{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T08:39:14Z","timestamp":1771922354828,"version":"3.50.1"},"reference-count":85,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"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":[[2025,10,19]]},"DOI":"10.1109\/iccvw69036.2025.00653","type":"proceedings-article","created":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T20:44:02Z","timestamp":1771879442000},"page":"6280-6291","source":"Crossref","is-referenced-by-count":0,"title":["Multi-Objective Optimization for Deep Neural Network Calibration"],"prefix":"10.1109","author":[{"given":"Dexter","family":"Neo","sequence":"first","affiliation":[{"name":"School of Computing, National University of Singapore"}]},{"given":"Tsuhan","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computing, National University of Singapore"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2867350"},{"key":"ref2","article-title":"The iWildCam 2020 competition dataset","volume":"abs\/2004.10340","author":"Beery","year":"2020","journal-title":"arXiv"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007379606734"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00516"},{"key":"ref5","first-page":"794","article-title":"GradNorm: Gradient normalization for adaptive loss balancing in deep multitask networks","volume-title":"Proceedings of the 35th International Conference on Machine Learning","author":"Chen","year":"2018"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01334"},{"key":"ref7","article-title":"On the limitations of temperature scaling for distributions with overlaps","volume-title":"The Twelfth International Conference on Learning Representations","author":"Chidambaram","year":"2024"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00646"},{"key":"ref9","first-page":"14609","article-title":"Human-aligned calibration for ai-assisted decision making","volume-title":"Advances in Neural Information Processing Systems","author":"Corvelo Benz","year":"2023"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref11","article-title":"You only train once: Loss-conditional training of deep networks","volume-title":"8th International Conference on Learning Representations, ICLR 2020","author":"Dosovitskiy","year":"2020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.crma.2012.03.014"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/nature21056"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s001860000043"},{"key":"ref15","first-page":"1583","article-title":"Adafocal: Calibration-aware adaptive focal loss","author":"Ghosh","year":"2022","journal-title":"Ad-vances in Neural Information Processing Systems"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2943604"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00151"},{"key":"ref18","first-page":"8618","article-title":"Better uncertainty calibration via proper scores for classification and beyond","volume-title":"Advances in Neural Information Processing Systems","author":"Gruber","year":"2022"},{"key":"ref19","first-page":"1321","article-title":"On calibration of modern neural networks","volume-title":"Proceedings of the 34th International Conference on Machine Learning","author":"Guo","year":"2017"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01270-0_17"},{"key":"ref21","article-title":"Calibration of neural networks using splines","volume-title":"9th International Conference on Learning Representations, ICLR 2021","author":"Gupta","year":"2021"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-21606-5"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01561"},{"key":"ref25","article-title":"Benchmarking neural network robustness to common corruptions and perturbations","volume-title":"7th International Conference on Learning Representations, ICLR 2019","author":"Hendrycks","year":"2019"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRev.106.620"},{"key":"ref27","article-title":"To trust or not to trust a classifier","volume-title":"Advances in Neural Information Processing Systems","author":"Jiang","year":"2018"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i12.26742"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295309"},{"key":"ref30","article-title":"Multi-task learning using uncertainty to weigh losses for scene geometry and semantics","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Kendall","year":"2018"},{"key":"ref31","article-title":"Auto-encoding variational bayes","volume-title":"2nd International Conference on Learning Representations, ICLR 2014","author":"Kingma","year":"2014"},{"key":"ref32","first-page":"5637","article-title":"Wilds: A bench-mark of in-the-wild distribution shifts","volume-title":"Proceedings of the 38th International Conference on Machine Learning","author":"Wei Koh","year":"2021"},{"key":"ref33","volume-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref34","first-page":"11683","article-title":"Calibrated and sharp uncertainties in deep learning via density estimation","volume-title":"Proceedings of the 39th International Conference on Machine Learning","author":"Kuleshov","year":"2022"},{"key":"ref35","article-title":"Polyloss: A polynomial expansion perspective of classification loss functions","volume-title":"The Tenth International Conference on Learning Representations, ICLR 2022","author":"Leng","year":"2022"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10847"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref38","first-page":"12037","article-title":"Pareto multi-task learning","volume-title":"Advances in Neural Information Processing Systems","author":"Lin","year":"2019"},{"key":"ref39","first-page":"18878","article-title":"Conflict-averse gradient descent for multi-task learning","volume-title":"Advances in Neural Information Processing Systems","author":"Liu","year":"2021"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00018"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01542"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00321"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00197"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01558"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01170"},{"key":"ref46","first-page":"7034","article-title":"Confidence-aware learning for deep neural networks","volume-title":"Proceedings of the 37th International Conference on Machine Learning","author":"Moon","year":"2020"},{"key":"ref47","first-page":"15288","article-title":"Calibrating