Are Transformers Effective for Time Series Forecasting?

Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task. We hope this surprising finding opens up new research directions for the LTSF task.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 Despite the growing performance over the past few years, we question the validity of this line of research in this work.
• 2 Specifically, Transformers is arguably the most successful solution to extract the semantic correlations among the elements in a long sequence.
• 3 However, in time series modeling, we are to extract the temporal relations in an ordered set of continuous points.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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