{"total":24,"rows":[{"id":"2312.02974","title":"Describing Differences in Image Sets with Natural Language","created":"2023-12-05","cited_by_count":53,"area":null},{"id":"2305.19164","title":"LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images","created":"2023-05-30","cited_by_count":46,"area":null},{"id":"2303.05470","title":"Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases","created":"2023-03-09","cited_by_count":41,"area":null},{"id":"2309.14356","title":"COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs","created":"2023-09-23","cited_by_count":39,"area":null},{"id":"2310.10402","title":"Real-Fake: Effective Training Data Synthesis Through Distribution Matching","created":"2023-10-16","cited_by_count":36,"area":null},{"id":"2309.07944","title":"Text-to-Image Models for Counterfactual Explanations: a Black-Box Approach","created":"2023-09-14","cited_by_count":28,"area":null},{"id":"2401.08567","title":"Connect, Collapse, Corrupt: Learning Cross-Modal Tasks with Uni-Modal Data","created":"2024-01-16","cited_by_count":27,"area":null},{"id":"2404.11534","title":"Decomposing and Editing Predictions by Modeling Model Computation","created":"2024-04-17","cited_by_count":19,"area":null},{"id":"2303.05072","title":"Identification of Systematic Errors of Image Classifiers on Rare Subgroups","created":"2023-03-09","cited_by_count":17,"area":null},{"id":"2311.17833","title":"DiG-IN: Diffusion Guidance for Investigating Networks -- Uncovering Classifier Differences Neuron Visualisations and Visual Counterfactual Explanations","created":"2023-11-29","cited_by_count":11,"area":null},{"id":"2306.08167","title":"Where Does My Model Underperform? A Human Evaluation of Slice Discovery Algorithms","created":"2023-06-13","cited_by_count":9,"area":null},{"id":"2310.00164","title":"PRIME: Prioritizing Interpretability in Failure Mode Extraction","created":"2023-09-29","cited_by_count":9,"area":null},{"id":"2402.03715","title":"Clarify: Improving Model Robustness With Natural Language Corrections","created":"2024-02-06","cited_by_count":8,"area":null},{"id":"2403.01231","title":"Benchmarking Segmentation Models with Mask-Preserved Attribute Editing","created":"2024-03-02","cited_by_count":6,"area":null},{"id":"2308.10103","title":"ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious Correlations","created":"2023-08-19","cited_by_count":5,"area":null},{"id":"2408.04471","title":"What could go wrong? Discovering and describing failure modes in computer vision","created":"2024-08-08","cited_by_count":5,"area":null},{"id":"2410.06243","title":"Unsupervised Model Diagnosis","created":"2024-10-08","cited_by_count":4,"area":null},{"id":"2411.01948","title":"Learning Where to Edit Vision Transformers","created":"2024-11-04","cited_by_count":4,"area":null},{"id":"2407.10633","title":"Evaluating Model Bias Requires Characterizing its Mistakes","created":"2024-07-15","cited_by_count":3,"area":null},{"id":"2603.01535","title":"Benchmarking Semantic Segmentation Models via Appearance and Geometry Attribute Editing","created":"2026-03-02","cited_by_count":2,"area":null},{"id":"2408.16536","title":"Are Pose Estimators Ready for the Open World? STAGE: A GenAI Toolkit for Auditing 3D Human Pose Estimators","created":"2024-08-28","cited_by_count":1,"area":null},{"id":"2405.02332","title":"Efficient Exploration of Image Classifier Failures with Bayesian Optimization and Text-to-Image Models","created":"2024-04-26","cited_by_count":0,"area":null},{"id":"2508.08701","title":"SafeFix: Targeted Model Repair via Controlled Image Generation","created":"2025-08-12","cited_by_count":0,"area":null},{"id":"2609.03677","title":"Understanding Autonomous Driving Datasets by Describing Differences between Image Subsets in Natural Language","created":"2026-09-03","cited_by_count":0,"area":null}],"next_cursor":null}