BITS: Rethinking Fair and Comprehensive Evaluation for Irregular Time Series Forecasting

arXiv:2609.33303 · cs.LG, cs.AI · Submitted 2026-09-27 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-27

Updated: 2026-09-27

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Time Series Forecasting — 51× in this paper · explained in 3 episodes
• Benchmark — 23× in this paper · explained in 2 episodes
• Aggregation — 11× in this paper · explained in 1 episode
• Foundation Model — 10× in this paper · explained in 3 episodes
• Foundation Models — 9× in this paper · explained in 7 episodes
• Benchmarking — 7× in this paper · explained in 3 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Alignment — 6× in this paper · explained in 1 episode
• Transformer — 5× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Hypergraph — 3× in this paper · explained in 2 episodes
• Mean Absolute Percentage Error — 3× in this paper
• Representation Learning — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Change Point Number Difference — 2× in this paper
• Directional Accuracy — 2× in this paper
• Graph Construction — 2× in this paper · explained in 3 episodes
• Information Entropy Ratio — 2× in this paper
• Information Leakage — 2× in this paper · explained in 2 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Symmetric Mean Absolute Percentage Error — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Dynamic Time Warping — 1× in this paper
• Dynamic Time Warping (DTW) — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Modified Symmetric Mean Absolute Percentage Error — 1× in this paper
• Root Mean Squared Error — 1× in this paper
• Time Series Foundation Models (TSFMs) — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Weighted Absolute Percent Error — 1× in this paper
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• Benchmarking with MIMIC-IV, an irregular, spare clinical time series dataset
• Recurrent Neural Networks for Multivariate Time Series with Missing Values
• Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline

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