SensorPersona uses LLMs for hierarchical reasoning on longitudinal mobile sensor streams to continually extract stable personas, showing up to 31.4% higher recall and 85.7% win rate over baselines on a 20-user dataset.
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Akashic’s MemAttention plus locality-aware placement improves agent task accuracy by up to 10.2 points and throughput by up to 1.21× over prior memory systems across four long-horizon workloads.
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SensorPersona: An LLM-Empowered System for Continual Persona Extraction from Longitudinal Mobile Sensor Streams
SensorPersona uses LLMs for hierarchical reasoning on longitudinal mobile sensor streams to continually extract stable personas, showing up to 31.4% higher recall and 85.7% win rate over baselines on a 20-user dataset.
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Akashic: A Low-Overhead LLM Inference Service with MemAttention
Akashic’s MemAttention plus locality-aware placement improves agent task accuracy by up to 10.2 points and throughput by up to 1.21× over prior memory systems across four long-horizon workloads.