TS-Arena -- A Live Forecast Pre-Registration Platform
Marcel Meyer, Sascha Kaltenpoth, Henrik Albers, Kevin Zalipski, Oliver M\"uller

TL;DR
TS-Arena is a live forecasting platform that evaluates models on future data with strict pre-registration, preventing data leakage and enabling continuous, real-time benchmarking of time series models.
Contribution
It introduces a novel live benchmarking platform with a pre-registration protocol that assesses models on future data, enhancing evaluation integrity and immediacy.
Findings
Established TSFMs show robust performance over time.
Newcomers can demonstrate immediate competitiveness.
The platform prevents test-set contamination.
Abstract
Time Series Foundation Models (TSFMs) are transforming the field of forecasting. However, evaluating them on historical data is increasingly difficult due to the risks of train-test sample overlaps and temporal overlaps between correlated train and test time series. To address this, we introduce TS-Arena, a live forecasting platform that shifts evaluation from the known past to the unknown future. Building on the concept of continuous benchmarking, TS-Arena evaluates models on future data. Crucially, we introduce a strict forecasting pre-registration protocol: models must submit predictions before the ground-truth data physically exists. This makes test-set contamination impossible by design. The platform relies on a modular microservice architecture that harmonizes and structures data from different sources and orchestrates containerized model submissions. By enforcing a strict…
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