{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:59:57Z","timestamp":1762325997720,"version":"build-2065373602"},"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":[[2025,11]]},"abstract":"<jats:p>An argument can be seen as a pair of premises and a claim they support.\n\nHuman arguments are often approximate, with some premises left implicit, leading to an implicit inference of the claim, i.e., forming enthymemes. \n\nTo better understand and use them, we must decode these approximate enthymemes, typically by identifying missing premises to make the inference explicit, and, as we propose, by also removing irrelevant content to improve argument quality in specific contexts.\n\nOften, multiple decodings of an enthymeme are possible. \n\nHowever, no formal method has yet been proposed for identifying higher-quality decodings. \n\nTo pave the way, we introduce six types of criteria for evaluating aspects of decodings. \n\nThen, we introduce the concept of a criterion measure, designed to evaluate decodings based on a specific criterion. \n\nIn parallel, we define desirable properties for criterion measures, referred to as axioms, and we systematically evaluate our criterion measures with respect to them.\n\nFinally, we introduce the notion of quality measure that combine specific criterion measures to give an overall evaluation of the quality of decodings.<\/jats:p>","DOI":"10.24963\/kr.2025\/11","type":"proceedings-article","created":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:10:44Z","timestamp":1762323044000},"page":"110-120","source":"Crossref","is-referenced-by-count":0,"title":["An Axiomatic Study of a Modular Evaluation of Enthymeme Decoding in Weighted Structured Argumentation"],"prefix":"10.24963","author":[{"given":"Jonathan","family":"Ben-Naim","sequence":"first","affiliation":[{"name":"CNRS"},{"name":"Universit\u00e9 Paul Sabatier"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Victor","family":"David","sequence":"additional","affiliation":[{"name":"Inria"},{"name":"Universit\u00e9 C\u00f4te d'Azur"},{"name":"CNRS"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anthony","family":"Hunter","sequence":"additional","affiliation":[{"name":"UCL"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"22nd International Conference on Principles of Knowledge Representation and Reasoning {KR-2025}","theme":"Artificial Intelligence","location":"Melbourne, Australia","acronym":"KR-2025","number":"22","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","Academic College of Tel-Aviv","European Association for Artificial Intelligence","National Science Foundation"],"start":{"date-parts":[[2025,11,11]]},"end":{"date-parts":[[2025,11,17]]}},"container-title":["Proceedings of the TwentySecond International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:10:53Z","timestamp":1762323053000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2025\/11"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2025\/11","relation":{},"subject":[],"published":{"date-parts":[[2025,11]]}}}