{"list":"other","total":53,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"1710.10903","title":"Graph Attention Networks","created":"2017-10-30","cited_by_count":8923},{"id":"1610.02391","title":"Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization","created":"2016-10-07","cited_by_count":6733},{"id":"1705.07874","title":"A Unified Approach to Interpreting Model Predictions","created":"2017-05-22","cited_by_count":6555},{"id":"1406.1078","title":"Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation","created":"2014-06-03","cited_by_count":4057},{"id":"1409.3215","title":"Sequence to Sequence Learning with Neural Networks","created":"2014-09-10","cited_by_count":2986},{"id":"1512.04150","title":"Learning Deep Features for Discriminative Localization","created":"2015-12-14","cited_by_count":2436},{"id":"1311.2901","title":"Visualizing and Understanding Convolutional Networks","created":"2013-11-12","cited_by_count":2290},{"id":"1910.10045","title":"Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI","created":"2019-10-22","cited_by_count":1552},{"id":"1704.02685","title":"Learning Important Features Through Propagating Activation Differences","created":"2017-04-10","cited_by_count":1458},{"id":"1702.08608","title":"Towards A Rigorous Science of Interpretable Machine Learning","created":"2017-02-28","cited_by_count":1416},{"id":"2002.08155","title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages","created":"2020-02-19","cited_by_count":1310},{"id":"1706.07269","title":"Explanation in Artificial Intelligence: Insights from the Social Sciences","created":"2017-06-22","cited_by_count":1206},{"id":"1802.01933","title":"A Survey Of Methods For Explaining Black Box Models","created":"2018-02-06","cited_by_count":973},{"id":"2109.00859","title":"CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation","created":"2021-09-02","cited_by_count":906},{"id":"2102.04664","title":"CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation","created":"2021-02-09","cited_by_count":744},{"id":"1903.03894","title":"GNNExplainer: Generating Explanations for Graph Neural Networks","created":"2019-03-10","cited_by_count":737},{"id":"1909.09436","title":"CodeSearchNet Challenge: Evaluating the State of Semantic Code Search","created":"2019-09-20","cited_by_count":654},{"id":"2009.08366","title":"GraphCodeBERT: Pre-training Code Representations with Data Flow","created":"2020-09-17","cited_by_count":609},{"id":"2201.08164","title":"From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI","created":"2022-01-20","cited_by_count":302},{"id":"1512.02479","title":"Explaining NonLinear Classification Decisions with Deep Taylor Decomposition","created":"2015-12-08","cited_by_count":250},{"id":"2011.07876","title":"A Survey on the Explainability of Supervised Machine Learning","created":"2020-11-16","cited_by_count":227},{"id":"2103.00073","title":"CURE: Code-Aware Neural Machine Translation for Automatic Program Repair","created":"2021-02-26","cited_by_count":86},{"id":"2101.05307","title":"Explainability of deep vision-based autonomous driving systems: Review and challenges","created":"2021-01-13","cited_by_count":80},{"id":"1908.00087","title":"explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning","created":"2019-07-29","cited_by_count":70},{"id":"2106.10478","title":"Vulnerability Detection with Fine-grained Interpretations","created":"2021-06-19","cited_by_count":56},{"id":"2202.06840","title":"What Do They Capture? -- A Structural Analysis of Pre-Trained Language Models for Source Code","created":"2022-02-14","cited_by_count":50},{"id":"2011.14597","title":"A Survey on Deep Learning for Software Engineering","created":"2020-11-30","cited_by_count":38},{"id":"2210.06929","title":"On the Explainability of Natural Language Processing Deep Models","created":"2022-10-13","cited_by_count":38},{"id":"2010.10563","title":"A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images","created":"2020-10-20","cited_by_count":35},{"id":"2205.04766","title":"Explainable Deep Learning Methods in Medical Image Classification: A Survey","created":"2022-05-10","cited_by_count":32},{"id":"2111.05711","title":"Counterfactual Explanations for Models of Code","created":"2021-11-10","cited_by_count":25},{"id":"2106.09282","title":"Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion","created":"2021-06-17","cited_by_count":24},{"id":"2106.03353","title":"Understanding Neural Code Intelligence Through Program Simplification","created":"2021-06-07","cited_by_count":22},{"id":"2401.00288","title":"Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit","created":"2023-12-30","cited_by_count":22},{"id":"2208.10605","title":"SoK: Explainable Machine Learning for Computer Security Applications","created":"2022-08-22","cited_by_count":20},{"id":"2207.09021","title":"Actionable and Interpretable Fault Localization for Recurring Failures in Online Service Systems","created":"2022-07-19","cited_by_count":19},{"id":"1804.01955","title":"Explanations of model predictions with live and breakDown packages","created":"2018-04-05","cited_by_count":17},{"id":"2004.11516","title":"Why an Android App is Classified as Malware? Towards Malware Classification Interpretation","created":"2020-04-24","cited_by_count":16},{"id":"1802.00603","title":"Explainable Software Analytics","created":"2018-02-02","cited_by_count":15},{"id":"2009.03612","title":"Predicting Defective Lines Using a Model-Agnostic Technique","created":"2020-09-08","cited_by_count":14},{"id":"2308.12415","title":"Benchmarking Causal Study to Interpret Large Language Models for Source Code","created":"2023-08-23","cited_by_count":14},{"id":"2308.11237","title":"Distinguishing Look-Alike Innocent and Vulnerable Code by Subtle Semantic Representation Learning and Explanation","created":"2023-08-22","cited_by_count":11},{"id":"2209.00812","title":"Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well?","created":"2022-09-02","cited_by_count":10},{"id":"2309.11960","title":"A Comprehensive Review on Financial Explainable AI","created":"2023-09-21","cited_by_count":10},{"id":"2111.10085","title":"Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors","created":"2021-11-19","cited_by_count":7},{"id":"2310.18740","title":"TraceDiag: Adaptive, Interpretable, and Efficient Root Cause Analysis on Large-Scale Microservice Systems","created":"2023-10-28","cited_by_count":7},{"id":"1904.00935","title":"STYLE-ANALYZER: fixing code style inconsistencies with interpretable unsupervised algorithms","created":"2019-04-01","cited_by_count":6},{"id":"2302.07445","title":"Silent Vulnerable Dependency Alert Prediction with Vulnerability Key Aspect Explanation","created":"2023-02-15","cited_by_count":5},{"id":"2102.09687","title":"SQAPlanner: Generating Data-Informed Software Quality Improvement Plans","created":"2021-02-19","cited_by_count":4},{"id":"2302.06065","title":"A Systematic Literature Review of Explainable AI for Software Engineering","created":"2023-02-13","cited_by_count":3},{"id":"2308.06005","title":"How Early Participation Determines Long-Term Sustained Activity in GitHub Projects?","created":"2023-08-11","cited_by_count":3}],"next_cursor":null}