[[Paper]](https://arxiv.org/abs/2509.19244) [[Project Site]](https://homepage.jackli.org/projects/lavida_o/index.html) [[Huggingface]](https://huggingface.co/jacklishufan/LaViDa-O-v1.0/tree/main)
Las características principales de adobe-research/lavida-o son: Multimodal Diffusion Models.
Las alternativas de código abierto para adobe-research/lavida-o incluyen: ml-gsai/llada — LLaDA is a masked diffusion language model and conditional text generator. It generates text by iteratively refining… vectorspacelab/omnigen — OmniGen is a unified image generation model and diffusion framework that processes text, images, and vision tasks… fudoki-hku/fudoki — This repository is the official implementation of FUDOKI: Discrete Flow-based Unified Understanding and Generation via… hustvl/diffusionvl — DiffusionVL: Translating Any Autoregressive Models into Diffusion Vision Language Models. jacklishufan/lavida — [[Paper]](paper/paper.pdf) [[Arxiv]](https://arxiv.org/abs/2505.16839) [[Checkpoints]](https://huggingface.co/collectio… gen-verse/mmada — Multimodal Large Diffusion Language Models (NeurIPS 2025).
LLaDA is a masked diffusion language model and conditional text generator. It generates text by iteratively refining masked tokens through a diffusion process rather than predicting the next token in a sequence. The project functions as a vision-language diffusion model, converting visual inputs into text responses. It also serves as a preference optimization framework that uses log-likelihood estimation and evidence lower bounds to tune model responses. The system supports multi-round conversational AI and text sequence evaluation. It integrates vision-language embedding for cross-modal con
OmniGen is a unified image generation model and diffusion framework that processes text, images, and vision tasks through a single system. It functions as a multimodal diffusion framework that treats diverse vision operations as unified image synthesis problems using shared model weights, removing the need for external adapter modules. The system supports subject-driven image generation to preserve the identity of objects from reference photos and allows for multi-reference image synthesis. It also operates as an instruction-based image editor, modifying visual content through natural languag
This repository is the official implementation of FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities.
Multimodal Large Diffusion Language Models (NeurIPS 2025)