机器人 / 具身智能

VDFD: Multi-Agent Value Decomposition Framework with Disentangled World Model

Zhizun Wang, David Meger

机构 * School of Computer Science, McGill University（计算机科学学院，麦吉尔大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments 43 pages

A Survey of World Models for Autonomous Driving

Tuo Feng, Wenguan Wang, Yi Yang

机构 * Collaborative Innovation Center of Artificial Intelligence (CCAI), Zhejiang University（人工智能协同创新中心（CCAI）、浙江大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.CV

Comments Ongoing project. Paper list: https://github.com/FengZicai/AwesomeWMAD Benchmark: https://github.com/FengZicai/WMAD-Benchmarks

Decentralized Transformers with Centralized Aggregation are Sample-Efficient Multi-Agent World Models

Yang Zhang, Chenjia Bai, Bin Zhao, Junchi Yan, Xiu Li, Xuelong Li

机构 * Tsinghua University（清华大学） ； Institute of Artificial Intelligence (TeleAI), China Telecom（人工智能研究所（TeleAI），中国电信） ； Shanghai AI Laboratory（上海人工智能实验室） ； Shanghai Jiaotong University（上海交通大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments Accepted by Transactions on Machine Learning Research

MUVO: A Multimodal Generative World Model for Autonomous Driving with Geometric Representations

Daniel Bogdoll, Yitian Yang, Tim Joseph, Melih Yazgan, J. Marius Zöllner

机构 * FZI Research Center for Information Technology, Germany（德国弗赖堡信息科技研究中心） ； Karlsruhe Institute of Technology, Germany（德国卡尔斯鲁厄理工学院） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.LG

Comments Daniel Bogdoll and Yitian Yang contributed equally. Accepted for publication at IV 2025

Bounding Distributional Shifts in World Modeling through Novelty Detection

Eric Jing, Abdeslam Boularias

机构 * Department of Computer Science, Rutgers University（计算机科学系，罗格斯大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.AI

Comments 7 pages, 6 figures

Assessing Adaptive World Models in Machines with Novel Games

Lance Ying, Katherine M. Collins, Prafull Sharma, Cedric Colas, Kaiya Ivy Zhao, Adrian Weller, Zenna Tavares, Phillip Isola, Samuel J. Gershman, Jacob D. Andreas, Thomas L. Griffiths, Francois Chollet, Kelsey R. Allen, Joshua B. Tenenbaum

机构 * MIT（麻省理工学院） ； Harvard University（哈佛大学） ； University of Cambridge（剑桥大学） ； Basis Research Institute（基础研究机构） ； Princeton University（普林斯顿大学） ； ARC Prize Foundation（ARC奖基金会） ； University of British Columbia（不列颠哥伦比亚大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments 17 pages, 4 figures

World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving

Yanchen Guan, Haicheng Liao, Chengyue Wang, Xingcheng Liu, Jiaxun Zhang, Zhenning Li

机构 * State Key Laboratory of Internet of Things for Smart City（物联网智能城市国家重点实验室） ； University of Macau（澳门大学） ； Department of Civil Engineering（土木工程系） ； Department of Computer and Information Science（计算机与信息科学系） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.CV、cs.LG

A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment

Raanan Y. Rohekar, Yaniv Gurwicz, Sungduk Yu, Estelle Aflalo, Vasudev Lal

机构 * Intel Labs（英特尔实验室） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments International Conference on Machine Learning (ICML), 2025

Learning Counterfactually Decoupled Attention for Open-World Model Attribution

Yu Zheng, Boyang Gong, Fanye Kong, Yueqi Duan, Bingyao Yu, Wenzhao Zheng, Lei Chen, Jiwen Lu, Jie Zhou

机构 * Tsinghua University（清华大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.CV、cs.LG

Comments Accepted by ICCV 2025. Code: \url{https://github.com/yzheng97/CDAL}

Learning World Models With Hierarchical Temporal Abstractions: A Probabilistic Perspective

Vaisakh Shaj

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments Doctoral Dissertation, Department of Computer Science, Karlsruhe Institute Of Technology, 2024

WorldVLA: Towards Autoregressive Action World Model

Jun Cen, Chaohui Yu, Hangjie Yuan, Yuming Jiang, Siteng Huang, Jiayan Guo, Xin Li, Yibing Song, Hao Luo, Fan Wang, Deli Zhao, Hao Chen

机构 * DAMO Academy, Alibaba Group（达摩院，阿里巴巴集团） ； Hupan Lab（虎跑实验室） ； Zhejiang University（浙江大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.AI

Comments Code: https://github.com/alibaba-damo-academy/WorldVLA

How Far is Video Generation from World Model: A Physical Law Perspective

Bingyi Kang, Yang Yue, Rui Lu, Zhijie Lin, Yang Zhao, Kaixin Wang, Gao Huang, Jiashi Feng

机构 * ByteDance Research（字节跳动研究团队） ； Tsinghua University（清华大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.CV

