75 citations · 83 across the 9 of their papers we have counts for
10 papers
Dynamical Parameters: An Interpretability Framework for Time-Series Foundation Models
Kang Yang, Gaofeng Dong, Liying Han +1
This work studies a central gap in interpreting time-series foundation models (TSFMs): a dynamical property may be accessible in a hidden state even when the forecast fails to resp…
Towards Causally Interpretable Wi-Fi CSI-Based Human Activity Recognition with Discrete Latent Compression and LTL Rule Extraction
Luca Cotti, Luca Lavazza, Marco Cominelli +10
We address Human Activity Recognition (HAR) utilizing Wi-Fi Channel State Information (CSI) under the joint requirements of causal interpretability, symbolic controllability, and d…
Can Time-Series Foundation Models Perform Building Energy Management Tasks?
Ozan Baris Mulayim, Pengrui Quan, Liying Han +4
Building energy management (BEM) tasks require processing and learning from a variety of time-series data. Existing solutions rely on bespoke task- and data-specific models to perf…
Toward Foundation Models for Online Complex Event Detection in CPS-IoT: A Case Study
Liying Han, Gaofeng Dong, Xiaomin Ouyang +3
Complex events (CEs) play a crucial role in CPS-IoT applications, enabling high-level decision-making in domains such as smart monitoring and autonomous systems. However, most exis…
Scaling Online Complex Event Detection with Synthetic Supervision and Mamba-Based Neural Algorithmic Reasoning
Liying Han, Gaofeng Dong, Xiaomin Ouyang +4
Modern machine learning models excel at detecting individual actions, sounds, or scene attributes from short, localized observations. However, many real-world tasks, such as in sma…
GSRF: Complex-Valued 3D Gaussian Splatting for Efficient Radio-Frequency Data Synthesis
Kang Yang, Gaofeng Dong, Sijie Ji +2
Synthesizing radio-frequency (RF) data given the transmitter and receiver positions, e.g., received signal strength indicator (RSSI), is critical for wireless networking and sensin…
AutoLife: Automatic Life Journaling with Smartphones and LLMs
Huatao Xu, Panrong Tong, Mo Li +1
This paper introduces a novel mobile sensing application - life journaling - designed to generate semantic descriptions of users' daily lives. We present AutoLife, an automatic lif…
Artificial Intelligence of Things: A Survey
Shakhrul Iman Siam, Hyunho Ahn, Li Liu +7
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In t…
An Empirical Evaluation of Neural and Neuro-symbolic Approaches to Real-time Multimodal Complex Event Detection
Liying Han, Mani B. Srivastava
Robots and autonomous systems require an understanding of complex events (CEs) from sensor data to interact with their environments and humans effectively. Traditional end-to-end n…
Penetrative AI: Making LLMs Comprehend the Physical World
Huatao Xu, Liying Han, Qirui Yang +2
Recent developments in Large Language Models (LLMs) have demonstrated their remarkable capabilities across a range of tasks. Questions, however, persist about the nature of LLMs an…