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Publication search results
found 25 matches
- 2024
- Fernando Aguilar-Canto, Omar García-Vázquez, Tania Alcántara, Alberto Espinosa-Juarez, Hiram Calvo:
Associative Interpretability of Hidden Semantics with Contrastiveness Operators in Face Classification Tasks. xAI (1) 2024: 469-491 - Kenza Amara, Rita Sevastjanova, Mennatallah El-Assady:
Challenges and Opportunities in Text Generation Explainability. xAI (1) 2024: 244-264 - Eric Arazo, Hristo Stoev, Cristian Bosch, Andrés L. Suárez-Cetrulo, Ricardo Simon Carbajo:
Xpression: A Unifying Metric to Optimize Compression and Explainability Robustness of AI Models. xAI (1) 2024: 370-382 - Alessandro Castelnovo, Roberto Depalmas, Fabio Mercorio, Nicolò Mombelli, Daniele Potertì, Antonio Serino, Andrea Seveso, Salvatore Sorrentino, Laura Viola:
Augmenting XAI with LLMs: A Case Study in Banking Marketing Recommendation. xAI (1) 2024: 211-229 - Teodor Chiaburu, Frank Haußer, Felix Bießmann:
CoProNN: Concept-Based Prototypical Nearest Neighbors for Explaining Vision Models. xAI (1) 2024: 69-91 - Jane Arleth dela Cruz, Iris Hendrickx, Martha A. Larson:
NoNE Found: Explaining the Output of Sequence-to-Sequence Models When No Named Entity Is Recognized. xAI (1) 2024: 265-284 - Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz:
Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model. xAI (1) 2024: 43-56 - Anna Hedström, Leander Weber, Sebastian Lapuschkin, Marina M.-C. Höhne:
A Fresh Look at Sanity Checks for Saliency Maps. xAI (1) 2024: 403-420 - Qi Huang, Emanuele Mezzi, Osman Mutlu, Miltiadis Kofinas, Vidya Prasad, Shadnan Azwad Khan, Elena Ranguelova, Niki van Stein:
Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI. xAI (1) 2024: 308-331 - Benjamin Leblanc, Pascal Germain:
Seeking Interpretability and Explainability in Binary Activated Neural Networks. xAI (1) 2024: 3-20 - Jiayi Li, Sheetal Satheesh, Stefan Heindorf, Diego Moussallem, René Speck, Axel-Cyrille Ngonga Ngomo:
AutoCL: AutoML for Concept Learning. xAI (1) 2024: 117-136 - Oscar Llorente, Rana Fawzy, Jared Keown, Michal Horemuz, Péter Vaderna, Sándor Laki, Roland Kotroczó, Rita Csoma, János Márk Szalai-Gindl:
Evaluating Neighbor Explainability for Graph Neural Networks. xAI (1) 2024: 383-402 - Helena Löfström, Tuwe Löfström:
Conditional Calibrated Explanations: Finding a Path Between Bias and Uncertainty. xAI (1) 2024: 332-355 - Georgii Mikriukov, Gesina Schwalbe, Franz Motzkus, Korinna Bade:
Unveiling the Anatomy of Adversarial Attacks: Concept-Based XAI Dissection of CNNs. xAI (1) 2024: 92-116 - Miquel Miró-Nicolau, Antoni Jaume-i-Capó, Gabriel Moyà-Alcover:
Meta-evaluating Stability Measures: MAX-Sensitivity and AVG-Sensitivity. xAI (1) 2024: 356-369 - Franz Motzkus, Georgii Mikriukov, Christian Hellert, Ute Schmid:
Locally Testing Model Detections for Semantic Global Concepts. xAI (1) 2024: 137-159 - Szymon Oplatek, Dawid Rymarczyk, Bartosz Zielinski:
Revisiting FunnyBirds Evaluation Framework for Prototypical Parts Networks. xAI (1) 2024: 57-68 - Shreyasi Pathak, Jörg Schlötterer, Jeroen Veltman, Jeroen Geerdink, Maurice van Keulen, Christin Seifert:
Prototype-Based Interpretable Breast Cancer Prediction Models: Analysis and Challenges. xAI (1) 2024: 21-42 - Alan Perotti, Claudio Borile, Arianna Miola, Francesco Paolo Nerini, Paolo Baracco, André Panisson:
Explainability, Quantified: Benchmarking XAI Techniques. xAI (1) 2024: 421-444 - Jérôme Rutinowski, Simon Klüttermann, Jan Endendyk, Christopher Reining, Emmanuel Müller:
Benchmarking Trust: A Metric for Trustworthy Machine Learning. xAI (1) 2024: 287-307 - Samuel Sithakoul, Sara Meftah, Clément Feutry:
BEExAI: Benchmark to Evaluate Explainable AI. xAI (1) 2024: 445-468 - Lenka Tetková, Teresa Karen Scheidt, Maria Mandrup Fogh, Ellen Marie Gaunby Jørgensen, Finn Årup Nielsen, Lars Kai Hansen:
Knowledge Graphs for Empirical Concept Retrieval. xAI (1) 2024: 160-183 - Jonas Teufel, Pascal Friederich:
Global Concept Explanations for Graphs by Contrastive Learning. xAI (1) 2024: 184-208 - Julian Tritscher, Philip Lissmann, Maximilian Wolf, Anna Krause, Andreas Hotho, Daniel Schlör:
Generative Inpainting for Shapley-Value-Based Anomaly Explanation. xAI (1) 2024: 230-243 - Luca Longo, Sebastian Lapuschkin, Christin Seifert:
Explainable Artificial Intelligence - Second World Conference, xAI 2024, Valletta, Malta, July 17-19, 2024, Proceedings, Part I. Communications in Computer and Information Science 2153, Springer 2024, ISBN 978-3-031-63786-5 [contents]
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