arXiv Artificial Intelligence

Gradient-based Model Shortcut Detection for Time Series Classification

4 days ago 07.09.2026 07:00 👁 1 views
Gradient-based Model Shortcut Detection for Time Series Classification

Quick summary

arXiv:2510.10075v2 Announce Type: replace-cross Abstract: Deep learning models have attracted lots of research attention in time series classification (TSC) task in the past two decades. Recently, deep neural networks (DNN) have surpassed classical distance-based methods and achieved state-of-the-art performance. Despite their promising performance, deep neural networks (DNNs) have been shown to rely on spurious correlations present in the training data, which can hinder generalization. For instance, a model might incorrectly associate the presence of grass with the label ``cat" if the trainin

Key takeaways

  • arXiv:2510.10075v2 Announce Type: replace-cross Abstract: Deep learning models have attracted lots of research attention in time series classification (TSC) task in the past two decades.
  • Recently, deep neural networks (DNN) have surpassed classical distance-based methods and achieved state-of-the-art performance.
  • Despite their promising performance, deep neural networks (DNNs) have been shown to rely on spurious correlations present in the training data, which can hinder generalization.

Why it matters

This model development creates a new option for users and a new testing obligation for developers. A fixed evaluation set comparing quality, cost and failure behavior is more useful than launch claims.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