and 354 AI-generated answers, provides evidence on markers’ ability to detect the GenAI scripts and whether some assessment types are more robust than others against GenAI misuse. …”
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