From the 1 of 7 linked papers with an AI index.
7 papers
RoboBRIDGE: A Modular Framework for Bridging Policies to Robust Real-World Robotic Agents
Sihyung Yoon, Minjong Yoo, Sanghyun Ahn +2
RoboBRIDGE is a modular orchestration framework that equips pretrained vision‑language‑action models with monitoring, perception, planning, control, and robot interface modules to…
Test-Time Mixture of World Models for Embodied Agents in Dynamic Environments
Jinwoo Jang, Minjong Yoo, Sihyung Yoon +1
Language model (LM)-based embodied agents are increasingly deployed in real-world settings. Yet, their adaptability remains limited in dynamic environments, where constructing accu…
Exploratory Retrieval-Augmented Planning For Continual Embodied Instruction Following
Minjong Yoo, Jinwoo Jang, Wei-jin Park +1
This study presents an Exploratory Retrieval-Augmented Planning (ExRAP) framework, designed to tackle continual instruction following tasks of embodied agents in dynamic, non-stati…
In-Context Policy Adaptation via Cross-Domain Skill Diffusion
Minjong Yoo, Woo Kyung Kim, Honguk Woo
In this work, we present an in-context policy adaptation (ICPAD) framework designed for long-horizon multi-task environments, exploring diffusion-based skill learning techniques in…
World Model Implanting for Test-time Adaptation of Embodied Agents
Minjong Yoo, Jinwoo Jang, Sihyung Yoon +1
In embodied AI, a persistent challenge is enabling agents to robustly adapt to novel domains without requiring extensive data collection or retraining. To address this, we present…
Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation
Daehee Lee, Minjong Yoo, Woo Kyung Kim +2
Continual Imitation Learning (CiL) involves extracting and accumulating task knowledge from demonstrations across multiple stages and tasks to achieve a multi-task policy. With rec…