https://github.com/CraftJarvis/ROCKET-1
공식 코드ROCKET-1: Mastering Open-World Interaction with Visual-Temporal Context Prompting
Papers with Code 아카이브
Minecraft
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/JiuTian-VL/Optimus-1
공식 코드Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks
https://github.com/MITLL-SMMAAL/pub_HMT_AAEtool_and_testbed
공식 코드Enabling Rapid Shared Human-AI Mental Model Alignment via the After-Action Review
https://github.com/Mawiszus/World-GAN
공식 코드https://github.com/Miffyli/minecraft-bc
공식 코드https://github.com/MineDojo/MineDojo
공식 코드MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge
https://github.com/MineDojo/Voyager
공식 코드Voyager: An Open-Ended Embodied Agent with Large Language Models
https://github.com/PKU-RL/CLIP4MC
공식 코드Reinforcement Learning Friendly Vision-Language Model for Minecraft
https://github.com/Zhoues/MineDreamer
공식 코드MineDreamer: Learning to Follow Instructions via Chain-of-Imagination for Simulated-World Control
https://github.com/amiranas/minerl_imitation_learning
공식 코드https://github.com/andrewpaulchester/sage-code
공식 코드SAGE: Generating Symbolic Goals for Myopic Models in Deep Reinforcement Learning
https://github.com/ayanami2003/gate
공식 코드GATE: Graph-based Adaptive Tool Evolution Across Diverse Tasks
https://github.com/cassidylaidlaw/minecraft-building-assistance-game
공식 코드https://github.com/cnsdqd-dyb/villageragent
공식 코드https://github.com/cocacola-lab/mineland
공식 코드https://github.com/cog-isa/forger
공식 코드Hierarchical Deep Q-Network from Imperfect Demonstrations in Minecraft
https://github.com/commandercero/netplay
공식 코드Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents
https://github.com/craftjarvis/mc-controller
공식 코드https://github.com/craftjarvis/mc-planner
공식 코드https://github.com/craftjarvis/mcu
공식 코드Towards Evaluating Generalist Agents: An Automated Benchmark in Open World
https://github.com/craftjarvis/minestudio
공식 코드MineStudio: A Streamlined Package for Minecraft AI Agent Development
https://github.com/danijar/dreamerv3
공식 코드https://github.com/dlpbc/penn-a
공식 코드Evolving Inborn Knowledge For Fast Adaptation in Dynamic POMDP Problems
https://github.com/dongyh20/octopus
공식 코드Octopus: Embodied Vision-Language Programmer from Environmental Feedback
https://github.com/elated-sawyer/WALL-E
공식 코드WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents
https://github.com/esteng/regal_program_learning
공식 코드ReGAL: Refactoring Programs to Discover Generalizable Abstractions
https://github.com/eugleo/vista-dataset
공식 코드ViSTa Dataset: Do vision-language models understand sequential tasks?
https://github.com/facebookresearch/craftassist
공식 코드CraftAssist: A Framework for Dialogue-enabled Interactive Agents
https://github.com/fudan-zvg/s-agents
공식 코드https://github.com/gautierdag/plancraft
공식 코드Plancraft: an evaluation dataset for planning with LLM agents
https://github.com/gillishermans/sigi
공식 코드Shape Inference and Grammar Induction for Example-based Procedural Generation
https://github.com/goelshivam1210/RAPid-Learn
공식 코드RAPid-Learn: A Framework for Learning to Recover for Handling Novelties in Open-World Environments
https://github.com/holmeswww/spring
공식 코드https://github.com/iretonliu/mine-pddl
공식 코드MinePlanner: A Benchmark for Long-Horizon Planning in Large Minecraft Worlds
https://github.com/kevin-lkw/loopnav
공식 코드Toward Memory-Aided World Models: Benchmarking via Spatial Consistency
https://github.com/michael-beukman/mchamr
공식 코드Hierarchically Composing Level Generators for the Creation of Complex Structures
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.