deep neural networks using focal loss","volume-title":"Advances in Neural Information Processing Systems","author":"Mukhoti","year":"2020"},{"key":"ref48","article-title":"When does label smoothing help?","volume-title":"Advances in Neural Information Processing Systems","author":"M\u00fcller","year":"2019"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01104"},{"key":"ref50","first-page":"71619","article-title":"Cal-detr: Calibrated detection transformer","volume-title":"Advances in Neural Information Processing Systems","author":"Akhtar Munir","year":"2023"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72691-0_9"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9602"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i19.30143"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1182"},{"key":"ref55","article-title":"Measuring calibration in deep learning","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops","author":"Nixon","year":"2019"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00131"},{"key":"ref57","article-title":"Can you trust your model\u2019s uncertainty? evaluating predictive uncertainty under dataset shift","volume-title":"Advances in Neural Information Processing Systems","author":"Ovadia","year":"2019"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00364"},{"key":"ref59","article-title":"Regularizing neural networks by penalizing confident output distributions","volume":"abs\/1701.06548","author":"Pereyra","year":"2017","journal-title":"arXiv"},{"key":"ref60","article-title":"Probabilistic outputs for svms and comparisons to regularized likelihood methods","author":"Platt","year":"2007","journal-title":"Advances in Large Margin Classifiers"},{"key":"ref61","article-title":"On fairness and calibration","volume-title":"Advances in Neural Information Processing Systems","author":"Pleiss","year":"2017"},{"key":"ref62","first-page":"4036","article-title":"Mitigating bias in calibration error estimation","volume-title":"Proceedings of The 25th International Conference on Artificial Intelligence and Statistics","author":"Roelofs","year":"2022"},{"key":"ref63","first-page":"62657","article-title":"Distributionally robust ensemble of lottery tickets towards calibrated sparse network training","volume-title":"Advances in Neural Information Processing Systems","author":"Sapkota","year":"2023"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1023\/A:1015472306888"},{"key":"ref65","article-title":"Multi-task learning as multi-objective optimization","volume-title":"Advances in Neural Information Processing Systems","author":"Sener","year":"2018"},{"key":"ref66","article-title":"Towards out-of-distribution generalization: A survey","volume":"abs\/2108.13624","author":"Shen","year":"2021","journal-title":"ArXiv"},{"key":"ref67","first-page":"33833","article-title":"Dual focal loss for calibration","volume-title":"Proceedings of the 40th International Conference on Machine Learning","author":"Tao","year":"2023"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.2172\/1525811"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr46437.2021.00999"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19778-9_32"},{"key":"ref71","first-page":"34344","article-title":"Beyond in-domain scenarios: Robust density-aware calibration","volume-title":"Proceedings of the 40th In-ternational Conference on Machine Learning","author":"Tomani","year":"2023"},{"key":"ref72","first-page":"2215","article-title":"On calibration and out-of-domain generalization","volume-title":"Advances in Neural Information Processing Systems","author":"Wald","year":"2021"},{"key":"ref73","first-page":"11809","article-title":"Rethinking calibration of deep neural networks: Do not be afraid of overconfidence","volume-title":"Advances in Neural Information Processing Systems","author":"Wang","year":"2021"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00735"},{"key":"ref75","first-page":"178","article-title":"Non-parametric calibration for classification","volume-title":"In Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics","author":"Wenger","year":"2020"},{"key":"ref76","first-page":"4509","article-title":"Direction-oriented multi-objective learning: Simple and provable stochastic algorithms","volume-title":"Advances in Neural Information Processing Systems","author":"Xiao","year":"2023"},{"key":"ref77","first-page":"68511","article-title":"Proximity-informed calibration for deep neural networks","volume-title":"Advances in Neural Information Processing Systems","author":"Xiong","year":"2023"},{"key":"ref78","first-page":"58448","article-title":"Beyond probability partitions: Calibrating neural networks with semantic aware grouping","volume-title":"Advances in Neural Information Processing Systems","author":"Yang","year":"2023"},{"key":"ref79","first-page":"27510","article-title":"Robust calibration with multi-domain temperature scaling","volume-title":"Advances in Neural Information Processing Systems","author":"Yu","year":"2022"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00391"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7502-7_79-1"},{"key":"ref82","first-page":"11117","article-title":"Mix-n-match: Ensemble and compositional methods for uncer-tainty calibration in deep learning","volume-title":"Proceedings of the 37th International Conference on Machine Learning","author":"Zhang","year":"2020"},{"key":"ref83","first-page":"26135","article-title":"When and how mixup improves calibration","volume-title":"Proceedings of the 39th International Conference on Machine Learning","author":"Zhang","year":"2022"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3070203"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1201\/b12207"}],"event":{"name":"2025 IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW)","location":"Honolulu, HI, USA","start":{"date-parts":[[2025,10,19]]},"end":{"date-parts":[[2025,10,20]]}},"container-title":["2025 IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11373940\/11374285\/11375484.pdf?arnumber=11375484","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T07:34:29Z","timestamp":1771918469000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11375484\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,19]]},"references-count":85,"URL":"https:\/\/doi.org\/10.1109\/iccvw69036.2025.00653","relation":{},"subject":[],"published":{"date-parts":[[2025,10,19]]}}}