1 citations · 3 across the 11 of their papers we have counts for
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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…