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Papers

Showing 125 of 236 papers

TitleStatusHype
Matrix-Game: Interactive World Foundation ModelCode5
Voyager: An Open-Ended Embodied Agent with Large Language ModelsCode5
Mastering Diverse Domains through World ModelsCode4
MineDojo: Building Open-Ended Embodied Agents with Internet-Scale KnowledgeCode4
Parallelized Planning-Acting for Efficient LLM-based Multi-Agent SystemsCode3
MineStudio: A Streamlined Package for Minecraft AI Agent DevelopmentCode3
Odyssey: Empowering Minecraft Agents with Open-World SkillsCode3
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement LearningCode3
Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online VideosCode3
WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM AgentsCode2
AssistanceZero: Scalably Solving Assistance GamesCode2
Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon TasksCode2
Craftium: An Extensible Framework for Creating Reinforcement Learning EnvironmentsCode2
VillagerAgent: A Graph-Based Multi-Agent Framework for Coordinating Complex Task Dependencies in MinecraftCode2
MineLand: Simulating Large-Scale Multi-Agent Interactions with Limited Multimodal Senses and Physical NeedsCode2
MineDreamer: Learning to Follow Instructions via Chain-of-Imagination for Simulated-World ControlCode2
Octopus: Embodied Vision-Language Programmer from Environmental FeedbackCode2
STEVE-1: A Generative Model for Text-to-Behavior in MinecraftCode2
Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and MemoryCode2
Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task AgentsCode2
Temporally Consistent Transformers for Video GenerationCode2
Toward Memory-Aided World Models: Benchmarking via Spatial ConsistencyCode1
MineAnyBuild: Benchmarking Spatial Planning for Open-world AI AgentsCode1
Plancraft: an evaluation dataset for planning with LLM agentsCode1
TeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in MinecraftCode1
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