{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:04:59Z","timestamp":1784203499464,"version":"3.55.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:p>We address the fundamental task of computing rigorous, sample-based abductive explanations for machine learning predictions. In this setting, we propose a new class of explanations derived from a generalization of the consensus operation in propositional logic. We prove that these explanations are precisely those that satisfy a monotonicity property ensuring they remain valid as the sample grows. Furthermore, we show that their computation can be performed efficiently. As a direct application, we also show how these explanations can be used to identify necessary and relevant features. The proposed framework provides a robust and scalable approach to formal model-agnostic XAI.<\/jats:p>","DOI":"10.24963\/kr.2026\/98","type":"proceedings-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T11:15:53Z","timestamp":1784200553000},"page":"1046-1056","source":"Crossref","is-referenced-by-count":0,"title":["Model-Agnostic Explanations by Consensus"],"prefix":"10.24963","author":[{"given":"Carlos","family":"Menc\u00eda","sequence":"first","affiliation":[{"name":"Universidad de Oviedo, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramon","family":"B\u00e9jar","sequence":"additional","affiliation":[{"name":"Universitat de Lleida, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ra\u00fal","family":"Menc\u00eda","sequence":"additional","affiliation":[{"name":"Universidad de Oviedo, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joao","family":"Marques-Silva","sequence":"additional","affiliation":[{"name":"ICREA & Universitat de Lleida, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"23nd International Conference on Principles of Knowledge Representation and Reasoning {KR-2026}","theme":"Artificial Intelligence","location":"Lisbon, Portuagal","acronym":"KR-2026","number":"23","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","European Association for Artificial Intelligence"],"start":{"date-parts":[[2026,7,20]]},"end":{"date-parts":[[2026,7,18]]}},"container-title":["Proceedings of the TwentyThird International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T11:16:19Z","timestamp":1784200579000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2026\/98"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2026\/98","relation":{},"subject":[],"published":{"date-parts":[[2026,7]]}}}