{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/explainable-artificial-intelligence/papers/8","list_of":"/task/explainable-artificial-intelligence","task":"Explainable artificial intelligence","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":8,"pages_in_order":10,"rows_per_page":100,"rows":[701,800],"of":971,"counts":{"archive_papers_tagged":971,"with_a_code_link":305,"where_syntology_ran_a_sample":40,"not_listed_spam_title":0,"listed":971,"listed_where_code_ran":40,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":35,"every_run_a_failure_of_syntologys_instrument":5,"listed_with_a_run_with_no_instrument_failure":35,"listed_every_run_a_failure_of_syntologys_instrument":5,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/explainable-artificial-intelligence","prev":"/task/explainable-artificial-intelligence/papers/7","next":"/task/explainable-artificial-intelligence/papers/9","papers":[{"url":null,"slug":"against-algorithmic-exploitation-of-human","title":"Against Algorithmic Exploitation of Human Vulnerabilities","date":"2023-01-12","arxiv_id":"2301.04993","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-imitation-learning-through-frames","title":"Explaining Imitation Learning through Frames","date":"2023-01-03","arxiv_id":"2301.01088","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-theoretical-framework-for-ai-models","title":"A Theoretical Framework for AI Models Explainability with Application in Biomedicine","date":"2022-12-29","arxiv_id":"2212.14447","repositories_listed":0,"syntology":null},{"url":null,"slug":"graphix-graph-based-in-silico-xai-explainable","title":"GraphIX: Graph-based In silico XAI(explainable artificial intelligence) for drug repositioning from biopharmaceutical network","date":"2022-12-21","arxiv_id":"2212.10788","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-in-2","title":"Explainable Artificial Intelligence in Retinal Imaging for the detection of Systemic Diseases","date":"2022-12-14","arxiv_id":"2212.07058","repositories_listed":0,"syntology":null},{"url":null,"slug":"analysis-of-explainable-artificial","title":"Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification","date":"2022-12-10","arxiv_id":"2212.10565","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixboost-improving-the-robustness-of-deep","title":"MixBoost: Improving the Robustness of Deep Neural Networks by Boosting Data Augmentation","date":"2022-12-08","arxiv_id":"2212.04059","repositories_listed":0,"syntology":null},{"url":null,"slug":"xrand-differentially-private-defense-against","title":"XRand: Differentially Private Defense against Explanation-Guided Attacks","date":"2022-12-08","arxiv_id":"2212.04454","repositories_listed":0,"syntology":null},{"url":null,"slug":"going-beyond-xai-a-systematic-survey-for","title":"Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning","date":"2022-12-07","arxiv_id":"2212.03954","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-xai-from","title":"Explainable Artificial Intelligence (XAI) from a user perspective- A synthesis of prior literature and problematizing avenues for future research","date":"2022-11-24","arxiv_id":"2211.15343","repositories_listed":0,"syntology":null},{"url":null,"slug":"crown-cam-reliable-visual-explanations-for","title":"Crown-CAM: Interpretable Visual Explanations for Tree Crown Detection in Aerial Images","date":"2022-11-23","arxiv_id":"2211.13126","repositories_listed":0,"syntology":null},{"url":null,"slug":"revealing-hidden-context-bias-in-segmentation","title":"Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations","date":"2022-11-21","arxiv_id":"2211.11426","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-and-1","title":"Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection","date":"2022-11-19","arxiv_id":"2211.10595","repositories_listed":0,"syntology":null},{"url":null,"slug":"soldernet-towards-trustworthy-visual","title":"SolderNet: Towards Trustworthy Visual Inspection of Solder Joints in Electronics Manufacturing Using Explainable Artificial Intelligence","date":"2022-11-18","arxiv_id":"2211.10274","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-explainability-to-design-physics-aware","title":"Using explainability to design physics-aware CNNs for solving subsurface inverse problems","date":"2022-11-16","arxiv_id":"2211.08651","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-in-1","title":"Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework","date":"2022-11-12","arxiv_id":"2211.06561","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-precepts","title":"Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction","date":"2022-11-12","arxiv_id":"2211.06579","repositories_listed":0,"syntology":null},{"url":null,"slug":"motif-guided-time-series-counterfactual","title":"Motif-guided