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Video generative models pre-trained on large-scale internet datasets have achieved remarkable success, excelling at producing realistic synthetic videos.
Dyna, an integrated architecture for learning, planning, and reacting
Richard S Sutton · 1991
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Reinforcement learning - an introduction
Richard S. Sutton and Andrew G. Barto · 1998
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Scope of validity of psnr in image/video quality assessment
Quan Huynh-Thu and Mohammed Ghanbari · 2008
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Mastering atari with discrete world models
Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, and Jimmy Ba · 2010
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The arcade learning environment: An evaluation platform for general agents
Marc G Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
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Playing atari with deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Self-supervised visual planning with temporal skip connections
Frederik Ebert, Chelsea Finn, Alex X Lee, and Sergey Levine · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Revisiting the arcade learning environment: Evaluation protocols and open problems for general agents
Marlos C Machado, Marc G Bellemare, Erik Talvitie, Joel Veness, Matthew Hausknecht, and Michael Bowling · 2018
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Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, et al · 2018
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Towards accurate generative models of video: A new metric & challenges
Thomas Unterthiner, Sjoerd Van Steenkiste, Karol Kurach, Raphael Marinier, Marcin Michalski, and Sylvain Gelly · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Learning latent dynamics for planning from pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, and James Davidson · 2019
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Leveraging procedural generation to benchmark reinforcement learning
Karl Cobbe, Chris Hesse, Jacob Hilton, and John Schulman · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Conservative q-learning for offline reinforcement learning
Aviral Kumar, Aurick Zhou, George Tucker, and Sergey Levine · 2020
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Fitvid: Overfitting in pixel-level video prediction
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, and Dumitru Erhan · 2021
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Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 2021
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Phasic policy gradient
Karl W Cobbe, Jacob Hilton, Oleg Klimov, and John Schulman · 2021
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Videogpt: Video generation using vq-vae and transformers
Wilson Yan, Yunzhi Zhang, Pieter Abbeel, and Aravind Srinivas · 2021
Cited alongside, same era.
Maskvit: Masked visual pre-training for video prediction
Agrim Gupta, Stephen Tian, Yunzhi Zhang, Jiajun Wu, Roberto Martín-Martín, and Li Fei-Fei · 2022
Cited alongside, same era.
The 37 implementation details of proximal policy optimization
Shengyi Huang, Rousslan Fernand Julien Dossa, Antonin Raffin, Anssi Kanervisto, and Weixun Wang · 2022
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Panda-70m: Captioning 70m videos with multiple cross-modality teachers
Tsai-Shien Chen, Aliaksandr Siarohin, Willi Menapace, Ekaterina Deyneka, Hsiang-wei Chao, Byung Eun Jeon, Yuwei Fang, Hsin-Ying Lee, Jian Ren, Ming-Hsuan Yang, and Sergey Tulyakov · 2024
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Oasis: A universe in a transformer
Decart, Julian Quevedo, Quinn McIntyre, Spruce Campbell, Xinlei Chen, and Robert Wachen · 2024
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Zihan Ding, Amy Zhang, Yuandong Tian, and Qinqing Zheng · 2024
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The matrix: Infinite-horizon world generation with real-time moving control
Ruili Feng, Han Zhang, Zhantao Yang, Jie Xiao, Zhilei Shu, Zhiheng Liu, Andy Zheng, Yukun Huang, Yu Liu, and Hongyang Zhang · 2024
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Offline reinforcement learning with implicit q-learning
Ilya Kostrikov, Ashvin Nair, and Sergey Levine · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2022
Cited alongside, same era.
Mcvd-masked conditional video diffusion for prediction, generation, and interpolation
Vikram Voleti, Alexia Jolicoeur-Martineau, and Chris Pal · 2022
Cited alongside, same era.
