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Fudan and NTU propose SimpleVLN, using a native multimodal large model to set a new SOTA in vision-language navigation

A team from Fudan University and Nanyang Technological University, Singapore, proposed SimpleVLN, which performs vision-language navigation without changing the core structure of the multimodal large model or adding dedicated navigation modules, relying only on historical frame selection, action-chunk decision-making, and three-stage training with SFT, DAgger, and reinforcement learning.

Part of the event: Fudan and Nanyang Technological University propose SimpleVLN navigation method

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