{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T15:56:48Z","timestamp":1781539008068,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,6,16]]},"DOI":"10.1145\/3805622.3810630","type":"proceedings-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T14:42:57Z","timestamp":1781534577000},"page":"1138-1146","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["PCMA: Prompt-guided Cross-domain Multi-prototype Alignment for Source-Free Domain Adaptation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-1300-7829","authenticated-orcid":false,"given":"Kaicheng","family":"Peng","sequence":"first","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3095-3707","authenticated-orcid":false,"given":"Ya","family":"Li","sequence":"additional","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,15]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Muhammad Awais Muzammal Naseer Salman Khan Rao\u00a0Muhammad Anwer Hisham Cholakkal Mubarak Shah Ming-Hsuan Yang and Fahad\u00a0Shahbaz Khan. 2024. Foundation Models Defining a New Era in Vision: A Survey and Outlook. TPAMI 47 (2024) 2245\u20132264.","DOI":"10.1109\/TPAMI.2024.3506283"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i2.27830"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00039"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02206"},{"key":"e_1_3_3_1_6_2","volume-title":"ICML","author":"Ganin Yaroslav","year":"2015","unstructured":"Yaroslav Ganin and Victor Lempitsky. 2015. Unsupervised Domain Adaptation by Backpropagation. In ICML."},{"key":"e_1_3_3_1_7_2","unstructured":"Chunjiang Ge Rui Huang Mixue Xie Zihang Lai Shiji Song Shuang Li and Gao Huang. 2023. Domain Adaptation via Prompt Learning. TNNLS 35 (2023) 1\u201311."},{"key":"e_1_3_3_1_8_2","volume-title":"NeurIPS","author":"Han Bo","year":"2018","unstructured":"Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, and Masashi Sugiyama. 2018. Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels. In NeurIPS."},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00297"},{"key":"e_1_3_3_1_12_2","volume-title":"ICCV","author":"Lai Zhengfeng","year":"2023","unstructured":"Zhengfeng Lai, Noranart Vesdapunt, Ning Zhou, Jun Wu, and Baoxin Li. 2023. PADCLIP: Pseudo-labeling with Adaptive Debiasing in CLIP. In ICCV."},{"key":"e_1_3_3_1_13_2","volume-title":"ICML Workshop","author":"Lee Dong-Hyun","year":"2013","unstructured":"Dong-Hyun Lee. 2013. Pseudo-Label: The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks. In ICML Workshop."},{"key":"e_1_3_3_1_14_2","volume-title":"ICML","author":"Lee Sungho","year":"2022","unstructured":"Sungho Lee, Taekyung Kim, and Chanho Kim. 2022. Confidence Score for Source-Free Unsupervised Domain Adaptation. In ICML."},{"key":"e_1_3_3_1_15_2","volume-title":"ICML","author":"Liang Jian","year":"2020","unstructured":"Jian Liang, Dapeng Hu, and Jiashi Feng. 2020. Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation. In ICML."},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00738"},{"key":"e_1_3_3_1_17_2","volume-title":"ICML","author":"Long Mingsheng","year":"2015","unstructured":"Mingsheng Long, Yue Cao, Jianmin Wang, and Michael\u00a0I. Jordan. 2015. Learning Transferable Features with Deep Adaptation Networks. In ICML."},{"key":"e_1_3_3_1_18_2","volume-title":"ICLR","author":"Loshchilov Ilya","year":"2017","unstructured":"Ilya Loshchilov and Frank Hutter. 2017. SGDR: Stochastic Gradient Descent with Warm Restarts. In ICLR."},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"crossref","unstructured":"Jiawen Peng Jiaxin Chen Rong Pan and Andy\u00a0J. Ma. 2025. Language-guided Alignment and Distillation for Source-free Domain Adaptation. Neurocomputing 648 (2025) 130501.","DOI":"10.1016\/j.neucom.2025.130501"},{"key":"e_1_3_3_1_20_2","unstructured":"Xingchao Peng Ben Usman Neez Kaber Judy Hoffman and Kate Saenko. 2017. VisDA: The Visual Domain Adaptation Challenge. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1710.06924 (2017)."},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19830-4_10"},{"key":"e_1_3_3_1_22_2","volume-title":"ICML","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong\u00a0Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021. Learning Transferable Visual Models From Natural Language Supervision. In ICML."