87 citations · 98 across the 7 of their papers we have counts for
7 papers
DiagChain: A Diagnostic Benchmark for Evaluating LLM Agents on Evidence-Grounded Attack Chain Reconstruction
Xuyang Liu, Yibin Han, Zhenwei Zhang +8
Large Language Model (LLM) agents offer a promising approach to attack chain reconstruction by retrieving and interpreting heterogeneous telemetry to infer ordered attacker actions…
MMTS-BENCH: A Comprehensive Benchmark for Time Series Understanding and Reasoning
Yao Yin, Zhenyu Xiao, Musheng Li +7
Time series data are central to domains such as finance, healthcare, and cloud computing, yet existing benchmarks for evaluating various large language models (LLMs) on temporal ta…
See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers
Jiaxin Zhuang, Leon Yan, Zhenwei Zhang +3
Time series anomaly detection (TSAD) is becoming increasingly vital due to the rapid growth of time series data across various sectors. Anomalies in web service data, for example,…
AnyTaskTune: Advanced Domain-Specific Solutions through Task-Fine-Tuning
Jiaxi Cui, Wentao Zhang, Jing Tang +6
The pervasive deployment of Large Language Models-LLMs in various sectors often neglects the nuanced requirements of individuals and small organizations, who benefit more from mode…
Unravel Anomalies: An End-to-end Seasonal-Trend Decomposition Approach for Time Series Anomaly Detection
Zhenwei Zhang, Ruiqi Wang, Ran Ding +1
Traditional Time-series Anomaly Detection (TAD) methods often struggle with the composite nature of complex time-series data and a diverse array of anomalies. We introduce TADNet,…
SageFormer: Series-Aware Framework for Long-term Multivariate Time Series Forecasting
Zhenwei Zhang, Linghang Meng, Yuantao Gu
In the burgeoning ecosystem of Internet of Things, multivariate time series (MTS) data has become ubiquitous, highlighting the fundamental role of time series forecasting across nu…
Unlocking the Potential of Deep Learning in Peak-Hour Series Forecasting
Zhenwei Zhang, Xin Wang, Jingyuan Xie +2
Unlocking the potential of deep learning in Peak-Hour Series Forecasting (PHSF) remains a critical yet underexplored task in various domains. While state-of-the-art deep learning m…