Reliance on spurious correlations due to simplicity bias is a well-known pitfall of deep learning models.
This issue stems from the statistical nature of deep learning algorithms and their inductive biases at all stages,
including data preprocessing, architectures, and optimization. Therefore, spurious correlations and shortcut learning
are fundamental and common practical problems across all branches of AI. The foundational nature and widespread occurrence
of reliance on spurious correlations and shortcut learning make it an important research topic and a gateway to understanding
how deep models learn patterns and the underlying mechanisms responsible for their effectiveness and generalization. This
workshop aims to address two aspects of this phenomenon: its foundations and potential solutions.
Submission Deadline: 16th February 2025, 11:59 PM (AoE).
The workshop will be held on 28th April, 2025 in Singapore EXPO.
For latest news about the workshop, follow @scslworkshop on X/Twitter.