LEADER 05329nam 22006375 450 001 9910872185403321 005 20250806170130.0 010 $a3-031-63787-9 024 7 $a10.1007/978-3-031-63787-2 035 $a(CKB)32775313100041 035 $a(MiAaPQ)EBC31523148 035 $a(Au-PeEL)EBL31523148 035 $a(DE-He213)978-3-031-63787-2 035 $a(EXLCZ)9932775313100041 100 $a20240710d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExplainable Artificial Intelligence $eSecond World Conference, xAI 2024, Valletta, Malta, July 17?19, 2024, Proceedings, Part I /$fedited by Luca Longo, Sebastian Lapuschkin, Christin Seifert 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (508 pages) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v2153 311 08$a3-031-63786-0 327 $a -- Intrinsically interpretable XAI and concept-based global explainability. -- Seeking Interpretability and Explainability in Binary Activated Neural Networks. -- Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges. -- Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model. -- Revisiting FunnyBirds evaluation framework for prototypical parts networks. -- CoProNN: Concept-based Prototypical Nearest Neighbors for Explaining Vision Models. -- Unveiling the Anatomy of Adversarial Attacks: Concept-based XAI Dissection of CNNs. -- AutoCL: AutoML for Concept Learning. -- Locally Testing Model Detections for Semantic Global Concepts. -- Knowledge graphs for empirical concept retrieval. -- Global Concept Explanations for Graphs by Contrastive Learning. -- Generative explainable AI and verifiability. -- Augmenting XAI with LLMs: A Case Study in Banking Marketing Recommendation. -- Generative Inpainting for Shapley-Value-Based Anomaly Explanation. -- Challenges and Opportunities in Text Generation Explainability. -- NoNE Found: Explaining the Output of Sequence-to-Sequence Models when No Named Entity is Recognized. -- Notion, metrics, evaluation and benchmarking for XAI. -- Benchmarking Trust: A Metric for Trustworthy Machine Learning. -- Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI. -- Conditional Calibrated Explanations: Finding a Path between Bias and Uncertainty. -- Meta-evaluating stability measures: MAX-Sensitivity & AVG-Senstivity. -- Xpression: A unifying metric to evaluate Explainability and Compression of AI models. -- Evaluating Neighbor Explainability for Graph Neural Networks. -- A Fresh Look at Sanity Checks for Saliency Maps. -- Explainability, Quantified: Benchmarking XAI techniques. -- BEExAI: Benchmark to Evaluate Explainable AI. -- Associative Interpretability of Hidden Semantics with Contrastiveness Operators in Face Classification tasks. 330 $aThis four-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2024, held in Valletta, Malta, during July 17-19, 2024. The 95 full papers presented were carefully reviewed and selected from 204 submissions. The conference papers are organized in topical sections on: Part I - intrinsically interpretable XAI and concept-based global explainability; generative explainable AI and verifiability; notion, metrics, evaluation and benchmarking for XAI. Part II - XAI for graphs and computer vision; logic, reasoning, and rule-based explainable AI; model-agnostic and statistical methods for eXplainable AI. Part III - counterfactual explanations and causality for eXplainable AI; fairness, trust, privacy, security, accountability and actionability in eXplainable AI. Part IV - explainable AI in healthcare and computational neuroscience; explainable AI for improved human-computer interaction and software engineering for explainability; applications of explainable artificial intelligence. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v2153 606 $aArtificial intelligence 606 $aNatural language processing (Computer science) 606 $aApplication software 606 $aComputer networks 606 $aArtificial Intelligence 606 $aNatural Language Processing (NLP) 606 $aComputer and Information Systems Applications 606 $aComputer Communication Networks 615 0$aArtificial intelligence. 615 0$aNatural language processing (Computer science) 615 0$aApplication software. 615 0$aComputer networks. 615 14$aArtificial Intelligence. 615 24$aNatural Language Processing (NLP). 615 24$aComputer and Information Systems Applications. 615 24$aComputer Communication Networks. 676 $a006.3 700 $aLongo$b Luca$01337583 701 $aLapuschkin$b Sebastian$01744132 701 $aSeifert$b Christin$01744133 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910872185403321 996 $aExplainable Artificial Intelligence$94173978 997 $aUNINA