世界模型

Active Predictive Coding: A Unified Neural Framework for Learning Hierarchical World Models for Perception and Planning

主动预测编码：一种统一的神经框架，用于学习感知与规划的分层世界模型

Rajesh P. N. Rao, Dimitrios C. Gklezakos, Vishwas Sathish

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

AI总结 本文提出主动预测编码框架，通过分层世界模型解决人工智能中感知与规划的两大核心问题。

Comments 15 pages, 10 figures, 2 supplementary figures

MindJourney: Test-Time Scaling with World Models for Spatial Reasoning

Yuncong Yang, Jiageng Liu, Zheyuan Zhang, Siyuan Zhou, Reuben Tan, Jianwei Yang, Yilun Du, Chuang Gan

机构 * UMass Amherst（马萨诸塞大学阿默斯特分校） ； JHU（约翰·霍普金斯大学） ； HKUST（香港科技大学） ； Microsoft Research（微软研究院） ； Harvard（哈佛大学） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments Project Page: https://umass-embodied-agi.github.io/MindJourney

Semantic World Models

Jacob Berg, Chuning Zhu, Yanda Bao, Ishan Durugkar, Abhishek Gupta

机构 * University of Washington（华盛顿大学） ； Sony AI（索尼人工智能） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

The Safety Challenge of World Models for Embodied AI Agents: A Review

Lorenzo Baraldi, Zifan Zeng, Chongzhe Zhang, Aradhana Nayak, Hongbo Zhu, Feng Liu, Qunli Zhang, Peng Wang, Shiming Liu, Zheng Hu, Angelo Cangelosi, Lorenzo Baraldi

机构 * University of Pisa（比萨大学） ； Huawei RAMS Lab（华为RAMS实验室） ； Technical University of Munich（慕尼黑技术大学） ； Technical University of Berlin（柏林技术大学） ； University of Manchester（曼彻斯特大学） ； University of Modena and Reggio Emilia（莫德纳和雷吉奥艾米利亚大学） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Bridging the Gap Between Multimodal Foundation Models and World Models

Xuehai He

机构 * Computer Science and Engineering University of California, Santa Cruz（计算机科学与工程大学加州大学圣克ruz分校） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments PhD thesis

Can World Models Benefit VLMs for World Dynamics?

Kevin Zhang, Kuangzhi Ge, Xiaowei Chi, Renrui Zhang, Shaojun Shi, Zhen Dong, Sirui Han, Shanghang Zhang

机构 * Peking University（北京大学） ； Hong Kong University of Science and Technology（香港科学与技术大学） ； Chinese University of Hong Kong（香港中文大学） ； University of California, Santa Barbara（加州大学圣芭芭拉分校） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments Project page: https://dyva-worldlm.github.io

Training Agents Inside of Scalable World Models

Danijar Hafner, Wilson Yan, Timothy Lillicrap

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments Website: https://danijar.com/dreamer4/

FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making

Yucen Wang, Rui Yu, Shenghua Wan, Le Gan, De-Chuan Zhan

机构 * School of Artificial Intelligence, Nanjing University, China（人工智能学院，南京大学） ； National Key Laboratory for Novel Software Technology, Nanjing University, China（新型软件技术国家重点实验室，南京大学） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments Accepted by Forty-Second International Conference on Machine Learning (ICML 2025)

Humanoid World Models: Open World Foundation Models for Humanoid Robotics

Muhammad Qasim Ali, Aditya Sridhar, Shahbuland Matiana, Alex Wong, Mohammad Al-Sharman

机构 * University of Waterloo（滑铁卢大学） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

WoMAP: World Models For Embodied Open-Vocabulary Object Localization

Tenny Yin, Zhiting Mei, Tao Sun, Lihan Zha, Emily Zhou, Jeremy Bao, Miyu Yamane, Ola Shorinwa, Anirudha Majumdar

