11 papers
ProAgent: Harnessing On-Demand Sensory Contexts for Proactive LLM Agent Systems in the Wild
Bufang Yang, Lilin Xu, Liekang Zeng +8
Recent studies have begun to explore proactive large language model (LLM) agents that provide unobtrusive assistance by automatically leveraging contextual information, such as in…
ProAssist: Continuous Step-aware Proactive Assistance with Multi-modal Egocentric Perception for Long-horizon Procedural Tasks
Lilin Xu, Bufang Yang, Siyang Jiang +6
Procedural tasks with multiple ordered steps are ubiquitous in daily life. Recent advances in multimodal large language models (MLLMs) have enabled personal assistants that support…
SensorPersona: An LLM-Empowered System for Continual Persona Extraction from Longitudinal Mobile Sensor Streams
Bufang Yang, Lilin Xu, Yixuan Li +3
Personalization is essential for Large Language Model (LLM)-based agents to adapt to users' preferences and improve response quality and task performance. However, most existing ap…
EgoLog: Ego-Centric Fine-Grained Daily Log with Ubiquitous Wearables
Lixing He, Bufang Yang, Di Duan +2
Despite advances in human activity recognition (HAR) with different modalities, a precise, robust, and accurate daily log system is not yet available. Current solutions primarily r…
PerCache: Predictive Hierarchical Cache for RAG Applications on Mobile Devices
Kaiwei Liu, Liekang Zeng, Lilin Xu +2
Retrieval-augmented generation (RAG) has been extensively used as a de facto paradigm in various large language model (LLM)-driven applications on mobile devices, such as mobile as…
DeepFeature: LLM-Empowered Context-aware Feature Generation for Wearable Biosignals
Kaiwei Liu, Yuting He, Bufang Yang +5
Biosignals collected from wearable devices are widely utilized in healthcare applications. Machine learning models used in these applications often rely on features extracted from…