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cs.CV2025

Sparse-LaViDa: Sparse Multimodal Discrete Diffusion Language Models

Shufan Li, Jiuxiang Gu, Kangning Liu +4

Masked Discrete Diffusion Models (MDMs) have achieved strong performance across a wide range of multimodal tasks, including image understanding, generation, and editing. However, t…

cs.AI2025

OIDA-QA: A Multimodal Benchmark for Analyzing the Opioid Industry Documents Archive

Xuan Shen, Brian Wingenroth, Zichao Wang +12

The opioid crisis represents a significant moment in public health that reveals systemic shortcomings across regulatory systems, healthcare practices, corporate governance, and pub…

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

Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation

Shufan Li, Jiuxiang Gu, Kangning Liu +4

We propose Lavida-O, a unified Masked Diffusion Model (MDM) for multimodal understanding and generation. Unlike existing multimodal MDMs such as MMaDa and Muddit which only support…

cs.CV2025

Refer to Any Segmentation Mask Group With Vision-Language Prompts

Shengcao Cao, Zijun Wei, Jason Kuen +6

Recent image segmentation models have advanced to segment images into high-quality masks for visual entities, and yet they cannot provide comprehensive semantic understanding for c…

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…