Papers Minecraft
“Minecraft” 태그가 달린 논문 236편 · 필터 해제
LTLCrit: A Temporal Logic-based LLM Critic for Safe and Efficient Embodied Agents
Large language models (LLMs) have demonstrated promise in reasoning tasks and general decision-making in static environments. In long-term planning tasks, however, errors tend to accumulate, often leading to unsafe or in…
Decision MakingFormal LogicMinecraftMatrix-Game: Interactive World Foundation Model
We introduce Matrix-Game, an interactive world foundation model for controllable game world generation. Matrix-Game is trained using a two-stage pipeline that first performs large-scale unlabeled pretraining for environm…
MinecraftmodelVideo GenerationTransDreamerV3: Implanting Transformer In DreamerV3
This paper introduces TransDreamerV3, a reinforcement learning model that enhances the DreamerV3 architecture by integrating a transformer encoder. The model is designed to improve memory and decision-making capabilities…
Decision MakingMinecraftModel-based Reinforcement Learningreinforcement-learning+1Optimus-3: Towards Generalist Multimodal Minecraft Agents with Scalable Task Experts
Recently, agents based on multimodal large language models (MLLMs) have achieved remarkable progress across various domains. However, building a generalist agent with capabilities such as perception, planning, action, gr…
DiversityMinecraftMixture-of-ExpertsMultimodal ReasoningToward Memory-Aided World Models: Benchmarking via Spatial Consistency
The ability to simulate the world in a spatially consistent manner is a crucial requirements for effective world models. Such a model enables high-quality visual generation, and also ensures the reliability of world mode…
BenchmarkingMinecraftLong-Context State-Space Video World Models
Video diffusion models have recently shown promise for world modeling through autoregressive frame prediction conditioned on actions. However, they struggle to maintain long-term memory due to the high computational cost…
Computational EfficiencyMinecraftState Space ModelsMineAnyBuild: Benchmarking Spatial Planning for Open-world AI Agents
Spatial Planning is a crucial part in the field of spatial intelligence, which requires the understanding and planning about object arrangements in space perspective. AI agents with the spatial planning ability can bette…
BenchmarkingMinecraftQuestion AnsweringSpatial Reasoning+2Knowledge Retrieval in LLM Gaming: A Shift from Entity-Centric to Goal-Oriented Graphs
Large Language Models (LLMs) demonstrate impressive general capabilities but often struggle with step-by-step reasoning, especially in complex applications such as games. While retrieval-augmented methods like GraphRAG a…
MinecraftRetrievalBAR: A Backward Reasoning based Agent for Complex Minecraft Tasks
Large language model (LLM) based agents have shown great potential in following human instructions and automatically completing various tasks. To complete a task, the agent needs to decompose it into easily executed step…
Large Language ModelMinecraftPLAICraft: Large-Scale Time-Aligned Vision-Speech-Action Dataset for Embodied AI
Advances in deep generative modelling have made it increasingly plausible to train human-level embodied agents. Yet progress has been limited by the absence of large-scale, real-time, multi-modal, and socially interactiv…
BenchmarkingMinecraftObject RecognitionBeliefNest: A Joint Action Simulator for Embodied Agents with Theory of Mind
This paper introduces an open-source simulator, BeliefNest, designed to enable embodied agents to perform collaborative tasks by leveraging Theory of Mind. BeliefNest dynamically and hierarchically constructs simulators …
MinecraftD3HRL: A Distributed Hierarchical Reinforcement Learning Approach Based on Causal Discovery and Spurious Correlation Detection
Current Hierarchical Reinforcement Learning (HRL) algorithms excel in long-horizon sequential decision-making tasks but still face two challenges: delay effects and spurious correlations. To address them, we propose a ca…
Causal DiscoveryDecision MakingHierarchical Reinforcement LearningMinecraft+1Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning
Collaboration is ubiquitous and essential in day-to-day life -- from exchanging ideas, to delegating tasks, to generating plans together. This work studies how LLMs can adaptively collaborate to perform complex embodied …
Imitation LearningMinecraftWALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents
Can we build accurate world models out of large language models (LLMs)? How can world models benefit LLM agents? The gap between the prior knowledge of LLMs and the specified environment's dynamics usually bottlenecks LL…
Knowledge GraphsMinecraftModel Predictive ControlMineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft
World modeling is a crucial task for enabling intelligent agents to effectively interact with humans and operate in dynamic environments. In this work, we propose MineWorld, a real-time interactive world model on Minecra…
MinecraftAssistanceZero: Scalably Solving Assistance Games
Assistance games are a promising alternative to reinforcement learning from human feedback (RLHF) for training AI assistants. Assistance games resolve key drawbacks of RLHF, such as incentives for deceptive behavior, by …
Imitation LearningMinecraftBugCraft: End-to-End Crash Bug Reproduction Using LLM Agents in Minecraft
Reproducing game bugs, in our case crash bugs in continuously evolving games like Minecraft, is a notoriously manual, time-consuming, and challenging process to automate. Despite the success of LLM-driven bug reproductio…
MinecraftEnabling Rapid Shared Human-AI Mental Model Alignment via the After-Action Review
In this work, we present two novel contributions toward improving research in human-machine teaming (HMT): 1) a Minecraft testbed to accelerate testing and deployment of collaborative AI agents and 2) a tool to allow use…
MinecraftJARVIS-VLA: Post-Training Large-Scale Vision Language Models to Play Visual Games with Keyboards and Mouse
Recently, action-based decision-making in open-world environments has gained significant attention. Visual Language Action (VLA) models, pretrained on large-scale web datasets, have shown promise in decision-making tasks…
Decision MakingImitation LearningMinecraftWorld KnowledgeUncertainty in Action: Confidence Elicitation in Embodied Agents
Expressing confidence is challenging for embodied agents navigating dynamic multimodal environments, where uncertainty arises from both perception and decision-making processes. We present the first work investigating em…
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