3 citations · 5 across the 7 of their papers we have counts for
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cs.AI2024
Embodied CoT Distillation From LLM To Off-the-shelf Agents
Wonje Choi, Woo Kyung Kim, Minjong Yoo +1
We address the challenge of utilizing large language models (LLMs) for complex embodied tasks, in the environment where decision-making systems operate timely on capacity-limited,…
cs.AI2024★ 3 cited
Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents
Wonje Choi, Woo Kyung Kim, SeungHyun Kim +1
For embodied reinforcement learning (RL) agents interacting with the environment, it is desirable to have rapid policy adaptation to unseen visual observations, but achieving zero-…
cs.AI2024★ 1 cited
One-shot Imitation in a Non-Stationary Environment via Multi-Modal Skill
Sangwoo Shin, Daehee Lee, Minjong Yoo +2
One-shot imitation is to learn a new task from a single demonstration, yet it is a challenging problem to adopt it for complex tasks with the high domain diversity inherent in a no…