Causality-Inspired Fair Representation Learning for Multimodal Recommendation
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Comments In ACM Transactions on Information Systems (TOIS), 2025 (just accepted)
AI 大模型
跨文本、图像、视频、音频等模态的大模型与学习方法。
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Comments In ACM Transactions on Information Systems (TOIS), 2025 (just accepted)
机构 * Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention(上海大气颗粒污染与防治重点实验室) ; National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary(长江入海口湿地生态系统观测与研究站) ; Department of Environmental Science and Engineering(环境科学与工程学院) ; Shanghai Academy of AI for Science (SAIS)(上海人工智能科学研究院) ; MOE Laboratory for National Development and Intelligent Governance(教育部国家发展与智能治理实验室) ; Shanghai Institute for Energy and Carbon Neutrality Strategy(上海能源与碳中和战略研究院) ; IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health(国际减灾与发展研究院风险互联与治理国际联合实验室) ; Shanghai Institute of Eco-Chongming (SIEC)(上海生态崇明研究院) ; Shanghai Environmental Monitoring Center (SEMC)(上海市环境监测中心)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
专题命中 多模态训练与对齐 :cross-modal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
Comments Error in Results. Need to re-run them
专题命中 多模态训练与对齐 :multimodal(title,abstract)
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Comments Accepted by SIGIR 2025
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Comments 9 pages, 6 figures, submitted to GECCO conference
机构 * Cooperative Medianet Innovation Center, Shanghai Jiao Tong University(上海交通大学 cooperative medianet innovation center) ; Nokia Bell Labs(诺基亚贝尔实验室) ; Institute of Intelligent Communications and Network Security, Chongqing University of Posts and Telecommunications(重庆邮电大学智能通信与网络安全研究所)
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
机构 * Aix-Marseille Univ(艾克斯-马赛大学) ; LIS(实验室) ; IRD(法国国家科研 Institute) ; ESPACE-DEV
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Journal ref Proceedings of The 28th International Conference on Artificial Intelligence and Statistics 2025, in Proceedings of Machine Learning Research 258:3142-3150 Available from https://proceedings.mlr.press/v258/bezirganyan25a.html
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
机构 * Department of Electrical Engineering, École de technologie supérieure, Montréal, Canada(电气工程系,超技术学院,蒙特利尔,加拿大)
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
Comments Presented at AI for Accelerated Materials Design(AI4Mat), ICLR 2025 (https://openreview.net/forum?id=pN4Zg6HBlq#discussion)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Comments Accepted by ICLR 2025 (https://openreview.net/forum?id=rbnf7oe6JQ)
机构 * Department of Aerospace Engineering and Engineering Mechanics , University of Texas at Austin(航空航天工程与工程力学系,德克萨斯大学奥斯汀分校)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
机构 * Lenovo Research(联想研究院)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
机构 * Institute of Automation, Chinese Academy of Sciences(中国科学院自动化研究所) ; Robotics Institute, Carnegie Mellon University(卡内基梅隆大学机器人研究所) ; School of Artificial Intelligence, University of Chinese Academy of Sciences(中国科学院大学人工智能学院)
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Comments 16 pages, 7 figures. Preliminary version; work in progress
专题命中 多模态训练与对齐 :multimodal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Comments Accepted by Design Automation Conference (DAC), 2025
专题命中 多模态训练与对齐 :multi-modal(title,abstract)
Comments After further review, we believe the content of the paper is not yet fully ready and requires additional time for improvement. To ensure quality, we have decided to withdraw this preprint
专题命中 多模态训练与对齐 :cross-modal(title,abstract)
专题命中 多模态训练与对齐 :multimodal(title,abstract)
Comments Accepted at CVPR2025