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From the 1 of 6 linked papers with an AI index.

activity
20242026
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6 papers

cs.CV2026

LaViDa: A Large Diffusion Language Model for Multimodal Understanding

Shufan Li, Konstantinos Kallidromitis, Hritik Bansal +7

LaViDa introduces a diffusion-based vision-language model that combines a vision encoder with discrete diffusion to enable fast parallel decoding and controllable multimodal genera…

cs.CV2025

Image Tokenizer Needs Post-Training

Kai Qiu, Xiang Li, Hao Chen +7

Recent image generative models typically capture the image distribution in a pre-constructed latent space, relying on a frozen image tokenizer. However, there exists a significant…

cs.CV2025

Robust Latent Matters: Boosting Image Generation with Sampling Error Synthesis

Kai Qiu, Xiang Li, Jason Kuen +7

Recent image generation schemes typically capture image distribution in a pre-constructed latent space relying on a frozen image tokenizer. Though the performance of tokenizer play…

cs.SD2024

Efficient Autoregressive Audio Modeling via Next-Scale Prediction

Kai Qiu, Xiang Li, Hao Chen +5

Audio generation has achieved remarkable progress with the advance of sophisticated generative models, such as diffusion models (DMs) and autoregressive (AR) models. However, due t…

cs.CV2024

ImageFolder: Autoregressive Image Generation with Folded Tokens

Xiang Li, Kai Qiu, Hao Chen +4

Image tokenizers are crucial for visual generative models, e.g., diffusion models (DMs) and autoregressive (AR) models, as they construct the latent representation for modeling. In…

cs.CV2024

XQ-GAN: An Open-source Image Tokenization Framework for Autoregressive Generation

Xiang Li, Kai Qiu, Hao Chen +5

Image tokenizers play a critical role in shaping the performance of subsequent generative models. Since the introduction of VQ-GAN, discrete image tokenization has undergone remark…