AgentGarten: Code Worlds for Evolving Agents

arXiv:2610.12374 · cs.CV · Submitted 2026-10-08 · Read on arXiv

cs.CV

Submitted: 2026-10-08

Updated: 2026-10-08

Code: https://github.com/MirroS-Lab/AgentGarten

Project page: https://mirros-lab.github.io/agent-garten

Terminology

• World Model — 22× in this paper · explained in 7 episodes
• Distillation — 19× in this paper · explained in 2 episodes
• Distribution Matching — 9× in this paper · explained in 2 episodes
• Diffusion Model — 6× in this paper · explained in 8 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Diffusion Models — 5× in this paper · explained in 6 episodes
• Reinforcement Learning — 5× in this paper · explained in 4 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Consistency — 4× in this paper · explained in 3 episodes
• Steering — 4× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Regularization — 3× in this paper · explained in 3 episodes
• Adversarial Training — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Embodied AI — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Higher-order derivatives — 2× in this paper · explained in 2 episodes
• KV cache — 2× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Agentic Discovery — 1× in this paper · explained in 1 episode
• Cooperation — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Joint Attention — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Similar to Self Gradient Forcing — 1× in this paper
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Genie: Generative Interactive Environments
• WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling
• Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory
• Infinite Worlds with Versatile Interactions
• Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion
• One-step Diffusion with Distribution Matching Distillation
• Improved Distribution Matching Distillation for Fast Image Synthesis
• Self Gradient Forcing: Native Long Video Extrapolation
• ViPE: Video Pose Engine for 3D Geometric Perception
• Depth Anything 3: Recovering the Visual Space from Any Views
• Image Generators are Generalist Vision Learners
• SAM 3: Segment Anything with Concepts
• SAM 3D: 3Dfy Anything in Images
• Cosmos 3: Omnimodal World Models for Physical AI
• Wan: Open and Advanced Large-Scale Video Generative Models
• NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation
• World Simulation with Video Foundation Models for Physical AI
• Diffusion Adversarial Post-Training for One-Step Video Generation
• Holodeck: Language Guided Generation of 3D Embodied AI Environments
• SceneCraft: An LLM Agent for Synthesizing 3D Scene as Blender Code

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