Improving Agent Interactions in Virtual Environments with Language
  Models
Jack Zhang
Enhancing AI systems with efficient communication skills for effective human
assistance necessitates proactive initiatives from the system side to discern
specific circumstances and interact aptly. This research focuses on a
collective building assignment in the Minecraft dataset, employing language
modeling to enhance task understanding through state-of-the-art methods. These
models focus on grounding multi-modal understanding and task-oriented dialogue
comprehension tasks, providing insights into their interpretative and
responsive capabilities. Our experimental results showcase a substantial
improvement over existing methods, indicating a promising direction for future
research in this domain.