SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms

ArXi:2603.04873v2 Announce Type: replace Accurate time series forecasting underpins decision-making across domains, yet conventional ML development suffers from data scarcity in new deployments, poor adaptability under distribution shift, and diminishing returns from manual iteration. We propose Self-Evolving Agent for Time Series Algorithms (SEA-TS), a framework that autonomously generates, validates, and optimizes forecasting code via an iterative self-evolution loop. Our framework