AliTok: Towards Sequence Modeling Alignment between Tokenizer and Autoregressive Model

• URL: http://arxiv.org/abs/2506.05289v1
• Date: Thu, 05 Jun 2025 17:45:10 GMT
• Title: AliTok: Towards Sequence Modeling Alignment between Tokenizer and Autoregressive Model
• Authors: Pingyu Wu, Kai Zhu, Yu Liu, Longxiang Tang, Jian Yang, Yansong Peng, Wei Zhai, Yang Cao, Zheng-Jun Zha,
• Abstract summary: We propose a novel Aligned Tokenizer (AliTok) to align the tokenizer and autoregressive model.<n>On ImageNet-256 benchmark, using a standard decoder-only autoregressive model as the generator, AliTok achieves a gFID score of 1.50 and an IS of 305.9.<n>When the parameter count is increased to 662M, AliTok achieves a gFID score of 1.35, surpassing the state-of-the-art diffusion method with 10x faster sampling speed.
• Score: 59.065471969232284
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Autoregressive image generation aims to predict the next token based on previous ones. However, existing image tokenizers encode tokens with bidirectional dependencies during the compression process, which hinders the effective modeling by autoregressive models. In this paper, we propose a novel Aligned Tokenizer (AliTok), which utilizes a causal decoder to establish unidirectional dependencies among encoded tokens, thereby aligning the token modeling approach between the tokenizer and autoregressive model. Furthermore, by incorporating prefix tokens and employing two-stage tokenizer training to enhance reconstruction consistency, AliTok achieves great reconstruction performance while being generation-friendly. On ImageNet-256 benchmark, using a standard decoder-only autoregressive model as the generator with only 177M parameters, AliTok achieves a gFID score of 1.50 and an IS of 305.9. When the parameter count is increased to 662M, AliTok achieves a gFID score of 1.35, surpassing the state-of-the-art diffusion method with 10x faster sampling speed. The code and weights are available at https://github.com/ali-vilab/alitok.

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