HALo uses smartglasses IMU head orientation to localize conversation partners' acoustic zones, achieving 21% better performance with known partner count, while CoCo classifies partner numbers at 0.74 accuracy using only IMU data.
MAESTRO : Adaptive Sparse Attention and Robust Learning for Multimodal Dynamic Time Series
3 Pith papers cite this work. Polarity classification is still indexing.
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MuViS is a new unified benchmark showing that neither gradient-boosted trees nor deep neural networks hold a universal advantage in multimodal virtual sensing.
SentryFuse delivers modality-aware zero-shot pruning and sparse attention that improves accuracy by 12.7% on average and up to 18% under sensor dropout while cutting memory 28.2% and latency up to 1.63x across multimodal edge models.
citing papers explorer
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Towards Localizing Conversation Partners using Head Motion
HALo uses smartglasses IMU head orientation to localize conversation partners' acoustic zones, achieving 21% better performance with known partner count, while CoCo classifies partner numbers at 0.74 accuracy using only IMU data.
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MuViS: Multimodal Virtual Sensing Benchmark
MuViS is a new unified benchmark showing that neither gradient-boosted trees nor deep neural networks hold a universal advantage in multimodal virtual sensing.
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Modality-Aware Zero-Shot Pruning and Sparse Attention for Efficient Multimodal Edge Inference
SentryFuse delivers modality-aware zero-shot pruning and sparse attention that improves accuracy by 12.7% on average and up to 18% under sensor dropout while cutting memory 28.2% and latency up to 1.63x across multimodal edge models.