Dan Pei

AutoDA-Timeseries: Automated Data Augmentation for Time Series

Thinking with Time Series: Interleaved Deep Thinking for Enhanced Time Series Reasoning

Robust Time Series Forecasting via Basis-Aligned Sampling in Decycled Residual Space

Frequency Decomposition and Enhancement for Time Series Generation Using Diffusion Models

TimeSense: Making Large Language Models Proficient in Time‑Series Analysis

OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures?

KAN-AD: Time Series Anomaly Detection with Kolmogorov–Arnold Networks

CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations

OpsEval: A Comprehensive Benchmark Suite for Evaluating Large Language Models’ Capability in IT Operations Domain

Dealing with Frequency Collapse in Time Series Embeddings by Post-Embedding reMapping

Flow-of-Action: SOP Enhanced LLM-Based Multi-Agent System for Root Cause Analysis