Analyzing Image Tokenizer Scaling via Multimodal Continual Pretraining

A controlled autoregressive testbed shows that image tokenizer performance varies significantly across text, T2I, and I2T tasks. Results indicate that loss analysis must be task-specific, as different tokenizers exhibit distinct scaling behaviors when modeling visual and text tokens jointly.