{"total":35,"rows":[{"id":"2102.12060","title":"Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processing","created":"2021-02-24","cited_by_count":126,"area":null},{"id":"2105.14944","title":"The effectiveness of feature attribution methods and its correlation with automatic evaluation scores","created":"2021-05-31","cited_by_count":88,"area":null},{"id":"2103.01035","title":"If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques","created":"2021-02-26","cited_by_count":82,"area":null},{"id":"2103.01378","title":"Contrastive Explanations for Model Interpretability","created":"2021-03-02","cited_by_count":75,"area":null},{"id":"2108.10539","title":"Counterfactual Explainable Recommendation","created":"2021-08-24","cited_by_count":60,"area":null},{"id":"2105.07878","title":"A Review on Explainability in Multimodal Deep Neural Nets","created":"2021-05-17","cited_by_count":46,"area":null},{"id":"2103.11072","title":"Local Interpretations for Explainable Natural Language Processing: A Survey","created":"2021-03-20","cited_by_count":31,"area":null},{"id":"2209.03943","title":"The Utility of Explainable AI in Ad Hoc Human-Machine Teaming","created":"2022-09-08","cited_by_count":30,"area":null},{"id":"2112.14005","title":"Towards Relatable Explainable AI with the Perceptual Process","created":"2021-12-28","cited_by_count":27,"area":null},{"id":"2306.05731","title":"Multimodal Explainable Artificial Intelligence: A Comprehensive Review of Methodological Advances and Future Research Directions","created":"2023-06-09","cited_by_count":25,"area":null},{"id":"2109.01401","title":"CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models","created":"2021-09-03","cited_by_count":20,"area":null},{"id":"2408.02788","title":"GazeXplain: Learning to Predict Natural Language Explanations of Visual Scanpaths","created":"2024-08-05","cited_by_count":15,"area":null},{"id":"2410.04253","title":"Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills","created":"2024-10-05","cited_by_count":14,"area":null},{"id":"2206.03178","title":"Fooling Explanations in Text Classifiers","created":"2022-06-07","cited_by_count":13,"area":null},{"id":"2205.15540","title":"MACE: An Efficient Model-Agnostic Framework for Counterfactual Explanation","created":"2022-05-31","cited_by_count":12,"area":null},{"id":"2212.08733","title":"Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ","created":"2022-12-16","cited_by_count":12,"area":null},{"id":"2102.03919","title":"Mitigating belief projection in explainable artificial intelligence via Bayesian Teaching","created":"2021-02-07","cited_by_count":10,"area":null},{"id":"2412.14056","title":"A Review of Multimodal Explainable Artificial Intelligence: Past, Present and Future","created":"2024-12-18","cited_by_count":9,"area":null},{"id":"2409.12809","title":"Don't be Fooled: The Misinformation Effect of Explanations in Human-AI Collaboration","created":"2024-09-19","cited_by_count":8,"area":null},{"id":"2211.09937","title":"Explainability Via Causal Self-Talk","created":"2022-11-17","cited_by_count":6,"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":"2109.13301","title":"Exploring The Role of Local and Global Explanations in Recommender Systems","created":"2021-09-27","cited_by_count":4,"area":null},{"id":"2201.03342","title":"COIN: Counterfactual Image Generation for VQA Interpretation","created":"2022-01-10","cited_by_count":4,"area":null},{"id":"2302.12189","title":"HL Dataset: Visually-grounded Description of Scenes, Actions and Rationales","created":"2023-02-23","cited_by_count":4,"area":null},{"id":"2504.20902","title":"Classifier-to-Bias: Toward Unsupervised Automatic Bias Detection for Visual Classifiers","created":"2025-04-29","cited_by_count":4,"area":null},{"id":"2401.09489","title":"PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies","created":"2024-01-16","cited_by_count":3,"area":null},{"id":"2211.05452","title":"Towards Human-Centred Explainability Benchmarks For Text Classification","created":"2022-11-10","cited_by_count":2,"area":null},{"id":"2404.16534","title":"SIDEs: Separating Idealization from Deceptive Explanations in xAI","created":"2024-04-25","cited_by_count":2,"area":null},{"id":"2408.10528","title":"NoMatterXAI: Generating \"No Matter What\" Alterfactual Examples for Explaining Black-Box Text Classification Models","created":"2024-08-20","cited_by_count":2,"area":null},{"id":"2503.05424","title":"Locally Explaining Prediction Behavior via Gradual Interventions and Measuring Property Gradients","created":"2025-03-07","cited_by_count":2,"area":null},{"id":"2204.13192","title":"Counterfactual Explanations for Natural Language Interfaces","created":"2022-04-27","cited_by_count":1,"area":null},{"id":"2410.14522","title":"Rethinking Distance Metrics for Counterfactual Explainability","created":"2024-10-18","cited_by_count":1,"area":null},{"id":"2105.07508","title":"Abstraction, Validation, and Generalization for Explainable Artificial Intelligence","created":"2021-05-16","cited_by_count":0,"area":null},{"id":"2408.16809","title":"See or Guess: Counterfactually Regularized Image Captioning","created":"2024-08-29","cited_by_count":0,"area":null},{"id":"2409.02965","title":"Do We Trust What They Say or What They Do? A Multimodal User Embedding Provides Personalized Explanations","created":"2024-09-04","cited_by_count":0,"area":null}],"next_cursor":null}