{"total":30,"rows":[{"id":"2405.20469","title":"Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images","created":"2024-05-30","cited_by_count":41,"area":null},{"id":"2110.00603","title":"Algorithm Fairness in AI for Medicine and Healthcare","created":"2021-10-01","cited_by_count":21,"area":null},{"id":"2405.08209","title":"Who's in and who's out? A case study of multimodal CLIP-filtering in DataComp","created":"2024-05-13","cited_by_count":15,"area":null},{"id":"2408.04154","title":"The Data Addition Dilemma","created":"2024-08-08","cited_by_count":15,"area":null},{"id":"2201.08186","title":"Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations","created":"2022-01-20","cited_by_count":14,"area":null},{"id":"2405.20456","title":"Scaling Laws for the Value of Individual Data Points in Machine Learning","created":"2024-05-30","cited_by_count":10,"area":null},{"id":"2401.09432","title":"RoleCraft-GLM: Advancing Personalized Role-Playing in Large Language Models","created":"2023-12-17","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":"2112.00818","title":"Models of fairness in federated learning","created":"2021-12-01","cited_by_count":8,"area":null},{"id":"2309.01837","title":"Delegating Data Collection in Decentralized Machine Learning","created":"2023-09-04","cited_by_count":8,"area":null},{"id":"2305.02995","title":"Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations","created":"2023-05-04","cited_by_count":7,"area":null},{"id":"2410.03020","title":"On Logical Extrapolation for Mazes with Recurrent and Implicit Networks","created":"2024-10-03","cited_by_count":7,"area":null},{"id":"2510.24626","title":"Relative Scaling Laws for LLMs","created":"2025-10-28","cited_by_count":6,"area":null},{"id":"2501.12535","title":"How Does the Spatial Distribution of Pre-training Data Affect Geospatial Foundation Models?","created":"2025-01-21","cited_by_count":5,"area":null},{"id":"2209.05274","title":"Fairness in Forecasting of Observations of Linear Dynamical Systems","created":"2022-09-12","cited_by_count":4,"area":null},{"id":"2211.06348","title":"Striving for data-model efficiency: Identifying data externalities on group performance","created":"2022-11-11","cited_by_count":4,"area":null},{"id":"2409.03734","title":"Safety vs. Performance: How Multi-Objective Learning Reduces Barriers to Market Entry","created":"2024-09-05","cited_by_count":4,"area":null},{"id":"2204.06664","title":"Achieving Representative Data via Convex Hull Feasibility Sampling Algorithms","created":"2022-04-13","cited_by_count":2,"area":null},{"id":"2302.05807","title":"Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play","created":"2023-02-11","cited_by_count":2,"area":null},{"id":"2407.08689","title":"Operationalizing the Blueprint for an AI Bill of Rights: Recommendations for Practitioners, Researchers, and Policy Makers","created":"2024-07-11","cited_by_count":2,"area":null},{"id":"2501.14551","title":"Fairness of Deep Ensembles: On the interplay between per-group task difficulty and under-representation","created":"2025-01-24","cited_by_count":2,"area":null},{"id":"2509.03749","title":"Mapping on a Budget: Optimizing Spatial Data Collection for ML","created":"2025-09-03","cited_by_count":2,"area":null},{"id":"2501.06826","title":"Aligning NLP Models with Target Population Perspectives using PAIR: Population-Aligned Instance Replication","created":"2025-01-12","cited_by_count":1,"area":null},{"id":"2507.14725","title":"GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning","created":"2025-07-19","cited_by_count":1,"area":null},{"id":"2604.21104","title":"Pretrain Where? Investigating How Pretraining Data Diversity Impacts Geospatial Foundation Model Performance","created":"2026-04-22","cited_by_count":1,"area":null},{"id":"2510.15970","title":"Predict Training Data Quality via Its Geometry in Metric Space","created":"2025-10-12","cited_by_count":0,"area":null},{"id":"2512.09496","title":"Representation Invariance and Allocation: When Subgroup Balance Matters","created":"2025-12-10","cited_by_count":0,"area":null},{"id":"2602.09340","title":"Measuring Dataset Diversity from a Geometric Perspective","created":"2026-02-10","cited_by_count":0,"area":null},{"id":"2603.22339","title":"Problems with Chinchilla Approach 2: Systematic Biases in IsoFLOP Parabola Fits","created":"2026-03-21","cited_by_count":0,"area":null},{"id":"2604.03478","title":"Investigating Data Interventions for Subgroup Fairness: An ICU Case Study","created":"2026-04-03","cited_by_count":0,"area":null}],"next_cursor":null}