Time Series Counterfactual Explanations","date":"2022-11-08","arxiv_id":"2211.04411","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-ai-over-the-internet-of-things","title":"Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions","date":"2022-11-02","arxiv_id":"2211.01036","repositories_listed":0,"syntology":null},{"url":null,"slug":"backtracking-counterfactuals","title":"Backtracking Counterfactuals","date":"2022-11-01","arxiv_id":"2211.00472","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-human-cognition-level-based","title":"Towards Human Cognition Level-based Experiment Design for Counterfactual Explanations (XAI)","date":"2022-10-31","arxiv_id":"2211.00103","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-diagnosis-of-myocarditis-disease-in","title":"Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence","date":"2022-10-26","arxiv_id":"2210.14611","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-temporal-type-2-fuzzy-system-for-time","title":"A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence","date":"2022-10-22","arxiv_id":"2210.12571","repositories_listed":0,"syntology":null},{"url":null,"slug":"sustainable-personalisation-and","title":"Sustainable Personalisation and Explainability in Dyadic Data Systems","date":"2022-10-19","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-automated-gender-classification-of","title":"Explaining automated gender classification of human gait","date":"2022-10-16","arxiv_id":"2211.17015","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-machine-learning-models-for-age","title":"Explaining machine learning models for age classification in human gait analysis","date":"2022-10-16","arxiv_id":"2211.17016","repositories_listed":0,"syntology":null},{"url":null,"slug":"infip-an-explainable-dnn-intellectual","title":"InFIP: An Explainable DNN Intellectual Property Protection Method based on Intrinsic Features","date":"2022-10-14","arxiv_id":"2210.07481","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-in-transaction-monitoring","title":"Machine Learning in Transaction Monitoring: The Prospect of xAI","date":"2022-10-14","arxiv_id":"2210.07648","repositories_listed":0,"syntology":null},{"url":null,"slug":"neuro-symbolic-explainable-artificial","title":"Neuro-symbolic Explainable Artificial Intelligence Twin for Zero-touch IoE in Wireless Network","date":"2022-10-13","arxiv_id":"2210.06649","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-the-application-of-xai-methods-in-eeg","title":"Toward the application of XAI methods in EEG-based systems","date":"2022-10-12","arxiv_id":"2210.06554","repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-explainable-ai-for-improving-the","title":"Utilizing Explainable AI for improving the Performance of Neural Networks","date":"2022-10-07","arxiv_id":"2210.04686","repositories_listed":0,"syntology":null},{"url":null,"slug":"fault-diagnosis-using-explainable-ai-a","title":"Fault Diagnosis using eXplainable AI: a Transfer Learning-based Approach for Rotating Machinery exploiting Augmented Synthetic Data","date":"2022-10-06","arxiv_id":"2210.02974","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-influence-of-explainable-artificial","title":"The Influence of Explainable Artificial Intelligence: Nudging Behaviour or Boosting Capability?","date":"2022-10-05","arxiv_id":"2210.02407","repositories_listed":0,"syntology":null},{"url":null,"slug":"oak4xai-model-towards-out-of-box-explainable","title":"OAK4XAI: Model towards Out-Of-Box eXplainable Artificial Intelligence for Digital Agriculture","date":"2022-09-29","arxiv_id":"2209.15104","repositories_listed":0,"syntology":null},{"url":null,"slug":"asset-pricing-and-deep-learning","title":"Asset Pricing and Deep Learning","date":"2022-09-24","arxiv_id":"2209.12014","repositories_listed":0,"syntology":null},{"url":null,"slug":"survey-on-deep-fuzzy-systems-in-regression","title":"Survey on Deep Fuzzy Systems in regression applications: a view on interpretability","date":"2022-09-09","arxiv_id":"2209.04230","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-to-detect","title":"Explainable Artificial Intelligence to Detect Image Spam Using Convolutional Neural Network","date":"2022-09-07","arxiv_id":"2209.03166","repositories_listed":0,"syntology":null},{"url":null,"slug":"responsibility-an-example-based-explainable","title":"Responsibility: An Example-based Explainable AI approach via Training Process