Luban: Building Open-Ended Creative Agents via Autonomous Embodied Verification
On the map: LLM agents and tool use → Reinforcement learning for LLM agents
Abstract (arXiv)
Building open agents has always been the ultimate goal in AI research, and creative agents are the more enticing. Existing LLM agents excel at long-horizon tasks with well-defined goals (e.g., `mine diamonds' in Minecraft). However, they encounter difficulties on creative tasks with open goals and abstract criteria due to the inability to bridge the gap between them, thus lacking feedback for self-improvement in solving the task. In this work, we introduce autonomous embodied verification techniques for agents to fill the gap, laying the groundwork for creative tasks. Specifically, we propose the Luban agent target creative building tasks in Minecraft, which equips with two-level autonomous embodied verification inspired by human design practices: (1) visual verification of 3D structural speculates, which comes from agent synthesized CAD modeling programs; (2) pragmatic verification of the creation by generating and verifying environment-relevant functionality programs based on the abstract criteria. Extensive multi-dimensional human studies and Elo ratings show that the Luban completes diverse creative building tasks in our proposed benchmark and outperforms other baselines (33% to 100%) in both visualization and pragmatism. Additional demos on the real-world robotic arm show the creation potential of the Luban in the physical world.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in Reinforcement learning for LLM agents, one of 16 directions in LLM agents and tool use. Builds on 22 of its 43 references that are in the map. First posted on arXiv 24 May 2024.
Builds on
22 of 43 references.
Closest ancestors · 3
Same direction, newest first
- 2023JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Models10 Nov
- 2023Voyager: An Open-Ended Embodied Agent with Large Language Models25 May
- 2022MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge17 Jun
Other references · 19
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- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
- 2022Generative Adversarial Networkscited by 5,603
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
- 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,302
- 2015Variational Inference with Normalizing Flowscited by 2,161
- 2022Code as Policies: Language Model Programs for Embodied Controlcited by 1,172
- 2022Inner Monologue: Embodied Reasoning through Planning with Language Modelscited by 1,057
- 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 694
- 2022Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videoscited by 338
- 20233DGen: Triplane Latent Diffusion for Textured Mesh Generationcited by 181
7 more
- 2023Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Modelcited by 115
- 2023HoloDiffusion: Training a 3D Diffusion Model using 2D Imagescited by 106
- 2023STEVE-1: A Generative Model for Text-to-Behavior in Minecraftcited by 95
- 2023Hierarchical Neural Coding for Controllable CAD Model Generationcited by 84
- 2023GROOT: Learning to Follow Instructions by Watching Gameplay Videoscited by 42
- 2023MCU: An Evaluation Framework for Open-Ended Game Agentscited by 33
- 2023Self-driven Grounding: Large Language Model Agents with Automatical Language-aligned Skill Learningcited by 9
Built on by
Citing papers per year: 2025: 4; 2026: 1.
5 papers.
- 2025The Landscape of Agentic Reinforcement Learning for LLMs: A Surveycited by 195
- 2025CausalMACE: Causality Empowered Multi-Agents in Minecraft Cooperative Taskscited by 8
- 2025Open-World Skill Discovery from Unsegmented Demonstrationscited by 7
- 2025GraphicBench: A Planning Benchmark for Graphic Design with Language Agentscited by 3
- 2026Rethinking Agentic Reinforcement Learning In Large Language Modelscited by 0
- 2026Rethinking Agentic Reinforcement Learning In Large Language Models30 Apr 2026
- 2025The Landscape of Agentic Reinforcement Learning for LLMs: A Survey2 Sep 2025
- 2025CausalMACE: Causality Empowered Multi-Agents in Minecraft Cooperative Tasks26 Aug 2025
- 2025GraphicBench: A Planning Benchmark for Graphic Design with Language Agents15 Apr 2025
- 2025Open-World Skill Discovery from Unsegmented Demonstrations11 Mar 2025
Similar, not cited
Close in wording, no citation either way
- 2025CrafterDojo: A Suite of Foundation Models for Building Open-Ended Embodied Agents in Crafter
- 2024APT: Architectural Planning and Text-to-Blueprint Construction Using Large Language Models for Open-World Agents
- 2023Creative Agents: Empowering Agents with Imagination for Creative Tasks
- 2025Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning
- 2024TeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in Minecraft
- 2025GuessBench: Sensemaking Multimodal Creativity in the Wild
- 2026MineExplorer: Evaluating Open-World Exploration of MLLM Agents in Minecraft
- 2025OpenHA: A Series of Open-Source Hierarchical Agentic Models in Minecraft