1 citations · 3 across the 11 of their papers we have counts for
13 papers
ProMemAgent: Long-Horizon Proactive Assistance with Context-Aware Prospective Memory from Sensory Perceptions
Lilin Xu, Linyang He, Kaiyuan Hou +4
Large language model (LLM) agents are moving beyond reactive responses toward proactive assistance that anticipates user needs without explicit requests. However, existing proactiv…
TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health
Yuang Fan, Lilin Xu, Millie Wu +8
Longitudinal passive sensing enables continuous health prediction, yet models often fail under cross-dataset distribution shifts. Traditional ML overfits cohort-specific artifacts,…
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…
A Large-Scale Multimodal Dataset and Benchmarks for Human Activity Scene Understanding and Reasoning
Siyang Jiang, Mu Yuan, Xiang Ji +12
Multimodal human action recognition (HAR) leverages complementary sensors for activity classification. Beyond recognition, recent advances in large language models (LLMs) enable de…
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…
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…
Exploring the Capabilities of LLMs for IMU-based Fine-grained Human Activity Understanding
Lilin Xu, Kaiyuan Hou, Xiaofan Jiang
Human activity recognition (HAR) using inertial measurement units (IMUs) increasingly leverages large language models (LLMs), yet existing approaches focus on coarse activities lik…
TDBench: A Benchmark for Top-Down Image Understanding with Reliability Analysis of Vision-Language Models
Kaiyuan Hou, Minghui Zhao, Lilin Xu +2
Top-down images play an important role in safety-critical settings such as autonomous navigation and aerial surveillance, where they provide holistic spatial information that front…
SocialMind: LLM-based Proactive AR Social Assistive System with Human-like Perception for In-situ Live Interactions
Bufang Yang, Yunqi Guo, Lilin Xu +4
Social interactions are fundamental to human life. The recent emergence of large language models (LLMs)-based virtual assistants has demonstrated their potential to revolutionize h…
Visualizing the Invisible: A Generative AR System for Intuitive Multi-Modal Sensor Data Presentation
Yunqi Guo, Kaiyuan Hou, Heming Fu +4
Understanding sensor data can be difficult for non-experts because of the complexity and different semantic meanings of sensor modalities. This leads to a need for intuitive and ef…
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…