Stable video diffusion: Scaling latent video diffusion models to large datasets
Andreas Blattmann, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi, Zion English, Vikram Voleti, Adam Letts, et al · 2023
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Pixart- α \alpha : Fast training of diffusion transformer for photorealistic text-to-image synthesis, 2023
Junsong Chen, Jincheng Yu, Chongjian Ge, Lewei Yao, Enze Xie, Yue Wu, Zhongdao Wang, James Kwok, Ping Luo, Huchuan Lu, and Zhenguo Li · 2023
Cited alongside, same era.
Mastering diverse domains through world models
Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, and Timothy Lillicrap · 2023
Cited alongside, same era.
Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
Cited alongside, same era.
Bin Lin, Yunyang Ge, Xinhua Cheng, Zongjian Li, Bin Zhu, Shaodong Wang, Xianyi He, Yang Ye, Shenghai Yuan, Liuhan Chen, et al · 2024
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Latte: Latent diffusion transformer for video generation
Xin Ma, Yaohui Wang, Gengyun Jia, Xinyuan Chen, Ziwei Liu, Yuan-Fang Li, Cunjian Chen, and Yu Qiao · 2024
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The generalization gap in offline reinforcement learning
Ishita Mediratta, Qingfei You, Minqi Jiang, and Roberta Raileanu · 2024
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Genie 2: A large-scale foundation world model
Jack Parker-Holder, Philip Ball, Jake Bruce, Vibhavari Dasagi, Kristian Holsheimer, Christos Kaplanis, Alexandre Moufarek, Guy Scully, Jeremy Shar, Jimmy Shi, Stephen Spencer, Jessica Yung, Michael Dennis, Sultan Kenjeyev, Shangbang Long, Vlad Mnih, Harris Chan, Maxime Gazeau, Bonnie Li, Fabio Pardo, Luyu Wang, Lei Zhang, Frederic Besse, Tim Harley, Anna Mitenkova, Jane Wang, Jeff Clune, Demis Hassabis, Raia Hadsell, Adrian Bolton, Satinder Singh, and Tim Rocktäschel · 2024
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Movie gen: A cast of media foundation models
Adam Polyak, Amit Zohar, Andrew Brown, Andros Tjandra, Animesh Sinha, Ann Lee, Apoorv Vyas, Bowen Shi, Chih-Yao Ma, Ching-Yao Chuang, et al · 2024
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Avid: Adapting video diffusion models to world models
Marc Rigter, Tarun Gupta, Agrin Hilmkil, and Chao Ma · 2024
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Visual autoregressive modeling: Scalable image generation via next-scale prediction
Keyu Tian, Yi Jiang, Zehuan Yuan, BINGYUE PENG, and Liwei Wang · 2024
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Diffusion models are real-time game engines
Dani Valevski, Yaniv Leviathan, Moab Arar, and Shlomi Fruchter · 2024
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ivideogpt: Interactive videogpts are scalable world models
Jialong Wu, Shaofeng Yin, Ningya Feng, Xu He, Dong Li, Jianye Hao, and Mingsheng Long · 2024
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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, et al · 2024
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Yang Zhang, Chenjia Bai, Bin Zhao, Junchi Yan, Xiu Li, and Xuelong Li · 2024
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Open-sora: Democratizing efficient video production for all, March 2024
Zangwei Zheng, Xiangyu Peng, Tianji Yang, Chenhui Shen, Shenggui Li, Hongxin Liu, Yukun Zhou, Tianyi Li, and Yang You · 2024
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Irasim: Learning interactive real-robot action simulators
Fangqi Zhu, Hongtao Wu, Song Guo, Yuxiao Liu, Chilam Cheang, and Tao Kong · 2024
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Gamegen-$\mathbb{X}$: Interactive open-world game video generation
Haoxuan Che, Xuanhua He, Quande Liu, Cheng Jin, and Hao Chen · 2025
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Gamefactory: Creating new games with generative interactive videos
Jiwen Yu, Yiran Qin, Xintao Wang, Pengfei Wan, Di Zhang, and Xihui Liu · 2025
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