},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.5555\/1888089.1888106"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW60793.2023.00470"},{"key":"e_1_3_3_1_25_2","volume-title":"NeurIPS","author":"Snell Jake","year":"2017","unstructured":"Jake Snell, Kevin Swersky, and Richard Zemel. 2017. Prototypical Networks for Few-shot Learning. In NeurIPS."},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"crossref","unstructured":"Song Tang An Chang Fabian Zhang Xiatian Zhu Mao Ye and Changshui Zhang. 2024. Source-Free Domain Adaptation via Target Prediction Distribution Searching. IJCV 132 (2024) 654\u2013672.","DOI":"10.1007\/s11263-023-01892-w"},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636206"},{"key":"e_1_3_3_1_28_2","volume-title":"ICLR","author":"Tang Song","year":"2025","unstructured":"Song Tang, Wenxin Su, Yan Gan, Mao Ye, Jianwei Zhang, and Xiatian Zhu. 2025. Proxy Denoising for Source-Free Domain Adaptation. In ICLR."},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02238"},{"key":"e_1_3_3_1_30_2","volume-title":"NeurIPS","author":"Tarvainen Antti","year":"2017","unstructured":"Antti Tarvainen and Harri Valpola. 2017. Mean Teachers are Better Role Models: Weight-averaged Consistency Targets Improve Semi-supervised Learning Results. In NeurIPS."},{"key":"e_1_3_3_1_31_2","unstructured":"Aaron van\u00a0den Oord Yazhe Li and Oriol Vinyals. 2018. Representation Learning with Contrastive Predictive Coding. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1807.03748 (2018)."},{"key":"e_1_3_3_1_32_2","unstructured":"Laurens van\u00a0der Maaten and Geoffrey Hinton. 2008. Visualizing Data using t-SNE. JMLR 9 (2008) 2579\u20132605."},{"key":"e_1_3_3_1_33_2","volume-title":"NeurIPS","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All You Need. In NeurIPS."},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"e_1_3_3_1_35_2","volume-title":"NeurIPS","author":"Yang Shiqi","year":"2021","unstructured":"Shiqi Yang, Yaxing Wang, Joost van\u00a0de Weijer, Luis Herranz, and Shangling Jui. 2021. Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation. In NeurIPS."},{"key":"e_1_3_3_1_36_2","volume-title":"NeurIPS","author":"Yang Shiqi","year":"2022","unstructured":"Shiqi Yang, Yaxing Wang, Joost van\u00a0de Weijer, Luis Herranz, and Shangling Jui. 2022. Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation. In NeurIPS."},{"key":"e_1_3_3_1_37_2","volume-title":"CVPR","author":"Yi Shuaicheng","year":"2023","unstructured":"Shuaicheng Yi, Yonggang Li, Zhen Li, and Yongming Guo. 2023. Source-Free Domain Adaptation via Target Entropy Regularization. In CVPR."},{"key":"e_1_3_3_1_38_2","volume-title":"NeurIPS","author":"Zhou Dengyong","year":"2003","unstructured":"Dengyong Zhou, Olivier Bousquet, Thomas\u00a0N. Lal, Jason Weston, and Bernhard Sch\u00f6lkopf. 2003. Learning with Local and Global Consistency. In NeurIPS."},{"key":"e_1_3_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01631"},{"key":"e_1_3_3_1_40_2","doi-asserted-by":"crossref","unstructured":"Kaiyang Zhou Jingkang Yang Chen\u00a0Change Loy and Ziwei Liu. 2022. Learning to Prompt for Vision-Language Models. IJCV 130 (2022) 2337\u20132348.","DOI":"10.1007\/s11263-022-01653-1"},{"key":"e_1_3_3_1_41_2","doi-asserted-by":"crossref","unstructured":"Lihua Zhou Nianxin Li Mao Ye Xiatian Zhu and Song Tang. 2024. Source-free Domain Adaptation with Class Prototype Discovery. Pattern Recognition 145 (2024) 109974.","DOI":"10.1016\/j.patcog.2023.109974"}],"event":{"name":"ICMR '26: International Conference on Multimedia Retrieval","location":"Amsterdam The Netherlands","acronym":"ICMR '26","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 2026 International Conference on Multimedia Retrieval"],"original-title":[],"deposited":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T15:33:16Z","timestamp":1781537596000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3805622.3810630"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,15]]},"references-count":40,"alternative-id":["10.1145\/3805622.3810630","10.1145\/3805622"],"URL":"https:\/\/doi.org\/10.1145\/3805622.3810630","relation":{},"subject":[],"published":{"date-parts":[[2026,6,15]]},"assertion":[{"value":"2026-06-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}