[ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
Search lots of data sets for spurious correlations
Implementation of the EMNLP 2020 paper "Counterfactual Generator: A Weakly-Supervised Method for Named Entity Recognition".
Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet
[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization
[Nature Medicine] The Limits of Fair Medical Imaging AI In Real-World Generalization
Official Repository for Spurious Memorization - Nature Communications 2025
Understanding Rare Spurious Correlations in Neural Network
[ICCV25] TD-DETR: The Devil is in the Spurious Correlations: Boosting Moment Retrieval with Dynamic Learning
Carloni, G., Tsaftaris, S. A., & Colantonio, S. (2024). CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning @ MICCAI 2024 UNSURE Workshop
Which Shortcut Solution Do Question Answering Models Prefer to Learn? (AAAI2023)
The official repository for "Training Debiased Subnetworks with Contrastive Weight Pruning"
This repository contains the code for the paper "Disentangling representations of retinal images with generative models".
How to detect spurious and hidden correlations in R using linear models
VISION is a framework for robust and interpretable code vulnerability detection using counterfactual data augmentation. It leverages GNNs, LLM-generated counterfactuals, and graph-based explainability to mitigate spurious correlations and improve generalization on real-world vulnerabilities (CWE-20).
Spurious correlation simulator
Official code of our paper "Autoencoder based approach for the mitigation of spurious correlations on YOLOv5"
Codebase for "Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations" (NeurIPS 25 Spotlight)
Reproduction code + artifacts for "When Do Deep Ensembles Improve Robustness to Spurious Correlations?" (TU Delft, 2026).
Mitigating Spurious Correlations for Self-supervised Recommendation
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