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<br> To reply this RQ, we evaluate our models on student submissions from a CS1 course. We additional show that the smaller, value-efficient variant (GPT-4o-mini) achieves results on par with state-of-the-art (GPT-4o) after positive-tuning, creating promising implications for smaller models for actual-time grading. Furthermore, these models are skilled and tested on datasets comparable to UCF-101 (Soomro et al., 2012) and Kinetics-400 (Kay et al., 2017), which contain lengthy duration movies and a wide range of actions. If the movements are incorrect, the suggestions supplies steering on tips on how to appropriate them to ensure proper execution of the exercise. The output contains an assessment of exercise high quality and textual feedback on the performed movements. The results of that is then handed on to the feedback creation. Future work will focus on accumulating and annotating rehabilitation exercise datasets with ground-reality feedback and leveraging this data to fantastic-tune pre-trained LLMs, enhancing their efficiency and reliability in exercise quality assessment and feedback generation.<br>
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