TerraMind: Large-Scale Generative Multimodality for Earth Observation
TerraMind:面向地球观测的大规模生成式多模态模型
Johannes Jakubik, Felix Yang, Benedikt Blumenstiel, Erik Scheurer, Rocco Sedona, Stefano Maurogiovanni, Jente Bosmans, Nikolaos Dionelis, Valerio Marsocci, Niklas Kopp, Rahul Ramachandran, Paolo Fraccaro, Thomas Brunschwiler, Gabriele Cavallaro, Juan Bernabe-Moreno, Nicolas Longépé
机构
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IBM Research – Europe(IBM欧洲研究院)
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ETH Zurich(苏黎世联邦理工学院)
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Forschungszentrum Jülich(尤利希研究中心)
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European Space Agency(欧洲航天局)
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Φ \Phi -Lab(Φ实验室)
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NASA IMPACT
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University of Iceland(爱沙尼亚大学)
专题命中
多模态训练与对齐
:multimodal(abstract);cross-modal(abstract);any-to-any(abstract);multimodal foundation model(abstract)
CommentsOur original goal was to use Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection (arXiv:2506.19420) to replace Commander-GPT: Fully Unleashing the Sarcasm Detection Capability of Multi-Modal Large Language Models (arXiv:2503.18681). Due to various reasons, both versions were released, so we would like to withdraw the latter
LF${}^{2}$AR: Accounting for Layerwise Dynamics to Improve Multimodal Adaptation of Language Models
LF²AR:考虑分层动态以改进语言模型的多模态适配
Santiago Cuervo, Adel Moumen, Yanis Labrak, Sameer Khurana, Antoine Laurent, Mickael Rouvier, Phil Woodland, Ricard Marxer
机构
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Université de Toulon, Aix-Marseille Université, CNRS, LIS, France(法国图卢兹大学、马赛大学、CNRS、LIS)
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Department of Engineering, University of Cambridge, UK(剑桥大学工程系)
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Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA(三菱电机研究实验室(MERL))
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LIA, Avignon Université, France(法国阿维尼翁大学LIA)
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LIUM, Le Mans Université, France(法国勒芒大学LIUM)
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Zenidoc, Marseille, France(法国马赛Zenidoc)