{"total":19,"rows":[{"id":"2302.05442","title":"Scaling Vision Transformers to 22 Billion Parameters","created":"2023-02-10","cited_by_count":694,"area":null},{"id":"2209.09858","title":"Extremely Simple Activation Shaping for Out-of-Distribution Detection","created":"2022-09-20","cited_by_count":212,"area":null},{"id":"2207.07068","title":"Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey","created":"2022-07-14","cited_by_count":125,"area":null},{"id":"2207.10384","title":"Detecting Shortcut Learning for Fair Medical AI using Shortcut Testing","created":"2022-07-21","cited_by_count":52,"area":null},{"id":"2206.04664","title":"On Data Scaling in Masked Image Modeling","created":"2022-06-09","cited_by_count":46,"area":null},{"id":"2202.01034","title":"Diagnosing failures of fairness transfer across distribution shift in real-world medical settings","created":"2022-02-02","cited_by_count":45,"area":null},{"id":"2403.04547","title":"CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?","created":"2024-03-07","cited_by_count":35,"area":null},{"id":"2209.07312","title":"Multicalibrated Regression for Downstream Fairness","created":"2022-09-15","cited_by_count":14,"area":null},{"id":"2204.04440","title":"Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks","created":"2022-04-09","cited_by_count":10,"area":null},{"id":"2205.15860","title":"A Reduction to Binary Approach for Debiasing Multiclass Datasets","created":"2022-05-31","cited_by_count":9,"area":null},{"id":"2406.17433","title":"Mind the Graph When Balancing Data for Fairness or Robustness","created":"2024-06-25","cited_by_count":9,"area":null},{"id":"2301.13803","title":"Fairness-aware Vision Transformer via Debiased Self-Attention","created":"2023-01-31","cited_by_count":6,"area":null},{"id":"2201.12947","title":"Fair Wrapping for Black-box Predictions","created":"2022-01-31","cited_by_count":4,"area":null},{"id":"2206.14853","title":"Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale","created":"2022-06-29","cited_by_count":4,"area":null},{"id":"2403.18196","title":"Looking Beyond What You See: An Empirical Analysis on Subgroup Intersectional Fairness for Multi-label Chest X-ray Classification Using Social Determinants of Racial Health Inequities","created":"2024-03-27","cited_by_count":3,"area":null},{"id":"2211.10193","title":"Layer-Stack Temperature Scaling","created":"2022-11-18","cited_by_count":2,"area":null},{"id":"2402.17106","title":"Achievable Fairness on Your Data With Utility Guarantees","created":"2024-02-27","cited_by_count":2,"area":null},{"id":"2402.10551","title":"Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information","created":"2024-02-16","cited_by_count":0,"area":null},{"id":"2502.11031","title":"A Critical Review of Predominant Bias in Neural Networks","created":"2025-02-16","cited_by_count":0,"area":null}],"next_cursor":null}