机器人 / 具身智能

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

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making

Jonathan Light, Sixue Xing, Yuanzhe Liu, Weiqin Chen, Min Cai, Xiusi Chen, Guanzhi Wang, Wei Cheng, Yisong Yue, Ziniu Hu

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

Comments Published at Language Gamification Workshop 2024 @ NeurIPS

Adaptive World Models: Learning Behaviors by Latent Imagination Under Non-Stationarity

Emiliyan Gospodinov, Vaisakh Shaj, Philipp Becker, Stefan Geyer, Gerhard Neumann

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

Comments Accepted at NeurIPS 2024 Workshop Adaptive Foundation Models

IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI

Xiaoyu Chen, Junliang Guo, Tianyu He, Chuheng Zhang, Pushi Zhang, Derek Cathera Yang, Li Zhao, Jiang Bian

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

Language Agents Meet Causality -- Bridging LLMs and Causal World Models

John Gkountouras, Matthias Lindemann, Phillip Lippe, Efstratios Gavves, Ivan Titov

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

Comments Project page: https://j0hngou.github.io/LLMCWM/

Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Shenyuan Gao, Jiazhi Yang, Li Chen, Kashyap Chitta, Yihang Qiu, Andreas Geiger, Jun Zhang, Hongyang Li

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

Comments NeurIPS 2024. Code and model: https://github.com/OpenDriveLab/Vista, demo page: https://vista-demo.github.io

Probing Multimodal LLMs as World Models for Driving

Shiva Sreeram, Tsun-Hsuan Wang, Alaa Maalouf, Guy Rosman, Sertac Karaman, Daniela Rus

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

Comments https://github.com/sreeramsa/DriveSim https://www.youtube.com/watch?v=Fs8jgngOJzU

One-shot World Models Using a Transformer Trained on a Synthetic Prior

Fabio Ferreira, Moreno Schlageter, Raghu Rajan, Andre Biedenkapp, Frank Hutter

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

Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Zihan Ding, Amy Zhang, Yuandong Tian, Qinqing Zheng

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

A Notion of Complexity for Theory of Mind via Discrete World Models

X. Angelo Huang, Emanuele La Malfa, Samuele Marro, Andrea Asperti, Anthony Cohn, Michael Wooldridge

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

Comments Accepted EMNLP 2024, Website https://flecart.github.io/complexity-tom-dwm

Spatial Reasoning and Planning for Deep Embodied Agents

Shu Ishida

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

Comments DPhil Thesis - Engineering Science, University of Oxford. Original copy available at https://ora.ox.ac.uk/objects/uuid:19489c19-dc5a-464a-831d-bbf887687c41

Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous Driving

Lingyu Xiao, Jiang-Jiang Liu, Sen Yang, Xiaofan Li, Xiaoqing Ye, Wankou Yang, Jingdong Wang

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

OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving

Julong Wei, Shanshuai Yuan, Pengfei Li, Qingda Hu, Zhongxue Gan, Wenchao Ding

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

CarDreamer: Open-Source Learning Platform for World Model based Autonomous Driving

Dechen Gao, Shuangyu Cai, Hanchu Zhou, Hang Wang, Iman Soltani, Junshan Zhang

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

Comments Dechen Gao, Shuangyu Cai, Hanchu Zhou, Hang Wang contributed equally