Inspection","date":"2022-09-07","arxiv_id":"2209.03433","repositories_listed":0,"syntology":null},{"url":null,"slug":"sell-me-the-blackbox-why-explainable","title":"Regulating eXplainable Artificial Intelligence (XAI) May Harm Consumers","date":"2022-09-07","arxiv_id":"2209.03499","repositories_listed":0,"syntology":null},{"url":null,"slug":"incremental-permutation-feature-importance","title":"Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams","date":"2022-09-05","arxiv_id":"2209.01939","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-detailed-saliency-maps-using-model","title":"Generating detailed saliency maps using model-agnostic methods","date":"2022-09-04","arxiv_id":"2209.09202","repositories_listed":0,"syntology":null},{"url":null,"slug":"identifying-dominant-industrial-sectors-in","title":"Identifying Dominant Industrial Sectors in Market States of the S&P 500 Financial Data","date":"2022-08-30","arxiv_id":"2208.14106","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-benchmarking-explainable-artificial","title":"Towards Benchmarking Explainable Artificial Intelligence Methods","date":"2022-08-25","arxiv_id":"2208.12120","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmented-cross-selling-through-explainable","title":"Augmented cross-selling through explainable AI -- a case from energy retailing","date":"2022-08-24","arxiv_id":"2208.11404","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-ai-for-tailored-electricity","title":"Explainable AI for tailored electricity consumption feedback -- an experimental evaluation of visualizations","date":"2022-08-24","arxiv_id":"2208.11408","repositories_listed":0,"syntology":null},{"url":null,"slug":"carefully-choose-the-baseline-lessons-learned","title":"Carefully choose the baseline: Lessons learned from applying XAI attribution methods for regression tasks in geoscience","date":"2022-08-19","arxiv_id":"2208.09473","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-biometrics-in-the-age-of-deep","title":"Causality-Inspired Taxonomy for Explainable Artificial Intelligence","date":"2022-08-19","arxiv_id":"2208.09500","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-reinforcement-learning-on","title":"Explainable Reinforcement Learning on Financial Stock Trading using SHAP","date":"2022-08-18","arxiv_id":"2208.08790","repositories_listed":0,"syntology":null},{"url":null,"slug":"transcending-xai-algorithm-boundaries-through","title":"Transcending XAI Algorithm Boundaries through End-User-Inspired Design","date":"2022-08-18","arxiv_id":"2208.08739","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-for-7","title":"Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand","date":"2022-08-15","arxiv_id":"2208.06981","repositories_listed":0,"syntology":null},{"url":null,"slug":"trustworthy-visual-analytics-in-clinical-gait","title":"Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy","date":"2022-08-10","arxiv_id":"2208.05232","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-means-end-account-of-explainable-artificial","title":"A Means-End Account of Explainable Artificial Intelligence","date":"2022-08-09","arxiv_id":"2208.04638","repositories_listed":0,"syntology":null},{"url":null,"slug":"diagnosis-of-paratuberculosis-in","title":"Diagnosis of Paratuberculosis in Histopathological Images Based on Explainable Artificial Intelligence and Deep Learning","date":"2022-08-02","arxiv_id":"2208.01674","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-approaches-in-processing-and-using-data-in","title":"AI Approaches in Processing and Using Data in Personalized Medicine","date":"2022-07-26","arxiv_id":"2208.04698","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-urban-population-health-observatory-for","title":"An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: Underlying Explainable Artificial Intelligence Model","date":"2022-07-26","arxiv_id":"2208.04144","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-interpretable-filters-to-predictions-of","title":"From Interpretable Filters to Predictions of Convolutional Neural Networks with Explainable Artificial Intelligence","date":"2022-07-26","arxiv_id":"2207.12958","repositories_listed":0,"syntology":null},{"url":null,"slug":"alterfactual-explanations-the-relevance-of","title":"Alterfactual Explanations -- The Relevance of Irrelevance for Explaining AI Systems","date":"2022-07-19","arxiv_id":"2207.09374","repositories_listed":0,"syntology":null},{"url":null,"slug":"creating-an-explainable-intrusion-detection","title":"Creating an Explainable Intrusion Detection System Using Self Organizing