WorldModelPapers

Paper collections of the continuous effort start from World Models.

Papers

1. World Models.

   David Ha, Jürgen Schmidhuber [pdf], 2018.3

2. Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

   Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy Lillicrap, David Silver [pdf], 2019.11

3. Dream to Control: Learning Behaviors by Latent Imagination.

   Danijar Hafner, Timothy Lillicrap, Jimmy Ba, Mohammad Norouzi [pdf], 2019.12

4. Mastering Atari with Discrete World Models.

   Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, Jimmy Ba [pdf], 2020.10

5. Mastering Atari Games with Limited Data.

   Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao [pdf], 2021.11

6. Temporal Difference Learning for Model Predictive Control

   Nicklas Hansen, Xiaolong Wang, Hao Su [pdf], 2022.3

7. A Path Towards Autonomous Machine Intelligence.

   Yann LeCun [pdf], 2022.6

8. DayDreamer: World Models for Physical Robot Learning.

   Philipp Wu, Alejandro Escontrela, Danijar Hafner, Ken Goldberg, Pieter Abbeel [pdf], 2022.6

9. Model-Based Imitation Learning for Urban Driving.

   Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zak Murez, Corina Gurau, Hudson Yeo, Alex Kendall, Roberto Cipolla, Jamie Shotton [pdf], 2022.10

10. Mastering Diverse Domains through World Models.

    Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, Timothy Lillicrap [pdf], 2023.1

11. Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture.

    Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael Rabbat, Yann LeCun, Nicolas Ballas [pdf], 2023.1

12. Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling.

    Kolby Nottingham, Prithviraj Ammanabrolu, Alane Suhr, Yejin Choi, Hannaneh Hajishirzi, Sameer Singh, Roy Fox [pdf], 2023.1

13. Learning Universal Policies via Text-Guided Video Generation.

    Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel [pdf], 2023.2

14. Language Models Meet World Models: Embodied Experiences Enhance Language Models

    Jiannan Xiang and Tianhua Tao and Yi Gu and Tianmin Shu and Zirui Wang and Zichao Yang and Zhiting Hu [pdf], 2023.5

15. Reasoning with Language Model is Planning with World Model

    Shibo Hao, Yi Gu, Haodi Ma, Joshua Jiahua Hong, Zhen Wang, Daisy Zhe Wang, Zhiting Hu [pdf], 2023.5

16. From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought

    Lionel Wong, Gabriel Grand, Alexander K Lew, Noah D Goodman, Vikash K Mansinghka, Jacob Andreas, Joshua B Tenenbaum [pdf], 2023.6

17. Learning to Model the World with Language

    Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca Dragan [pdf], 2023.7

18. GAIA-1: A Generative World Model for Autonomous Driving.

    Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, Gianluca Corrado [pdf], 2023.9

19. DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving.

    Xiaofeng Wang, Zheng Zhu, Guan Huang, Xinze Chen, Jiwen Lu [pdf], 2023.9

20. Video Language Planning.

    Yilun Du, Mengjiao Yang, Pete Florence, Fei Xia, Ayzaan Wahid, Brian Ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B. Tenenbaum, Leslie Kaelbling, Andy Zeng, Jonathan Tompson [pdf], 2023.10

21. Finetuning Offline World Models in the Real World

    Yunhai Feng, Nicklas Hansen, Ziyan Xiong, Chandramouli Rajagopalan, Xiaolong Wang [pdf], 2023.10

22. TD-MPC2: Scalable, Robust World Models for Continuous Control

    Nicklas Hansen, Hao Su, Xiaolong Wang [pdf], 2023.10

23. Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion

    Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, Raquel Urtasun [pdf], 2023.11

24. Gradient-based Planning with World Models

    Jyothir S V, Siddhartha Jalagam, Yann LeCun, Vlad Sobal [pdf], 2023.12

25. World Models via Policy-Guided Trajectory Diffusion

    Marc Rigter, Jun Yamada, Ingmar Posner [pdf], 2023.12

26. Diffusion World Model

    Zihan Ding, Amy Zhang, Yuandong Tian, Qinqing Zheng [pdf],2024.2

27. Genie: Generative Interactive Environments

    Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal Behbahani, Stephanie Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel [pdf], 2024.2

28. Learning and Leveraging World Models in Visual Representation Learning

    Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun [pdf], 2024.3

29. Diffusion for World Modeling: Visual Details Matter in Atari

    Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos Storkey, Tim Pearce, François Fleuret [pdf], 2024.5

30. Pandora: Towards General World Model with Natural Language Actions and Video States

    Jiannan Xiang, Guangyi Liu, Yi Gu, Qiyue Gao, Yuting Ning, Yuheng Zha, Zeyu Feng, Tianhua Tao, Shibo Hao, Yemin Shi, Zhengzhong Liu, Eric P. Xing, Zhiting Hu [pdf], 2024.5

31. iVideoGPT: Interactive VideoGPTs are Scalable World Models

    Jialong Wu, Shaofeng Yin, Ningya Feng, Xu He, Dong Li, Jianye Hao, Mingsheng Long [pdf], 2024.5

32. PWM: Policy Learning with Large World Models

    Ignat Georgiev, Varun Giridhar, Nicklas Hansen, Animesh Garg [pdf], 2024.7

Previous collections

Here are some paper collections I made (or mainly contributed to) previously and the timestamps for your interests:

• RetrivalLMPapers, or RAG , started from 2022.2
• EnvInteractiveLMPapers , started from 2022.2
• Chain-of-ThoughtsPapers , started from 2022.4
• XLangPaper, code generation, tool-use, web navigation, robotics, etc , started from 2023.7

Have fun!