{"total":44,"rows":[{"id":"2409.00265","title":"Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction","created":"2024-08-30","cited_by_count":46,"area":null},{"id":"2311.00750","title":"Are These the Same Apple? Comparing Images Based on Object Intrinsics","created":"2023-11-01","cited_by_count":19,"area":null},{"id":"2406.17536","title":"MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions","created":"2024-06-25","cited_by_count":17,"area":null},{"id":"2203.09475","title":"CaRTS: Causality-driven Robot Tool Segmentation from Vision and Kinematics Data","created":"2022-03-15","cited_by_count":16,"area":null},{"id":"2407.06992","title":"Robust Neural Information Retrieval: An Adversarial and Out-of-distribution Perspective","created":"2024-07-09","cited_by_count":15,"area":null},{"id":"2309.05192","title":"Towards Viewpoint Robustness in Bird's Eye View Segmentation","created":"2023-09-11","cited_by_count":13,"area":null},{"id":"2210.03102","title":"Ambiguous Images With Human Judgments for Robust Visual Event Classification","created":"2022-10-06","cited_by_count":12,"area":null},{"id":"2502.16184","title":"Robustness and Cybersecurity in the EU Artificial Intelligence Act","created":"2025-02-22","cited_by_count":11,"area":null},{"id":"2305.04634","title":"Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods","created":"2023-05-08","cited_by_count":10,"area":null},{"id":"2401.03188","title":"A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence","created":"2024-01-06","cited_by_count":10,"area":null},{"id":"2210.08906","title":"A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities","created":"2022-10-17","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":"2404.00897","title":"Machine Learning Robustness: A Primer","created":"2024-04-01","cited_by_count":8,"area":null},{"id":"2407.11906","title":"SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge","created":"2024-07-16","cited_by_count":8,"area":null},{"id":"2305.14986","title":"Non-adversarial Robustness of Deep Learning Methods for Computer Vision","created":"2023-05-24","cited_by_count":6,"area":null},{"id":"2308.14899","title":"RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-centric Learning","created":"2023-08-28","cited_by_count":6,"area":null},{"id":"2206.06127","title":"SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico Experiments","created":"2022-06-13","cited_by_count":5,"area":null},{"id":"2212.00072","title":"Rethinking Causality-driven Robot Tool Segmentation with Temporal Constraints","created":"2022-11-30","cited_by_count":5,"area":null},{"id":"2402.11892","title":"Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing","created":"2024-02-19","cited_by_count":5,"area":null},{"id":"2305.05400","title":"Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm Corruptions","created":"2023-05-09","cited_by_count":4,"area":null},{"id":"2502.09688","title":"Towards Virtual Clinical Trials of Radiology AI with Conditional Generative Modeling","created":"2025-02-13","cited_by_count":4,"area":null},{"id":"2310.07555","title":"Does resistance to style-transfer equal Global Shape Bias? Measuring network sensitivity to global shape configuration","created":"2023-10-11","cited_by_count":3,"area":null},{"id":"2403.07277","title":"A Bayesian Approach to OOD Robustness in Image Classification","created":"2024-03-12","cited_by_count":3,"area":null},{"id":"2411.01644","title":"Achieving Domain-Independent Certified Robustness via Knowledge Continuity","created":"2024-11-03","cited_by_count":3,"area":null},{"id":"2405.09600","title":"Aggregate Representation Measure for Predictive Model Reusability","created":"2024-05-15","cited_by_count":2,"area":null},{"id":"2405.12864","title":"Transparency Distortion Robustness for SOTA Image Segmentation Tasks","created":"2024-05-21","cited_by_count":2,"area":null},{"id":"2410.23494","title":"Causality-Driven Audits of Model Robustness","created":"2024-10-30","cited_by_count":2,"area":null},{"id":"2306.02979","title":"The Chai Platform's AI Safety Framework","created":"2023-06-05","cited_by_count":1,"area":null},{"id":"2408.01139","title":"Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition","created":"2024-08-02","cited_by_count":1,"area":null},{"id":"2410.20026","title":"Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Representation","created":"2024-10-26","cited_by_count":1,"area":null},{"id":"2603.01568","title":"Same Compression Principle, Different Geometry: Rate-Distortion Signatures Dissociate Biological and Artificial Visual Systems","created":"2026-03-02","cited_by_count":1,"area":null},{"id":"2207.09031","title":"Decorrelative Network Architecture for Robust Electrocardiogram Classification","created":"2022-07-19","cited_by_count":0,"area":null},{"id":"2210.06888","title":"AccelAT: A Framework for Accelerating the Adversarial Training of Deep Neural Networks through Accuracy Gradient","created":"2022-10-13","cited_by_count":0,"area":null},{"id":"2311.15356","title":"Having Second Thoughts? Let's hear it","created":"2023-11-26","cited_by_count":0,"area":null},{"id":"2503.02797","title":"A Causal Framework for Aligning Image Quality Metrics and Deep Neural Network Robustness","created":"2025-03-04","cited_by_count":0,"area":null},{"id":"2503.09969","title":"Detecting Dataset Bias in Medical AI: A Generalized and Modality-Agnostic Auditing Framework","created":"2025-03-13","cited_by_count":0,"area":null},{"id":"2505.12642","title":"Two out of Three (ToT): using self-consistency to make robust predictions","created":"2025-05-19","cited_by_count":0,"area":null},{"id":"2510.05006","title":"Latent Uncertainty Representations for Video-based Driver Action and Intention Recognition","created":"2025-10-06","cited_by_count":0,"area":null},{"id":"2510.10653","title":"A Machine Learning Perspective on Automated Driving Corner Cases","created":"2025-10-12","cited_by_count":0,"area":null},{"id":"2512.03014","title":"Instant Video Models: Universal Adapters for Stabilizing Image-Based Networks","created":"2025-12-02","cited_by_count":0,"area":null},{"id":"2601.13122","title":"Responsible AI for General-Purpose Systems: Overview, Challenges, and A Path Forward","created":"2026-01-19","cited_by_count":0,"area":null},{"id":"2603.13286","title":"Advancing Trustworthy AI in Healthcare Through Meta-Research: Results of an Interdisciplinary Design-Thinking Workshop","created":"2026-02-27","cited_by_count":0,"area":null},{"id":"2605.17153","title":"Stress-Testing Neural Network Verifiers with Provably Robust Instances","created":"2026-05-16","cited_by_count":0,"area":null},{"id":"2608.29167","title":"Feature-Spectral Fragility in Segmentation: Dataset Dependence, Architecture-Specific Localization, and Spectral Correlates","created":"2026-08-29","cited_by_count":0,"area":null}],"next_cursor":null}