{"total":22,"rows":[{"id":"2112.12591","title":"Black-Box Testing of Deep Neural Networks Through Test Case Diversity","created":"2021-12-20","cited_by_count":18,"area":null},{"id":"2408.03573","title":"AcTracer: Active Testing of Large Language Model via Multi-Stage Sampling","created":"2024-08-07","cited_by_count":17,"area":null},{"id":"2112.00646","title":"Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance","created":"2021-11-30","cited_by_count":16,"area":null},{"id":"2406.07320","title":"A Framework for Efficient Model Evaluation through Stratification, Sampling, and Estimation","created":"2024-06-11","cited_by_count":14,"area":null},{"id":"2106.01258","title":"Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles","created":"2021-06-02","cited_by_count":11,"area":null},{"id":"2303.04878","title":"DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks","created":"2023-03-08","cited_by_count":11,"area":null},{"id":"2207.10942","title":"Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation","created":"2022-07-22","cited_by_count":9,"area":null},{"id":"2109.05720","title":"Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories","created":"2021-09-13","cited_by_count":7,"area":null},{"id":"2103.04333","title":"Measuring Discrimination to Boost Comparative Testing for Multiple Deep Learning Models","created":"2021-03-07","cited_by_count":6,"area":null},{"id":"2206.05480","title":"CodeS: Towards Code Model Generalization Under Distribution Shift","created":"2022-06-11","cited_by_count":6,"area":null},{"id":"2308.01314","title":"Evaluating the Robustness of Test Selection Methods for Deep Neural Networks","created":"2023-07-29","cited_by_count":4,"area":null},{"id":"2303.01295","title":"Iterative Assessment and Improvement of DNN Operational Accuracy","created":"2023-03-02","cited_by_count":3,"area":null},{"id":"2307.11011","title":"Neuron Sensitivity Guided Test Case Selection for Deep Learning Testing","created":"2023-07-20","cited_by_count":3,"area":null},{"id":"2112.02542","title":"Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models","created":"2021-12-05","cited_by_count":2,"area":null},{"id":"2204.04220","title":"Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment","created":"2022-04-08","cited_by_count":2,"area":null},{"id":"2403.19271","title":"DeepSample: DNN sampling-based testing for operational accuracy assessment","created":"2024-03-28","cited_by_count":2,"area":null},{"id":"2204.03994","title":"LaF: Labeling-Free Model Selection for Automated Deep Neural Network Reusing","created":"2022-04-08","cited_by_count":1,"area":null},{"id":"2405.16082","title":"Uncertainty Measurement of Deep Learning System based on the Convex Hull of Training Sets","created":"2024-05-25","cited_by_count":1,"area":null},{"id":"2601.08024","title":"A Highly Efficient Diversity-based Input Selection for DNN Improvement Using VLMs","created":"2026-01-12","cited_by_count":1,"area":null},{"id":"2410.19794","title":"DiffGAN: A Test Generation Approach for Differential Testing of Deep Neural Networks for Image Analysis","created":"2024-10-15","cited_by_count":0,"area":null},{"id":"2509.23961","title":"Learning-Based Testing for Deep Learning: Enhancing Model Robustness with Adversarial Input Prioritization","created":"2025-09-28","cited_by_count":0,"area":null},{"id":"2605.24008","title":"CAFD: Concept-Aware DNN Fault Detection using VLMs","created":"2026-05-19","cited_by_count":0,"area":null}],"next_cursor":null}