Maps","date":"2022-07-15","arxiv_id":"2207.07465","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-integration-in-systems-genetics-and","title":"Data integration in systems genetics and aging research","date":"2022-07-07","arxiv_id":"2207.03540","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-human-like-explanations-for-robot","title":"Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios","date":"2022-07-07","arxiv_id":"2207.03214","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainability-in-deep-reinforcement-learning-1","title":"Explainability in Deep Reinforcement Learning, a Review into Current Methods and Applications","date":"2022-07-05","arxiv_id":"2207.01911","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-any-ml-model-on-goals-and","title":"Explaining Any ML Model? -- On Goals and Capabilities of XAI","date":"2022-06-28","arxiv_id":"2206.13888","repositories_listed":0,"syntology":null},{"url":null,"slug":"explanation-is-not-a-technical-term-the","title":"\"Explanation\" is Not a Technical Term: The Problem of Ambiguity in XAI","date":"2022-06-27","arxiv_id":"2207.00007","repositories_listed":0,"syntology":null},{"url":null,"slug":"explanation-based-counterfactual-retraining","title":"Explanation-based Counterfactual Retraining(XCR): A Calibration Method for Black-box Models","date":"2022-06-22","arxiv_id":"2206.11126","repositories_listed":0,"syntology":null},{"url":null,"slug":"stop-ordering-machine-learning-algorithms-by","title":"Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability","date":"2022-06-20","arxiv_id":"2206.10610","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-in-sports-a-case-study-on","title":"Machine Learning in Sports: A Case Study on Using Explainable Models for Predicting Outcomes of Volleyball Matches","date":"2022-06-18","arxiv_id":"2206.09258","repositories_listed":0,"syntology":null},{"url":null,"slug":"attributions-beyond-neural-networks-the","title":"Attributions Beyond Neural Networks: The Linear Program Case","date":"2022-06-14","arxiv_id":"2206.07203","repositories_listed":0,"syntology":null},{"url":null,"slug":"mediators-conversational-agents-explaining","title":"Mediators: Conversational Agents Explaining NLP Model Behavior","date":"2022-06-13","arxiv_id":"2206.06029","repositories_listed":0,"syntology":null},{"url":null,"slug":"eclad-extracting-concepts-with-local","title":"ECLAD: Extracting Concepts with Local Aggregated Descriptors","date":"2022-06-09","arxiv_id":"2206.04531","repositories_listed":0,"syntology":null},{"url":null,"slug":"challenges-in-applying-explainability-methods","title":"Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models","date":"2022-06-08","arxiv_id":"2206.03945","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-xai-for-2","title":"Explainable Artificial Intelligence (XAI) for Internet of Things: A Survey","date":"2022-06-07","arxiv_id":"2206.04800","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-requirements-engineering-support","title":"Can Requirements Engineering Support Explainable Artificial Intelligence? Towards a User-Centric Approach for Explainability Requirements","date":"2022-06-03","arxiv_id":"2206.01507","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparing-interpretation-methods-in-mental","title":"Comparing interpretation methods in mental state decoding analyses with deep learning models","date":"2022-05-31","arxiv_id":"2205.15581","repositories_listed":0,"syntology":null},{"url":null,"slug":"multivariate-probabilistic-forecasting-of","title":"Multivariate Probabilistic Forecasting of Intraday Electricity Prices using Normalizing Flows","date":"2022-05-27","arxiv_id":"2205.13826","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-psychological-theory-of-explainability","title":"A Psychological Theory of Explainability","date":"2022-05-17","arxiv_id":"2205.08452","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-conflict-between-explainable-and","title":"The Conflict Between Explainable and Accountable Decision-Making Algorithms","date":"2022-05-11","arxiv_id":"2205.05306","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-meta-analysis-on-the-utility-of-explainable","title":"A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making","date":"2022-05-10","arxiv_id":"2205.05126","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-ai-via-learning-to-optimize","title":"Explainable AI via Learning to Optimize","date":"2022-04-29","arxiv_id":"2204.14174","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-prior-knowledge-in-post-hoc","title":"Integrating Prior Knowledge in Post-hoc Explanations","date":"2022-04-25","arxiv_id":"2204.11634","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-analysis-of-deep-learning-methods","title":"Explainable