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Taewoong Kim

2 accepted papers

2025

Multi-Modal Grounded Planning and Efficient Replanning for Learning Embodied Agents with a Few Examples

AAAI 2025technical

Learning a perception and reasoning module for robotic assistants to plan steps to perform complex tasks based on natural language instructions often requires large free-form language annotations, especially for short high-level instructions. To reduce the cost of annotation, large language models (…

2024

ReALFRED: An Embodied Instruction Following Benchmark in Photo-Realistic Environments

ECCV 2024poster

"Simulated virtual environments have been widely used to learn robotic agents that perform daily household tasks. These environments encourage research progress by far, but often provide limited object interactability, visual appearance different from real-world environments, or relatively smaller e…