8 papers
TS-Skill: A Benchmark for Evaluating Analytical Skills in Time-Series Question Answering
Liying Han, Kang Yang, Oliver Wang +9
Large language models (LLMs) and time-series language models (TSLMs) are increasingly applied to time-series question answering (TSQA). Unlike text-only QA, TSQA requires models to…
Preliminary Insights in Chronos Frequency Data Understanding and Reconstruction
Alessandro Pagani, Marco Cominelli, Liying Han +11
This paper presents a preliminary analysis of the ability of Chronos foundation model to process and internally represent frequency domain information. Foundation models that proce…
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…
Benchmarking Spatiotemporal Reasoning in LLMs and Reasoning Models: Capabilities and Challenges
Pengrui Quan, Brian Wang, Kang Yang +2
Spatiotemporal reasoning plays a key role in Cyber-Physical Systems (CPS). Despite advances in Large Language Models (LLMs) and Large Reasoning Models (LRMs), their capacity to rea…
NAROCE: A Neural Algorithmic Reasoner Framework for Online Complex Event Detection
Liying Han, Gaofeng Dong, Xiaomin Ouyang +3
Modern machine learning models excel at detecting individual actions, objects, or scene attributes from short, local observations. However, many real-world tasks, such as in smart…
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…