AnyMo pre-trains a graph encoder on physics-simulated multi-placement IMU data and aligns full-body motion tokens with LLMs to enable zero-shot activity recognition, retrieval, and captioning across unseen datasets and setups.
Enabling sustainability and energy awareness in schools based on iot and real-world data
4 Pith papers cite this work. Polarity classification is still indexing.
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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.
Simulations indicate that a three-sensor quantum magnetometer array on a drone, combined with Bayesian active sampling and Gaussian process regression, can recover magnetic signatures of steel-reinforced rubble from ~1 m altitude in the sub-pT to sub-nT range after roughly 100 samples.
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 pre-trains a graph encoder on physics-simulated multi-placement IMU data and aligns full-body motion tokens with LLMs to enable zero-shot activity recognition, retrieval, and captioning across unseen datasets and setups.
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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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From Rubble Simulation to Active Magnetic Mapping: Quantum Sensing for Disaster Response
Simulations indicate that a three-sensor quantum magnetometer array on a drone, combined with Bayesian active sampling and Gaussian process regression, can recover magnetic signatures of steel-reinforced rubble from ~1 m altitude in the sub-pT to sub-nT range after roughly 100 samples.
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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.