1 citations · 2 across the 9 of their papers we have counts for
12 papers
EdgeCraft: Automated Model Crafting for Edge IoT
Genglin Wang, Kaiwei Liu, Liekang Zeng +4
Machine learning (ML) increasingly powers Internet of Things (IoT) applications at the edge. Yet producing a deployable edge ML artifact for a specific scenario requires navigating…
SkillVine: Agent Skill Evolution via Branching Exploration
Kaiwei Liu, Jiqian Dong, Liran Dong +7
Agent skills encapsulate reusable procedural knowledge that enables LLM agents to perform tasks, and they can be improved automatically using trajectories from interactions with th…
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…
PerCache: Predictive Hierarchical Cache for RAG Applications on Mobile Devices
Kaiwei Liu, Liekang Zeng, Lilin Xu +2
Retrieval-augmented generation (RAG) has become a de facto paradigm in various large language model (LLM)-driven applications on mobile devices, such as mobile assistants leveragin…
DeepFeature: LLM-Empowered Context-aware Feature Generation for Wearable Biosignals
Kaiwei Liu, Yuting He, Bufang Yang +6
Biosignals collected from wearable devices are widely utilized in healthcare applications. Machine learning models used in these applications often rely on features extracted from…
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…
Synera: Synergistic LLM Serving across Device and Cloud at Scale
Genglin Wang, Liekang Zeng, Bufang Yang +6
Large Language Models (LLMs) are becoming key components in various mobile operating systems, driving smart applications like interactive chatbots and personal assistants. While br…
An LLM-Empowered Low-Resolution Vision System for On-Device Human Behavior Understanding
Siyang Jiang, Bufang Yang, Lilin Xu +8
The rapid advancements in Large Vision Language Models (LVLMs) offer the potential to surpass conventional labeling by generating richer, more detailed descriptions of on-device hu…
ContextAgent: Context-Aware Proactive LLM Agents with Open-World Sensory Perceptions
Bufang Yang, Lilin Xu, Liekang Zeng +7
Recent advances in Large Language Models (LLMs) have propelled intelligent agents from reactive responses to proactive support. While promising, existing proactive agents either re…
DrHouse: An LLM-empowered Diagnostic Reasoning System through Harnessing Outcomes from Sensor Data and Expert Knowledge
Bufang Yang, Siyang Jiang, Lilin Xu +6
Large language models (LLMs) have the potential to transform digital healthcare, as evidenced by recent advances in LLM-based virtual doctors. However, current approaches rely on p…
VIAssist: Adapting Multi-modal Large Language Models for Users with Visual Impairments
Bufang Yang, Lixing He, Kaiwei Liu +1
Individuals with visual impairments, encompassing both partial and total difficulties in visual perception, are referred to as visually impaired (VI) people. An estimated 2.2 billi…