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In the field of Embodied Instructions Following (EIF), the agent needs to understand instructions and execute sequential of subtasks involving interaction with objects and state changes of environment. Our work is done in the context of the ALFRED benchmark. ALFRED (The Action Learning from Realistic Environments and Directives) Benchmark is one of the embodied AI datasets that provides numerous language instruction data and interactive simulation environment, therefore allowing developers to test their agent’s ability to follow instruction in known and unknown environment In ALFRED, the agent needs to follow the natural language instruction using egocentric vision. The natural language instruction is given by the form of both high-level goal and low-level step-by-step instruction. |
IEEE/ICACT20230029 Slide.01
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