ZhiYuan Research Institute Releases 1 Billion Parameter General 3D Vision Model Uni3D


["ZhiYuan Research Institute has released the new generation multimodal foundation model Emu2, pushing the boundaries of multimodal contextual learning capabilities.", "Emu2 surpasses Flamingo-80B and IDEFICS-80B, demonstrating excellent performance in few-shot multimodal understanding tasks.", "Emu2 achieves optimal performance in multiple few-shot understanding, visual question answering, and image generation tasks.", "Emu2-Chat realizes accurate understanding of text-image instructions, while Emu2-Gen offers flexible, controllable, high-quality images."]
ZhiYuan Research Institute has open-sourced the JudgeLM evaluation model, which can efficiently assess various large models and provide scores. Compared to GPT-4, JudgeLM's cost is only 1/120, with a consistency rate of over 90% for evaluation results. JudgeLM can be applied in various assessment scenarios including pure text and multimodal contexts, generating scores and justifying reasons. The consistency of JudgeLM with reference answers exceeds 90%, approaching human performance. ZhiYuan Research Institute has also released datasets for training and validation samples for in-depth research on large models.
ZhiYuan Research Institute has unveiled the new open-source bilingual model Wudao・Tianying 34 Billion Aquila2-34B, which excels in reasoning, generalization, and more. The institute has also released a comprehensive open-source toolkit to promote collaborative innovation in large model research. Aquila2-34B surpasses other open-source foundational models in overall capabilities, with the ZhiYuan team developing the NLPE method to enhance the model's extension capabilities.
The ZhiYuan Research Institute has released the world's largest Chinese-English semantic vector model training dataset, MTP, with a data scale of 300 million pairs. MTP is the largest open-source dataset of Chinese-English related text pairs, providing an important foundation for training semantic vector models. The dataset includes Chinese-English text pairs from multiple sources, covering various types such as Q&A, comments, and news. The ZhiYuan Research Institute stated that this data plays a crucial role in training large models and will promote collaborative innovation in artificial intelligence. The release of this dataset is expected to address the shortage of training datasets for Chinese models.
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