Comments ICML 2025

Time-Aware World Model for Adaptive Prediction and Control

Anh N. Nhu, Sanghyun Son, Ming Lin

机构 * University of Maryland（马里兰大学） ； Department of Computer Science（计算机科学系） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments Paper accepted to ICML 2025

Ego-centric Learning of Communicative World Models for Autonomous Driving

Hang Wang, Dechen Gao, Junshan Zhang

机构 * Department of Electrical and Computer Engineering, University of California, Davis（电气与计算机工程系，加州大学戴维斯分校） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.AI

FOLIAGE: Towards Physical Intelligence World Models Via Unbounded Surface Evolution

Xiaoyi Liu, Hao Tang

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.CV

Simple, Good, Fast: Self-Supervised World Models Free of Baggage

Jan Robine, Marc Höftmann, Stefan Harmeling

机构 * TU Dortmund（图鲁姆大学） ； Lamarr Institute for Machine Learning and Artificial Intelligence（拉马尔人工智能与机器学习研究所） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments Published as a conference paper at ICLR 2025. Code is available at https://github.com/jrobine/sgf

Four Principles for Physically Interpretable World Models

Jordan Peper, Zhenjiang Mao, Yuang Geng, Siyuan Pan, Ivan Ruchkin

机构 * University of Florida（佛罗里达大学） 纠错

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.LG

Comments Equal contribution by the first two authors

Learning to Drive from a World Model

Mitchell Goff, Greg Hogan, George Hotz, Armand du Parc Locmaria, Kacper Raczy, Harald Schäfer, Adeeb Shihadeh, Weixing Zhang, Yassine Yousfi

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.CV

Learning Actionable World Models for Industrial Process Control

Peng Yan, Ahmed Abdulkadir, Gerrit A. Schatte, Giulia Aguzzi, Joonsu Gha, Nikola Pascher, Matthias Rosenthal, Yunlong Gao, Benjamin F. Grewe, Thilo Stadelmann

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments Accepted by SDS 2025

MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft

Junliang Guo, Yang Ye, Tianyu He, Haoyu Wu, Yushu Jiang, Tim Pearce, Jiang Bian

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.CV

Comments Technical report. Project page https://aka.ms/mineworld

Better Decisions through the Right Causal World Model

Elisabeth Dillies, Quentin Delfosse, Jannis Blüml, Raban Emunds, Florian Peter Busch, Kristian Kersting

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments 5 pages including references, 2 figures

World Modeling Makes a Better Planner: Dual Preference Optimization for Embodied Task Planning

Siyin Wang, Zhaoye Fei, Qinyuan Cheng, Shiduo Zhang, Panpan Cai, Jinlan Fu, Xipeng Qiu

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.CV

Imagine-2-Drive: Leveraging High-Fidelity World Models via Multi-Modal Diffusion Policies

Anant Garg, K Madhava Krishna

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.AI

Comments Submitted to IROS 2025

Transformers Use Causal World Models in Maze-Solving Tasks

Alex F. Spies, William Edwards, Michael I. Ivanitskiy, Adrians Skapars, Tilman Räuker, Katsumi Inoue, Alessandra Russo, Murray Shanahan

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments Main paper: 9 pages, 9 figures. Supplementary material: 10 pages, 17 additional figures. Code and data will be available upon publication. Corresponding author: A. F. Spies (afspies@imperial.ac.uk)

World Models for Anomaly Detection during Model-Based Reinforcement Learning Inference

Fabian Domberg, Georg Schildbach

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.AI

FACTS: A Factored State-Space Framework For World Modelling

Li Nanbo, Firas Laakom, Yucheng Xu, Wenyi Wang, Jürgen Schmidhuber

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments Code released in https://github.com/NanboLi/FACTS

Journal ref ICLR 2025

Learning To Explore With Predictive World Model Via Self-Supervised Learning

Alana Santana, Paula P. Costa, Esther L. Colombini

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

AdaWM: Adaptive World Model based Planning for Autonomous Driving

Hang Wang, Xin Ye, Feng Tao, Chenbin Pan, Abhirup Mallik, Burhaneddin Yaman, Liu Ren, Junshan Zhang

专题命中 具身推理 ：world model(title,abstract)；分类 cs.RO、cs.AI

Comments ICLR 2025

Towards Unraveling and Improving Generalization in World Models

Qiaoyi Fang, Weiyu Du, Hang Wang, Junshan Zhang

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments An earlier version of this paper was submitted to NeurIPS and received ratings of (7, 6, 6). The reviewers' comments and the original draft are available at OpenReview. This version contains minor modifications based on that submission

SimuDICE: Offline Policy Optimization Through World Model Updates and DICE Estimation

Catalin E. Brita, Stephan Bongers, Frans A. Oliehoek

专题命中 具身推理 ：world model(title,abstract)；分类 cs.AI、cs.LG

Comments Published at BNAIC/BeNeLearn 2024