4 citations · 4 across the 6 of their papers we have counts for
3 papers · 1 filter
Multi-Modal Grounded Planning and Efficient Replanning For Learning Embodied Agents with A Few Examples
Taewoong Kim, Byeonghwi Kim, Jonghyun Choi
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 langu…
ReALFRED: An Embodied Instruction Following Benchmark in Photo-Realistic Environments
Taewoong Kim, Cheolhong Min, Byeonghwi Kim +3
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 pr…
Online Continual Learning For Interactive Instruction Following Agents
Byeonghwi Kim, Minhyuk Seo, Jonghyun Choi
In learning an embodied agent executing daily tasks via language directives, the literature largely assumes that the agent learns all training data at the beginning. We argue that…