{"total":30,"rows":[{"id":"2105.10497","title":"Intriguing Properties of Vision Transformers","created":"2021-05-21","cited_by_count":446,"area":null},{"id":"2110.14189","title":"Robust Contrastive Learning Using Negative Samples with Diminished Semantics","created":"2021-10-27","cited_by_count":43,"area":null},{"id":"2108.04890","title":"On the Effect of Pruning on Adversarial Robustness","created":"2021-08-10","cited_by_count":23,"area":null},{"id":"2404.01509","title":"Can Biases in ImageNet Models Explain Generalization?","created":"2024-04-01","cited_by_count":20,"area":null},{"id":"2106.13122","title":"Exploring Corruption Robustness: Inductive Biases in Vision Transformers and MLP-Mixers","created":"2021-06-24","cited_by_count":13,"area":null},{"id":"2509.20234","title":"ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression","created":"2025-09-24","cited_by_count":13,"area":null},{"id":"2305.06568","title":"Convolutional Neural Networks Rarely Learn Shape for Semantic Segmentation","created":"2023-05-11","cited_by_count":12,"area":null},{"id":"2401.09109","title":"Trapped in texture bias? A large scale comparison of deep instance segmentation","created":"2024-01-17","cited_by_count":10,"area":null},{"id":"2409.18055","title":"Visual Data Diagnosis and Debiasing with Concept Graphs","created":"2024-09-26","cited_by_count":6,"area":null},{"id":"2401.08107","title":"Deep Shape-Texture Statistics for Completely Blind Image Quality Evaluation","created":"2024-01-16","cited_by_count":5,"area":null},{"id":"2503.09206","title":"Robust Asymmetric Heterogeneous Federated Learning with Corrupted Clients","created":"2025-03-12","cited_by_count":5,"area":null},{"id":"2406.02535","title":"Enhancing 2D Representation Learning with a 3D Prior","created":"2024-06-04","cited_by_count":3,"area":null},{"id":"2503.12453","title":"Shape Bias and Robustness Evaluation via Cue Decomposition for Image Classification and Segmentation","created":"2025-03-16","cited_by_count":3,"area":null},{"id":"2110.13968","title":"On the Effects of Artificial Data Modification","created":"2021-10-26","cited_by_count":2,"area":null},{"id":"2509.00765","title":"Decomposing and Revising What Language Models Generate","created":"2025-08-31","cited_by_count":2,"area":null},{"id":"2111.13065","title":"Robust Object Detection with Multi-input Multi-output Faster R-CNN","created":"2021-11-25","cited_by_count":1,"area":null},{"id":"2301.10608","title":"Connecting metrics for shape-texture knowledge in computer vision","created":"2023-01-25","cited_by_count":1,"area":null},{"id":"2301.13514","title":"Fourier Sensitivity and Regularization of Computer Vision Models","created":"2023-01-31","cited_by_count":1,"area":null},{"id":"2302.00980","title":"Domain Generalization Emerges from Dreaming","created":"2023-02-02","cited_by_count":1,"area":null},{"id":"2406.05006","title":"Clarifying Myths About the Relationship Between Shape Bias, Accuracy, and Robustness","created":"2024-06-07","cited_by_count":1,"area":null},{"id":"2507.10239","title":"Transferring Styles for Reduced Texture Bias and Improved Robustness in Semantic Segmentation Networks","created":"2025-07-14","cited_by_count":1,"area":null},{"id":"2603.10834","title":"On the Reliability of Cue Conflict and Beyond","created":"2026-03-11","cited_by_count":1,"area":null},{"id":"2203.12872","title":"Intrinsic Bias Identification on Medical Image Datasets","created":"2022-03-24","cited_by_count":0,"area":null},{"id":"2307.06500","title":"On the ability of CNNs to extract color invariant intensity based features for image classification","created":"2023-07-13","cited_by_count":0,"area":null},{"id":"2410.14878","title":"On the Influence of Shape, Texture and Color for Learning Semantic Segmentation","created":"2024-10-18","cited_by_count":0,"area":null},{"id":"2410.15416","title":"Contrast All the Time: Learning Time Series Representation from Temporal Consistency","created":"2024-10-20","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},{"id":"2604.25065","title":"ShapeY: A Principled Framework for Measuring Shape Recognition Capacity via Nearest-Neighbor Matching","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2605.04231","title":"Anatomy of a failure: When, how, and why deep vision fails in scientific domains","created":"2026-05-05","cited_by_count":0,"area":null},{"id":"2609.30478","title":"The Shape of Events: Edge-Based Inductive Biases via Cross-Domain Distillation","created":"2026-09-24","cited_by_count":0,"area":null}],"next_cursor":null}