10 papers
Functional Cache Grafting: Robust and Rapid Code-Policy Synthesis for Embodied Agents
Saehun Chun, Wonje Choi, Sera Choi +2
Code-writing large language models (CodeLLMs) generate executable code policies for embodied agents by translating natural language goals and environmental constraints into structu…
Efficient Skill Grounding via Code Refactoring with Small Language Models
Sera Choi, Wonje Choi, Saehun Chun +4
Effective skill grounding is essential for deploying reusable skills in embodied agents, as even minor embodiment or environmental differences can render an entire skill incompatib…
Cross-Domain Demo-to-Code via Neurosymbolic Counterfactual Reasoning
Jooyoung Kim, Wonje Choi, Younguk Song +1
Recent advances in Vision-Language Models (VLMs) have enabled video-instructed robotic programming, allowing agents to interpret video demonstrations and generate executable contro…
Policy Compatible Skill Incremental Learning via Lazy Learning Interface
Daehee Lee, Dongsu Lee, TaeYoon Kwack +2
Skill Incremental Learning (SIL) is the process by which an embodied agent expands and refines its skill set over time by leveraging experience gained through interaction with its…
Towards Reliable Code-as-Policies: A Neuro-Symbolic Framework for Embodied Task Planning
Sanghyun Ahn, Wonje Choi, Junyong Lee +2
Recent advances in large language models (LLMs) have enabled the automatic generation of executable code for task planning and control in embodied agents such as robots, demonstrat…
NeSyPr: Neurosymbolic Proceduralization For Efficient Embodied Reasoning
Wonje Choi, Jooyoung Kim, Honguk Woo
We address the challenge of adopting language models (LMs) for embodied tasks in dynamic environments, where online access to large-scale inference engines or symbolic planners is…