FusionSense uses server-side fusion learning, filter-out-safe labels, and edge compaction to enable runtime-adaptive multimodal sensing that cuts energy up to 33x while preserving task quality on RGB+Depth data.
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cs.LG 2years
2026 2verdicts
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CARE-ECG unifies ECG representation learning, causal graph-based diagnosis, and counterfactual assessment in an agentic LLM pipeline to improve accuracy and explanation faithfulness.
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FusionSense: Tri-Stage Near-Sensor Learning for Runtime-Adaptive Multimodal Edge Intelligence
FusionSense uses server-side fusion learning, filter-out-safe labels, and edge compaction to enable runtime-adaptive multimodal sensing that cuts energy up to 33x while preserving task quality on RGB+Depth data.
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CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation
CARE-ECG unifies ECG representation learning, causal graph-based diagnosis, and counterfactual assessment in an agentic LLM pipeline to improve accuracy and explanation faithfulness.