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World models are a powerful paradigm in AI and robotics, enabling agents to reason about the future by predicting visual observations or compact latent states.
Multiscale structural similarity for image quality assessment
Z Wang, EP Simoncelli, and AC Bovik · 2003
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Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 2016
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GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Attention is All you Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
Kurtland Chua, Roberto Calandra, Rowan McAllister, and Sergey Levine · 2018
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Recurrent World Models Facilitate Policy Evolution
David Ha and Jürgen Schmidhuber · 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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Decoupled Weight Decay Regularization
Ilya Loshchilov and Frank Hutter · 2019
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Scheduled Sampling for Transformers
Tsvetomila Mihaylova and André F. T. Martins · 2019
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Language Models are Unsupervised Multitask Learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2020
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Query-Key Normalization for Transformers
Alex Henry, Prudhvi Raj Dachapally, Shubham Shantaram Pawar, and Yuxuan Chen · 2020
Cited alongside, same era.
Classifier-Free Diffusion Guidance
Jonathan Ho and Tim Salimans · 2021
Cited alongside, same era.
Spatial-Temporal Transformer Networks for Traffic Flow Forecasting
Mingxing Xu, Wenrui Dai, Chunmiao Liu, Xing Gao, Weiyao Lin, Guo-Jun Qi, and Hongkai Xiong · 2021
Cited alongside, same era.
Mastering Atari with Discrete World Models
Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, and Jimmy Ba · 2022
Cited alongside, same era.
Temporal Difference Learning for Model Predictive Control
Nicklas A. Hansen, Hao Su, and Xiaolong Wang · 2022
Cited alongside, same era.
CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers
Diffusion for World Modeling: Visual Details Matter in Atari
Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos Storkey, Tim Pearce, and François Fleuret · 2024
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Amir Bar, Gaoyue Zhou, Danny Tran, Trevor Darrell, and Yann LeCun · 2024
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By Tying Embeddings You Are Assuming the Distributional Hypothesis
Francesco Bertolotti and Walter Cazzola · 2024
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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, de Nando Freitas, Satinder Singh, and Tim Rocktäschel · 2024
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Oasis: A Universe in a Transformer
Etched Decart, Quinn McIntyre, Spruce Campbell, Xinlei Chen, and Robert Wachen · 2024
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Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, and Jie Tang · 2022
Cited alongside, same era.
LoRA: Low-Rank Adaptation of Large Language Models
Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2022
Cited alongside, same era.
Transformers are Sample-Efficient World Models
Vincent Micheli, Eloi Alonso, and François Fleuret · 2022
Cited alongside, same era.
Transformer-based World Models Are Happy With 100k Interactions
Jan Robine, Marc Höftmann, Tobias Uelwer, and Stefan Harmeling · 2022
Cited alongside, same era.
TD-MPC2: Scalable, Robust World Models for Continuous Control
Nicklas Hansen, Hao Su, and Xiaolong Wang · 2023
Cited alongside, same era.
Scalable Diffusion Models with Transformers
William Peebles and Saining Xie · 2023
Cited alongside, same era.
STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning
Weipu Zhang, Gang Wang, Jian Sun, Yetian Yuan, and Gao Huang · 2023
Cited alongside, same era.
Later among the works it cites.
LTX-Video: Realtime Video Latent Diffusion
Yoav HaCohen, Nisan Chiprut, Benny Brazowski, Daniel Shalem, Dudu Moshe, Eitan Richardson, Eran Levin, Guy Shiran, Nir Zabari, Ori Gordon, Poriya Panet, Sapir Weissbuch, Victor Kulikov, Yaki Bitterman, Zeev Melumian, and Ofir Bibi · 2024
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HunyuanVideo: A Systematic Framework For Large Video Generative Models
Weijie Kong, Qi Tian, Zijian Zhang, Rox Min, Zuozhuo Dai, Jin Zhou, Jiangfeng Xiong, Xin Li, Bo Wu, Jianwei Zhang, et al · 2024
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CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
Zhuoyi Yang, Jiayan Teng, Wendi Zheng, Ming Ding, Shiyu Huang, Jiazheng Xu, Yuanming Yang, Wenyi Hong, Xiaohan Zhang, Guanyu Feng, et al · 2024
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MineWorld: A Real-Time and Open-Source Interactive World Model on Minecraft
Junliang Guo, Yang Ye, Tianyu He, Haoyu Wu, Yushu Jiang, Tim Pearce, and Jiang Bian · 2025
Closest in time.
Mastering Diverse Control Tasks through World Models
Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, and Timothy Lillicrap · 2025
Closest in time.
Effective World Modeling for Humanoid Robots: Long-Horizon Prediction and Efficient State Compression
Peter Liu, Annabelle Chu, and Yiran Chen · 2025
Closest in time.
Discrete Codebook World Models for Continuous Control
Aidan Scannell, Mohammadreza Nakhaei, Kalle Kujanpää, Yi Zhao, Kevin Luck, Arno Solin, and Joni Pajarinen · 2025
Closest in time.