{"total":31,"rows":[{"id":"2210.11369","title":"On Feature Learning in the Presence of Spurious Correlations","created":"2022-10-20","cited_by_count":145,"area":null},{"id":"2212.10445","title":"Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization","created":"2022-12-20","cited_by_count":97,"area":null},{"id":"2212.04825","title":"A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others","created":"2022-12-09","cited_by_count":85,"area":null},{"id":"2207.09944","title":"Probable Domain Generalization via Quantile Risk Minimization","created":"2022-07-20","cited_by_count":66,"area":null},{"id":"2309.08534","title":"Towards Last-layer Retraining for Group Robustness with Fewer Annotations","created":"2023-09-15","cited_by_count":54,"area":null},{"id":"2206.07766","title":"Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization","created":"2022-06-15","cited_by_count":38,"area":null},{"id":"2304.11327","title":"Understanding and Improving Feature Learning for Out-of-Distribution Generalization","created":"2023-04-22","cited_by_count":35,"area":null},{"id":"2211.02291","title":"SelecMix: Debiased Learning by Contradicting-pair Sampling","created":"2022-11-04","cited_by_count":29,"area":null},{"id":"2309.16748","title":"Discovering environments with XRM","created":"2023-09-28","cited_by_count":26,"area":null},{"id":"2309.17230","title":"Spurious Feature Diversification Improves Out-of-distribution Generalization","created":"2023-09-29","cited_by_count":26,"area":null},{"id":"2206.15369","title":"No Reason for No Supervision: Improved Generalization in Supervised Models","created":"2022-06-30","cited_by_count":23,"area":null},{"id":"2205.15704","title":"Mitigating Dataset Bias by Using Per-sample Gradient","created":"2022-05-31","cited_by_count":22,"area":null},{"id":"2307.09933","title":"Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features","created":"2023-07-19","cited_by_count":21,"area":null},{"id":"2210.01302","title":"Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation","created":"2022-10-04","cited_by_count":18,"area":null},{"id":"2212.07346","title":"Learning useful representations for shifting tasks and distributions","created":"2022-12-14","cited_by_count":14,"area":null},{"id":"2410.11397","title":"FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection","created":"2024-10-15","cited_by_count":14,"area":null},{"id":"2310.06161","title":"Mitigating Simplicity Bias in Deep Learning for Improved OOD Generalization and Robustness","created":"2023-10-09","cited_by_count":7,"area":null},{"id":"2210.13533","title":"Sufficient Invariant Learning for Distribution Shift","created":"2022-10-24","cited_by_count":6,"area":null},{"id":"2211.15724","title":"Malign Overfitting: Interpolation Can Provably Preclude Invariance","created":"2022-11-28","cited_by_count":6,"area":null},{"id":"2310.06670","title":"Domain Generalization by Rejecting Extreme Augmentations","created":"2023-10-10","cited_by_count":5,"area":null},{"id":"2302.04132","title":"Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection","created":"2023-02-08","cited_by_count":4,"area":null},{"id":"2308.16274","title":"Learning Diverse Features in Vision Transformers for Improved Generalization","created":"2023-08-30","cited_by_count":4,"area":null},{"id":"2502.05098","title":"TIF: Learning Temporal Invariance in Android Malware Detectors","created":"2025-02-07","cited_by_count":4,"area":null},{"id":"2210.01360","title":"Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in Neural Networks","created":"2022-10-04","cited_by_count":3,"area":null},{"id":"2403.00946","title":"Fine-tuning with Very Large Dropout","created":"2024-03-01","cited_by_count":3,"area":null},{"id":"2506.11347","title":"Improving Group Robustness on Spurious Correlation via Evidential Alignment","created":"2025-06-12","cited_by_count":3,"area":null},{"id":"2509.24332","title":"Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning","created":"2025-09-29","cited_by_count":2,"area":null},{"id":"2212.01189","title":"Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels","created":"2022-12-01","cited_by_count":1,"area":null},{"id":"2506.18221","title":"These Are Not All the Features You Are Looking For: A Fundamental Bottleneck in Supervised Pretraining","created":"2025-06-23","cited_by_count":1,"area":null},{"id":"2407.01749","title":"Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments","created":"2024-07-01","cited_by_count":0,"area":null},{"id":"2603.25083","title":"Learning domain-invariant features through channel-level sparsification for Out-Of Distribution Generalization","created":"2026-03-26","cited_by_count":0,"area":null}],"next_cursor":null}