{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:38:15Z","timestamp":1763192295026,"version":"3.45.0"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/ijcnn64981.2025.11228092","type":"proceedings-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T18:46:15Z","timestamp":1763145975000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["Muppet: A Modular and Constructive Decomposition for Perturbation-Based Explanation Methods"],"prefix":"10.1109","author":[{"given":"Quentin","family":"Ferr\u00e9","sequence":"first","affiliation":[{"name":"Euranova,Marseille,13006"}]},{"given":"Ismail","family":"Bachchar","sequence":"additional","affiliation":[{"name":"Euranova,Marseille,13006"}]},{"given":"Hakima","family":"Arroubat","sequence":"additional","affiliation":[{"name":"Euranova,Marseille,13006"}]},{"given":"Aziz","family":"Jedidi","sequence":"additional","affiliation":[{"name":"Euranova,Marseille,13006"}]},{"given":"Youssef","family":"Achenchabe","sequence":"additional","affiliation":[{"name":"Euranova,Marseille,13006"}]},{"given":"Antoine","family":"Bonnefoy","sequence":"additional","affiliation":[{"name":"Euranova,Marseille,13006"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1312"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.12.012"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0048-x"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/iccv.2017.74"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00304"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3051315"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.371"},{"key":"ref8","article-title":"Real time image saliency for black box classifiers","volume":"30","author":"Dabkowski","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9413046"},{"journal-title":"Rise: Randomized input sampling for explanation of black-box models","year":"2018","author":"Petsiuk","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.10.013"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108102"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-28954-6_9"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2021.06.030"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939778"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3321\/j.issn:0529-6579.2007.z1.029"},{"issue":"1","key":"ref17","first-page":"9477","article-title":"Explaining by removing: A unified framework for model explanation","volume":"22","author":"Covert","year":"2021","journal-title":"The Journal of Machine Learning Research"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2024.104101"},{"journal-title":"Captum: A unified and generic model interpretability library for pytorch","year":"2020","author":"Kokhlikyan","key":"ref19"},{"journal-title":"One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques","year":"2019","author":"Arya","key":"ref20"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i11.21540"},{"article-title":"Omnixai: A library for explainable ai.(2022)","year":"2022","author":"Yang","key":"ref22"},{"key":"ref23","first-page":"799","article-title":"What went wrong and when? instance-wise feature importance for time-series black-box models","volume":"33","author":"Tonekaboni","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19775-8_19"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00020"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-023-01773-2"},{"article-title":"A unified approach to interpreting model predictions","volume-title":"31st Conference on Neural Information Processing Systems (NIPS 2017)","author":"Lundberg","key":"ref27"},{"issue":"34","key":"ref28","first-page":"1","article-title":"Quantus: An explainable ai toolkit for responsible evaluation of neural network explanations and beyond","volume":"24","author":"Hedstr\u00f6m","year":"2023","journal-title":"Journal of Machine Learning Research"},{"year":"2020","key":"ref29","article-title":"Dry Bean"},{"first-page":"2009","article-title":"ImageNet-Sample(1000)","author":"Deng","key":"ref30"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/417"},{"article-title":"Towards robust interpretability with self-explaining neural networks","year":"2018","author":"Alvarez-Melis","key":"ref32"},{"journal-title":"Irof: a low resource evaluation metric for explanation methods","year":"2020","author":"Rieger","key":"ref33"},{"key":"ref34","first-page":"9046","article-title":"When explanations lie: Why many modified bp attributions fail","volume-title":"International conference on machine learning","author":"Sixt"},{"key":"ref35","first-page":"1383","article-title":"Concise explanations of neural networks using adversarial training","volume-title":"International conference on machine learning","author":"Chalasani"}],"event":{"name":"2025 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2025,6,30]]},"location":"Rome, Italy","end":{"date-parts":[[2025,7,5]]}},"container-title":["2025 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11227166\/11227148\/11228092.pdf?arnumber=11228092","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:33:49Z","timestamp":1763192029000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11228092\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/ijcnn64981.2025.11228092","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}