AnyMo uses physics-grounded IMU simulation over dense body placements, graph encoder pre-training, and LLM alignment to enable setup-agnostic motion modeling, reporting gains on zero-shot HAR, retrieval, and captioning across datasets.
Enabling sustainability and energy awareness in schools based on iot and real-world data,
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Users entangle their lived experiences with AI predictions in menstrual tracking apps, leading to self-fulfilling prophecies, limited critical awareness from UI, and isolation for non-normative users.
Methodology for IoT-based energy savings in schools reporting 20% reductions from the GAIA project.
citing papers explorer
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AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild
AnyMo uses physics-grounded IMU simulation over dense body placements, graph encoder pre-training, and LLM alignment to enable setup-agnostic motion modeling, reporting gains on zero-shot HAR, retrieval, and captioning across datasets.
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"It became a self-fulfilling prophecy": How Lived Experiences are Entangled with AI Predictions in Menstrual Cycle Tracking Apps
Users entangle their lived experiences with AI predictions in menstrual tracking apps, leading to self-fulfilling prophecies, limited critical awareness from UI, and isolation for non-normative users.
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A Methodology for Saving Energy in Educational Buildings Using an IoT Infrastructure
Methodology for IoT-based energy savings in schools reporting 20% reductions from the GAIA project.