325 citations · 606 across the 12 of their papers we have counts for
13 papers
From Memorization to Creation: Evaluating the Cognitive Depth of LLM-Generated Educational Questions
Xiaolong Wang, Zhe Zhao, Song Lai +5
While LLMs show promise in automating educational content creation, their ability to generate questions that stimulate higher-order thinking remains understudied. This work evaluat…
Time Series Analysis for Education: Methods, Applications, and Future Directions
Shengzhong Mao, Chaoli Zhang, Yichi Song +4
Recent advancements in the collection and analysis of sequential educational data have brought time series analysis to a pivotal position in educational research, highlighting its…
A Survey on Diffusion Models for Time Series and Spatio-Temporal Data
Yiyuan Yang, Ming Jin, Haomin Wen +9
Diffusion models have been widely used in time series and spatio-temporal data, enhancing generative, inferential, and downstream capabilities. These models are applied across dive…
Large Language Models for Education: A Survey and Outlook
Shen Wang, Tianlong Xu, Hang Li +5
The advent of Large Language Models (LLMs) has brought in a new era of possibilities in the realm of education. This survey paper summarizes the various technologies of LLMs in edu…
Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook
Ming Jin, Yaxuan Kong, Yuxuan Liang +13
Temporal data, including time series and spatio-temporal data, are pervasive in real-world applications. Generated in massive volumes by physical and virtual sensors, they record d…
Bridging AI and Energy Forecasting: An Autonomous Workflow with Customized Toolkit
Zhixian Wang, Leandro Von Krannichfeldt, Qingsong Wen +4
Energy forecasting is crucial for the power grid, but fundamentally different from general time series analysis: it highly relies on covariates like meteorological factors, and its…
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection
Yiyuan Yang, Chaoli Zhang, Tian Zhou +2
Time series anomaly detection is critical for a wide range of applications. It aims to identify deviant samples from the normal sample distribution in time series. The most fundame…
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects
Kexin Zhang, Qingsong Wen, Chaoli Zhang +8
Self-supervised learning (SSL) has recently achieved impressive performance on various time series tasks. The most prominent advantage of SSL is that it reduces the dependence on l…
DiffLoad: Uncertainty Quantification in Electrical Load Forecasting with the Diffusion Model
Zhixian Wang, Qingsong Wen, Chaoli Zhang +2
Electrical load forecasting plays a crucial role in decision-making for power systems, including unit commitment and economic dispatch. The integration of renewable energy sources…
AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes
Zhiqiang Zhou, Chaoli Zhang, Lingna Ma +6
The existing resource allocation policy for application instances in Kubernetes cannot dynamically adjust according to the requirement of business, which would cause an enormous wa…
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis
Chaoli Zhang, Tian Zhou, Qingsong Wen +1
Time series anomaly detection is a challenging problem due to the complex temporal dependencies and the limited label data. Although some algorithms including both traditional and…
NetRCA: An Effective Network Fault Cause Localization Algorithm
Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang +4
Localizing the root cause of network faults is crucial to network operation and maintenance. However, due to the complicated network architectures and wireless environments, as wel…
Transformers in Time Series: A Survey
Qingsong Wen, Tian Zhou, Chaoli Zhang +4
Transformers have achieved superior performances in many tasks in natural language processing and computer vision, which also triggered great interest in the time series community.…