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PaLI-X:关于扩展多语言视觉与语言模型的研究

PaLI-X: On Scaling up a Multilingual Vision and Language Model

Google Research(谷歌研究院)
Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shake… 展开作者

Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, AJ Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut

AI总结:

本文通过扩大模型组件规模和训练任务混合广度来扩展多语言视觉与语言模型 PaLI-X,在超过25个视觉与语言基准上取得最先进性能,并观察到复杂计数和多语言目标检测等涌现能力。

摘要:

我们介绍了扩展 PaLI-X(一个多语言视觉与语言模型)的训练方案与结果,既包括组件规模的扩大,也包括训练任务混合广度的扩展。我们的模型在广泛多样且复杂的任务上取得了新的性能水平,包括多个基于图像的描述和问答任务、基于图像的文档理解与少样本(上下文内)学习,以及目标检测、视频问答和视频描述。PaLI-X 在所考虑的大多数视觉与语言基准(超过 25 个)上推动了最先进水平。最后,我们观察到了一些涌现能力,例如复杂计数和多语言目标检测,这些任务并未明确包含在训练混合中。

英文摘要:

We present the training recipe and results of scaling up PaLI-X, a multilingual vision and language model, both in terms of size of the components and the breadth of its training task mixture. Our model achieves new levels of performance on a wide-range of varied and complex tasks, including multiple image-based captioning and question-answering tasks, image-based document understanding and few-shot (in-context) learning, as well as object detection, video question answering, and video captioning. PaLI-X advances the state-of-the-art on most vision-and-language benchmarks considered (25+ of them). Finally, we observe emerging capabilities, such as complex counting and multilingual object detection, tasks that are not explicitly in the training mix.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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