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Human intelligence's adaptability is remarkable, allowing us to adjust to newtasks and multi-modal environments swiftly. This skill is evident from a youngage as we acquire new abilities and solve problems by imitating others orfollowing natural language instructions. The research community is activelypursuing the development of interactive "embodied agents" that can engage innatural conversations with humans and assist them with real-world tasks. Theseagents must possess the ability to promptly request feedback in casecommunication breaks down or instructions are unclear. Additionally, they mustdemonstrate proficiency in learning new vocabulary specific to a given domain.  In this paper, we made the following contributions: (1) a crowd-sourcing toolfor collecting grounded language instructions; (2) the largest dataset ofgrounded language instructions; and (3) several state-of-the-art baselines.These contributions are suitable as a foundation for further research.

Transforming Human-Centered AI Collaboration: Redefining Embodied Agents Capabilities through Interactive Grounded Language Instructions