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Learning Agentic Time Series Forecasting via Trajectory Distillation and Memory-Based Reinforcement Learning
Xiaoyu Tao, Mingyue Cheng, Chuang Jiang +7
Recent agentic time series forecasting (TSF) approaches use large language models (LLMs) to autonomously orchestrate analytical and forecasting tools and reason about temporal patt…
AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning
Xiaoyu Tao, Yuchong Wu, Mingyue Cheng +2
Time series anomaly detection is critical in many real-world applications, where effective solutions must localize anomalous regions and support reliable decision-making under comp…
Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone
Max Sobol Mark, Tian Gao, Georgia Gabriela Sampaio +4
Recent advances in learning decision-making policies can largely be attributed to training expressive policy models, largely via imitation learning. While imitation learning discar…