Language instruction plays an essential role in the natural language groundednavigation tasks . We propose a DynamicReinforced Instruction Attacker (DR-Attacker) which learns to mislead thenavigator to move to the wrong target by destroying the most instructive information in instructions at different timesteps . DR-Attacker is optimized by the reinforcement learning algorithm to generate perturbed instructions sequentially during the navigation, according to a learnable attack score . The proposed method is overstate-of-the-art and shows the superiority of our proposed method over state-of the-art methods . Code is available at https://://:// is available in the source of the proposed DR-ATTACKER and the code is available to download at http://

Author(s) : Bingqian Lin, Yi Zhu, Yanxin Long, Xiaodan Liang, Qixiang Ye, Liang Lin

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Keywords : attacker - dr - proposed - da - instruction -

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