Evaluation Choices Decide the Forecasting Leaderboard: Evidence from a Production Marketplace Panel

arXiv:2609.27867 · cs.LG, stat.AP, stat.ME · Submitted 2026-08-20 · Read on arXiv

cs.LG, stat.AP, stat.ME

Submitted: 2026-08-20

Updated: 2026-08-20

Terminology

• Benchmark — 16× in this paper · explained in 2 episodes
• Accuracy — 13× in this paper · explained in 1 episode
• Foundation Model — 12× in this paper · explained in 3 episodes
• Foundation Models — 9× in this paper · explained in 7 episodes
• Aggregation — 7× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• Time Series Forecasting — 3× in this paper · explained in 3 episodes
• Calibration Failure — 2× in this paper · explained in 2 episodes
• Conformal Prediction — 2× in this paper · explained in 5 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Abstention — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
• A Look at the Evaluation Setup of the M5 Forecasting Competition
• TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks