{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:37:22Z","timestamp":1761176242397,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Conformal prediction, as an emerging uncertainty quantification technique, typically functions as post-hoc processing for the outputs of trained classifiers. To optimize the classifier for maximum predictive efficiency, Conformal Training rectifies the training objective of base classifiers with a regularization that minimizes the average prediction set size at a specific error rate. However, the regularization term inevitably deteriorates the classification accuracy of classifiers, thereby leading to suboptimal efficiency of conformal predictors. To address this issue, we introduce Conformal Adapter (C-Adapter), an adapter-based tuning method to enhance the efficiency of conformal predictors without sacrificing accuracy. In particular, we implement the adapter as a class of intra order-preserving functions and tune it with our proposed loss that maximizes the discriminability of non-conformity scores between correctly and randomly matched data-label pairs. Using C-Adapter, the model tends to produce higher non-conformity scores for incorrect labels than for correct ones, thereby enhancing predictive efficiency across different coverage rates. Extensive experiments demonstrate that C-Adapter can effectively adapt various classifiers for efficient conformal prediction sets, as well as enhance the conformal training method.<\/jats:p>","DOI":"10.3233\/faia251208","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:54:40Z","timestamp":1761126880000},"source":"Crossref","is-referenced-by-count":0,"title":["C-Adapter: Adapting Deep Classifiers for Efficient Conformal Prediction Sets"],"prefix":"10.3233","author":[{"given":"Kangdao","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Computer and Information Science, University of Macau"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Statistics and Data Science, Southern University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianguo","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Computing and Data Science, Nanyang Technological University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huiping","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Shien-Ming Wu School of Intelligent Engineering, Nanyang Technological University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chi-Man","family":"Vong","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, University of Macau"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxin","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Statistics and Data Science, Southern University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251208","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:54:40Z","timestamp":1761126880000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251208"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251208","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}