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Durham University
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By reformulating spatial-temporal reasoning into localized coupled graph aggregation, HSTGFormer significantly enhances 3D human pose estimation accuracy while maintaining computational efficiency.
LLMs can misclassify harmless rephrasings as critical errors, but a new lightweight metric outperforms larger models in clinical significance evaluation.