Analysis of Deep Learning Methods for SAR Image Classification","date":"2022-04-14","arxiv_id":"2204.06783","repositories_listed":0,"syntology":null},{"url":null,"slug":"explain-yourself-effects-of-explanations-in","title":"Explain yourself! Effects of Explanations in Human-Robot Interaction","date":"2022-04-09","arxiv_id":"2204.04501","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-data-driven-framework-for-identifying","title":"A Data-Driven Framework for Identifying Investment Opportunities in Private Equity","date":"2022-04-04","arxiv_id":"2204.01852","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-deep-is-your-art-an-experimental-study-on","title":"How Deep is Your Art: An Experimental Study on the Limits of Artistic Understanding in a Single-Task, Single-Modality Neural Network","date":"2022-03-30","arxiv_id":"2203.16031","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-meta-survey-of-quality-evaluation-criteria","title":"A Meta Survey of Quality Evaluation Criteria in Explanation Methods","date":"2022-03-25","arxiv_id":"2203.13929","repositories_listed":0,"syntology":null},{"url":null,"slug":"concept-embedding-analysis-a-review","title":"Concept Embedding Analysis: A Review","date":"2022-03-25","arxiv_id":"2203.13909","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-for-5","title":"Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines","date":"2022-03-24","arxiv_id":"2203.13108","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-multi-objective-model-based","title":"Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models","date":"2022-03-24","arxiv_id":"2203.13347","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-centric-artificial-intelligence","title":"Human-Centric Artificial Intelligence Architecture for Industry 5.0 Applications","date":"2022-03-21","arxiv_id":"2203.10794","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-binary-decision-diagrams-with","title":"Optimizing Binary Decision Diagrams with MaxSAT for classification","date":"2022-03-21","arxiv_id":"2203.11386","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-explainable-stacked-ensemble-model-for","title":"An Explainable Stacked Ensemble Model for Static Route-Free Estimation of Time of Arrival","date":"2022-03-17","arxiv_id":"2203.09438","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-explaining-opportunities-and","title":"Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement","date":"2022-03-15","arxiv_id":"2203.08008","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-machine-learning-for-predicting","title":"Explainable Machine Learning for Predicting Homicide Clearance in the United States","date":"2022-03-09","arxiv_id":"2203.04768","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainability-for-identification-of","title":"Explainability for identification of vulnerable groups in machine learning models","date":"2022-03-01","arxiv_id":"2203.00317","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-a-deep-reinforcement-learning","title":"Explaining a Deep Reinforcement Learning Docking Agent Using Linear Model Trees with User Adapted Visualization","date":"2022-03-01","arxiv_id":"2203.00368","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-natural-language-processing-and","title":"Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain","date":"2022-02-25","arxiv_id":"2202.12678","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-reproducibility-and-explainable","title":"Deep Learning Reproducibility and Explainable AI (XAI)","date":"2022-02-23","arxiv_id":"2202.11452","repositories_listed":0,"syntology":null},{"url":null,"slug":"timereise-time-series-randomized-evolving","title":"TimeREISE: Time-series Randomized Evolving Input Sample Explanation","date":"2022-02-16","arxiv_id":"2202.07952","repositories_listed":0,"syntology":null},{"url":null,"slug":"hat5-hate-language-identification-using-text","title":"HaT5: Hate Language Identification using Text-to-Text Transfer Transformer","date":"2022-02-11","arxiv_id":"2202.05690","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-ai-through-the-learning-of","title":"Explainable AI through the Learning of Arguments","date":"2022-02-01","arxiv_id":"2202.00383","repositories_listed":0,"syntology":null},{"url":null,"slug":"causal-explanations-and-xai","title":"Causal Explanations and XAI","date":"2022-01-31","arxiv_id":"2201.13169","repositories_listed":0,"syntology":null}],"record_sha256":"2890c2c6f39aee786f5ffc1390c5eb0b71d5a066c567b7358959a209d7d27630","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}