MAEPose is a masked autoencoder that learns spatiotemporal representations from unlabeled mmWave radar videos to estimate human poses, outperforming baselines by up to 22.1% in MPJPE.
1988.Statistical Power Analysis for the Behavioral Sciences(2nd ed.)
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Adding interprocedural context from callers or callees enables LLMs to detect vulnerabilities more effectively, with Gemini 3 Flash achieving F1 scores of at least 0.978 for C at low cost and Claude Haiku 4.5 excelling at explanations.
Task type dominates AI coding agent PR acceptance rates, with documentation at 82.1% versus 66.1% for new features, and no single agent best across all categories.
citing papers explorer
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MAEPose: Self-Supervised Spatiotemporal Learning for Human Pose Estimation on mmWave Video
MAEPose is a masked autoencoder that learns spatiotemporal representations from unlabeled mmWave radar videos to estimate human poses, outperforming baselines by up to 22.1% in MPJPE.
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Vulnerability Detection with Interprocedural Context in Multiple Languages: Assessing Effectiveness and Cost of Modern LLMs
Adding interprocedural context from callers or callees enables LLMs to detect vulnerabilities more effectively, with Gemini 3 Flash achieving F1 scores of at least 0.978 for C at low cost and Claude Haiku 4.5 excelling at explanations.
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Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance
Task type dominates AI coding agent PR acceptance rates, with documentation at 82.1% versus 66.1% for new features, and no single agent best across all categories.