4 citations · 4 across the 6 of their papers we have counts for
Showing 2024 · cs.ROShow all
2 papers · 2 filters
cs.RO2024
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…
cs.RO2024
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…