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Vector Quantization (VQ) is essential for discretizing continuous representations in unsupervised learning but suffers from representation collapse, causing low codebook utilization and limiting scalability.
Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs
A.W. Rix, J.G. Beerends, M.P. Hollier, and A.P. Hekstra · 2001
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville · 2013
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Auto-encoding variational bayes
Diederik P. Kingma and Max Welling · 2013
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2017
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Neural discrete representation learning
Aaron van den Oord, Oriol Vinyals, and koray kavukcuoglu · 2017
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Theory and experiments on vector quantized autoencoders
Aurko Roy, Ashish Vaswani, Arvind Neelakantan, and Niki Parmar · 2018
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Generating diverse high-fidelity images with vq-vae-2
Ali Razavi, Aaron van den Oord, and Oriol Vinyals · 2019
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Libritts: A corpus derived from librispeech for text-to-speech
Heiga Zen, Viet Dang, Rob Clark, Yu Zhang, Ron J Weiss, Ye Jia, Zhifeng Chen, and Yonghui Wu · 2019
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wav2vec 2.0: A framework for self-supervised learning of speech representations
Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli · 2020
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Autoregressive image generation using residual quantization
Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, and Wook-Shin Han · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Utmos: Utokyo-sarulab system for voicemos challenge 2022
Takaaki Saeki, Detai Xin, Wataru Nakata, Tomoki Koriyama, Shinnosuke Takamichi, and Hiroshi Saruwatari · 2022
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SQ-VAE: Variational Bayes on discrete representation with self-annealed stochastic quantization
Yuhta Takida, Takashi Shibuya, Weihsiang Liao, Chieh-Hsin Lai, Junki Ohmura, Toshimitsu Uesaka, Naoki Murata, Shusuke Takahashi, Toshiyuki Kumakura, and Yuki Mitsufuji · 2022
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High-quality pluralistic image completion via code shared vqgan
Chuanxia Zheng, Guoxian Song, Tat-Jen Cham, Jianfei Cai, Dinh Q. Phung, and Linjie Luo · 2022
Online clustered codebook
Chuanxia Zheng and Andrea Vedaldi · 2023
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Genie: Generative interactive environments
Jake Bruce, Michael D Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Maria Elisabeth Bechtle, Feryal Behbahani, Stephanie C.Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando De Freitas, Satinder Singh, and Tim Rocktäschel · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
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Foldtoken: Learning protein language via vector quantization and beyond
Zhangyang Gao, Cheng Tan, Jue Wang, Yufei Huang, Lirong Wu, and Stan Z Li · 2024
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Wavtokenizer: an efficient acoustic discrete codec tokenizer for audio language modeling
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Audiolm: A language modeling approach to audio generation
Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matt Sharifi, Dominik Roblek, Olivier Teboul, David Grangier, Marco Tagliasacchi, and Neil Zeghidour · 2023
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High fidelity neural audio compression
Alexandre Défossez, Jade Copet, Gabriel Synnaeve, and Yossi Adi · 2023
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Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks
Minyoung Huh, Brian Cheung, Pulkit Agrawal, and Phillip Isola · 2023
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Vector quantized wasserstein auto-encoder
Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, and Dinh Phung · 2023
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Neural codec language models are zero-shot text to speech synthesizers
Chengyi Wang, Sanyuan Chen, Yu Wu, Ziqiang Zhang, Long Zhou, Shujie Liu, Zhuo Chen, Yanqing Liu, Huaming Wang, Jinyu Li, et al · 2023
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Sc-vae: Sparse coding-based variational autoencoder
Pan Xiao, Peijie Qiu, and Aristeidis Sotiras · 2023
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Shengpeng Ji, Ziyue Jiang, Xize Cheng, Yifu Chen, Minghui Fang, Jialong Zuo, Qian Yang, Ruiqi Li, Ziang Zhang, Xiaoda Yang, et al · 2024
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Finite scalar quantization: VQ-VAE made simple
Fabian Mentzer, David Minnen, Eirikur Agustsson, and Michael Tschannen · 2024
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Vocos: Closing the gap between time-domain and fourier-based neural vocoders for high-quality audio synthesis
Hubert Siuzdak · 2024
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Autoregressive model beats diffusion: Llama for scalable image generation
Peize Sun, Yi Jiang, Shoufa Chen, Shilong Zhang, Bingyue Peng, Ping Luo, and Zehuan Yuan · 2024
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Scaling laws with vocabulary: Larger models deserve larger vocabularies
Chaofan Tao, Qian Liu, Longxu Dou, Niklas Muennighoff, Zhongwei Wan, Ping Luo, Min Lin, and Ngai Wong · 2024
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Chameleon: Mixed-modal early-fusion foundation models
Chameleon Team · 2024
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Language model beats diffusion - tokenizer is key to visual generation
Lijun Yu, Jose Lezama, Nitesh Bharadwaj Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G Hauptmann, Boqing Gong, Ming-Hsuan Yang, Irfan Essa, David A Ross, and Lu Jiang · 2024
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Speechtokenizer: Unified speech tokenizer for speech language models
Xin Zhang, Dong Zhang, Shimin Li, Yaqian Zhou, and Xipeng Qiu · 2024
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