机构 * Princeton University（普林斯顿大学） ； McGill University（麦吉尔大学） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets

Chuning Zhu, Raymond Yu, Siyuan Feng, Benjamin Burchfiel, Paarth Shah, Abhishek Gupta

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

World Models in Artificial Intelligence: Sensing, Learning, and Reasoning Like a Child

Javier Del Ser, Jesus L. Lobo, Heimo Müller, Andreas Holzinger

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments 11 pages, 1 figure

Toward Stable World Models: Measuring and Addressing World Instability in Generative Environments

Soonwoo Kwon, Jin-Young Kim, Hyojun Go, Kyungjune Baek

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments Preprint

ACT-Bench: Towards Action Controllable World Models for Autonomous Driving

Hidehisa Arai, Keishi Ishihara, Tsubasa Takahashi, Yu Yamaguchi

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey

Ao Fu, Yi Zhou, Tao Zhou, Yi Yang, Bojun Gao, Qun Li, Guobin Wu, Ling Shao

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Learning World Models for Unconstrained Goal Navigation

Yuanlin Duan, Wensen Mao, He Zhu

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments NeurIPS2024 Poster. arXiv admin note: substantial text overlap with arXiv:2411.01396

World Models for Autonomous Driving: An Initial Survey

Yanchen Guan, Haicheng Liao, Zhenning Li, Jia Hu, Runze Yuan, Yunjian Li, Guohui Zhang, Chengzhong Xu

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

The Essential Role of Causality in Foundation World Models for Embodied AI

Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Marc Rigter, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Learning and Leveraging World Models in Visual Representation Learning

Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments 23 pages, 16 figures

Slot Structured World Models

Jonathan Collu, Riccardo Majellaro, Aske Plaat, Thomas M. Moerland

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Neural World Models for Computer Vision

Anthony Hu

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments PhD thesis

Co-Learning Empirical Games and World Models

Max Olan Smith, Michael P. Wellman

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Transformers are Sample-Efficient World Models

Vincent Micheli, Eloi Alonso, François Fleuret

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments ICLR 2023 (notable top 5%)

World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges

Tadahiro Taniguchi, Shingo Murata, Masahiro Suzuki, Dimitri Ognibene, Pablo Lanillos, Emre Ugur, Lorenzo Jamone, Tomoaki Nakamura, Alejandra Ciria, Bruno Lara, Giovanni Pezzulo

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments 28 pages, 3 figures

Iso-Dream: Isolating and Leveraging Noncontrollable Visual Dynamics in World Models

Minting Pan, Xiangming Zhu, Yunbo Wang, Xiaokang Yang

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation

Cansu Sancaktar, Sebastian Blaes, Georg Martius

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments NeurIPS 2022 camera-ready version

DayDreamer: World Models for Physical Robot Learning

Philipp Wu, Alejandro Escontrela, Danijar Hafner, Ken Goldberg, Pieter Abbeel

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments Website: https://danijar.com/daydreamer

Constrained Policy Optimization via Bayesian World Models

Yarden As, Ilnura Usmanova, Sebastian Curi, Andreas Krause

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment

Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen Roberts

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

Comments Accepted @ ICML 2021; Spotlight @ ICLR 2021 "Self-Supervision for Reinforcement Learning Workshop"

Graph-Operator World Models for Morphology-Parameter Generalization in Continuous Control

用于连续控制中形态参数泛化的图算子世界模型

Xu Yang, Yiqin Yang, Qianchuan Zhao

机构 * Tsinghua University（清华大学） ； Chinese Academy of Sciences（中国科学院） 纠错

专题命中 通用世界模型 ：world model(title,abstract)；world models(title,abstract)；world model(title,abstract)；world models(title,abstract)

AI总结 提出GraphOp-WM结构化世界模型，通过分解转移为形态无关局部基与形态相关算子，实现连续控制中铰接机器人家族的形态参数泛化，定义MuJoCo参数划分验证方法。