Retrieval-Guided Structured Reasoning and Interpretable Representation Learning for Large-Scale Video–Language Models

The evaluation of 3D forms in VR requires continuous process level computation, whereas traditional art training systems retain the final art and subjective scores. This paper presents a VR spatial-sketching platform, which integrates 60 Hz head-mount display posture, dual controller trajectory, stroke event, coordinate registration, state awareness filtering, multi-view coverage estimation, and geometric feature extraction. The trajectory of the algorithm is based on a three sample adaptive window, a low speed threshold of 0.03 m/s, a break point of 120 ms, and a break point of 80 mm. The feedback is updated every 2 s based on viewpoint-coverage entropy, the content ratio error, the center offset, and the interruption cost. A 12-week quasi-experiment involved 216 students, 1 296 works, 7 776 orthographic images, and approximately 7.2 million interaction records. The results of the ablation were 4.9 mm, the turning retention rate was 95.1%, the invalid trajectory was 93.6%, the error was 8.9%, and the delay was 42.6 ms. The results of the experiment were 85.4 ± 5.8 and 79.7 ± 6.4 in the control group, which confirmed the accuracy, continuity, interpretation, and adaptability of VR assessment.