{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T15:00:12Z","timestamp":1790175612514,"version":"4.1.0"},"reference-count":28,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010418","name":"Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government","doi-asserted-by":"publisher","award":["RS-2024-00394920"],"award-info":[{"award-number":["RS-2024-00394920"]}],"id":[{"id":"10.13039\/501100010418","id-type":"DOI","asserted-by":"publisher"}]},{"award":["RS-2024-00394920"],"award-info":[{"award-number":["RS-2024-00394920"]}],"id":[{"id":"https:\/\/ror.org\/01g0hqq23","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Federated learning under label skew aggregates models trained with different local class distributions. Local logit adjustment can reduce class-dependent bias, but the adjusted loss updates both the encoder and classifier in client-specific directions. StabFL optimizes a joint local objective that combines logit-adjusted classification loss, full-model proximal regularization, and supervised contrastive learning with a client-local queue. The queue retains recent labeled projected representations and extends the comparison set available to small mini-batches. Across CIFAR-10 and PAMAP2, StabFL reaches 85.57\u00b11.36% and 75.76\u00b13.21% accuracy on CIFAR-10 under moderate and severe label skew, and 83.21\u00b10.46% and 74.68\u00b14.10% on PAMAP2 under the same skew levels. Compared with StabFL w\/o Queue, the client-local queue raises mean accuracy by 0.39 and 1.66 percentage points on CIFAR-10 and by 1.76 and 4.44 percentage points on PAMAP2 while transmitting no queued projected representations, labels, or local class priors.<\/jats:p>","DOI":"10.3390\/s26196033","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T14:03:26Z","timestamp":1790172206000},"page":"6033","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["StabFL: Stabilized Logit Adjustment with Queue-Augmented Representation Learning for Label-Skewed Federated Learning"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-9483-0010","authenticated-orcid":false,"given":"Yujin","family":"Shin","sequence":"first","affiliation":[{"name":"School of Integrated Technology, College of Computing, Yonsei University, Seoul 03722, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6588-2986","authenticated-orcid":false,"given":"Suhan","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Mobile Systems Engineering, PRIMUS International College, Yongin 16890, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6631-6938","authenticated-orcid":false,"given":"JaeYeon","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Mobile Systems Engineering, PRIMUS International College, Yongin 16890, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"ref_1","unstructured":"McMahan, B., Moore, E., Ramage, D., Hampson, S., and y Arcas, B.A. (2017, January 20\u201322). 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