Papers with TEACh

1 papers
DANLI: Deliberative Agent for Following Natural Language Instructions (2022.emnlp-main)

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Challenge: Recent work on embodied AI agents that can perform tasks by following human language instructions is limited by reactive methods, which are insufficient for long-horizon complex tasks.
Approach: They propose a neuro-symbolic deliberative agent that, while following language instructions, proactively applies reasoning and planning based on its neural and symbolic representations acquired from past experience.
Outcome: The proposed agent achieves greater than 70% improvement over reactive baselines on the challenging TEACh benchmark.

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