{"total":24,"rows":[{"id":"2310.19035","title":"Does Invariant Graph Learning via Environment Augmentation Learn Invariance?","created":"2023-10-29","cited_by_count":42,"area":null},{"id":"2409.02772","title":"Unifying Causal Representation Learning with the Invariance Principle","created":"2024-09-04","cited_by_count":31,"area":null},{"id":"2412.07684","title":"The Pitfalls of Memorization: When Memorization Hurts Generalization","created":"2024-12-10","cited_by_count":19,"area":null},{"id":"2410.06303","title":"Compositional Risk Minimization","created":"2024-10-08","cited_by_count":13,"area":null},{"id":"2402.13368","title":"Unsupervised Concept Discovery Mitigates Spurious Correlations","created":"2024-02-20","cited_by_count":11,"area":null},{"id":"2404.05579","title":"DRoP: Distributionally Robust Data Pruning","created":"2024-04-08","cited_by_count":7,"area":null},{"id":"2503.18258","title":"Severing Spurious Correlations with Data Pruning","created":"2025-03-24","cited_by_count":7,"area":null},{"id":"2406.16846","title":"Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection","created":"2024-06-24","cited_by_count":5,"area":null},{"id":"2510.18052","title":"Measure-Theoretic Anti-Causal Representation Learning","created":"2025-10-16","cited_by_count":4,"area":null},{"id":"2410.14315","title":"Optimizing importance weighting in the presence of sub-population shifts","created":"2024-10-18","cited_by_count":3,"area":null},{"id":"2410.17358","title":"FairLoRA: Unpacking Bias Mitigation in Vision Models with Fairness-Driven Low-Rank Adaptation","created":"2024-10-22","cited_by_count":3,"area":null},{"id":"2505.21363","title":"Subgroups Matter for Robust Bias Mitigation","created":"2025-05-27","cited_by_count":2,"area":null},{"id":"2411.15272","title":"Curriculum-enhanced GroupDRO: Challenging the Norm of Avoiding Curriculum Learning in Subpopulation Shift Setups","created":"2024-11-22","cited_by_count":1,"area":null},{"id":"2504.17314","title":"Class-Conditional Distribution Balancing for Group Robust Classification","created":"2025-04-24","cited_by_count":1,"area":null},{"id":"2505.06831","title":"Fine-Grained Class-Conditional Distribution Balancing for Debiased Learning","created":"2025-05-11","cited_by_count":1,"area":null},{"id":"2606.24161","title":"Dual-Branch Cross-Projection Debiasing through Diffusion-based Disentanglement","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2610.00968","title":"Structure-agnostic Causal Representation Learning","created":"2026-10-01","cited_by_count":1,"area":null},{"id":"2403.09869","title":"Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors","created":"2024-03-14","cited_by_count":0,"area":null},{"id":"2510.06982","title":"Revisiting Mixout: An Overlooked Path to Robust Finetuning","created":"2025-10-08","cited_by_count":0,"area":null},{"id":"2601.22944","title":"Environment-Conditioned Tail Reweighting for Invariant Learning under Mixed Shifts","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2605.28780","title":"Bias Leaves a Gradient Trail: Label-Free Bias Identification via Gradient Probes on Concept Decompositions","created":"2026-05-27","cited_by_count":0,"area":null},{"id":"2606.23609","title":"Discovering Latent Groups for Robust Classification","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2608.13190","title":"ProME: Prototype-Margin Environments with Repair-Aware Selection for Group-Robust Learning","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2609.35541","title":"Learning the Robustness Mechanism with Bilevel Optimization","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}