AI RESEARCH

Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting

arXiv CS.AI

ArXi:2509.23074v3 Announce Type: replace-cross In the era of increasingly complex AI models for time series forecasting, progress is often measured by marginal improvements on benchmark leaderboards. However, this approach suffers from a fundamental flaw: standard evaluation metrics conflate a model's performance with the data's intrinsic unpredictability. To address this pressing challenge, we