Search Results for author:
Found 4 papers, 4 papers with code
ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning
To the best of our knowledge, ChatTS is the first TS-MLLM that takes multivariate time series as input for understanding and reasoning, which is fine-tuned exclusively on synthetic datasets.
Generic and Robust Root Cause Localization for Multi-Dimensional Data in Online Service Systems
Such attribute combinations are substantial clues to the underlying root causes and thus are called root causes of multidimensional data.
Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention Recognition
Fault diagnosis is critical in many domains, as faults may lead to safety threats or economic losses.
Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e. g., Page Views, number of online users, and number of orders) of its Web applications, to accurately detect anomalies and trigger timely troubleshooting/mitigation.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
