13 citations · 36 across the 9 of their papers we have counts for
4 papers · 1 filter
IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents
Shrestha Mohanty, Negar Arabzadeh, Andrea Tupini +5
Seamless interaction between AI agents and humans using natural language remains a key goal in AI research. This paper addresses the challenges of developing interactive agents cap…
Transforming Human-Centered AI Collaboration: Redefining Embodied Agents Capabilities through Interactive Grounded Language Instructions
Shrestha Mohanty, Negar Arabzadeh, Julia Kiseleva +6
Human intelligence's adaptability is remarkable, allowing us to adjust to new tasks and multi-modal environments swiftly. This skill is evident from a young age as we acquire new a…
Learning to Solve Voxel Building Embodied Tasks from Pixels and Natural Language Instructions
Alexey Skrynnik, Zoya Volovikova, Marc-Alexandre Côté +9
The adoption of pre-trained language models to generate action plans for embodied agents is a promising research strategy. However, execution of instructions in real or simulated e…
NeurIPS 2021 Competition IGLU: Interactive Grounded Language Understanding in a Collaborative Environment
Julia Kiseleva, Ziming Li, Mohammad Aliannejadi +12
Human intelligence has the remarkable ability to adapt to new tasks and environments quickly. Starting from a very young age, humans acquire new skills and learn how to solve new t…