OneFlow: Concurrent Mixed-Modal and Interleaved Generation with Edit Flows
We present OneFlow, the first non-autoregressive multimodal model that enables variable-length and concurrent mixed-modal generation. Unlike autoregressive models that enforce rigid causal ordering between text and image generation, OneFlow combines an insertion-based Edit Flow for discrete text tokens with Flow Matching for image latents. OneFlow enables concurrent text-image synthesis with hierarchical sampling that prioritizes content over grammar. Through controlled experiments across model sizes from 1B to 8B, we demonstrate that OneFlow outperforms autoregressive baselines on both generation and understanding tasks while using up to 50% fewer training FLOPs. OneFlow surpasses both autoregressive and diffusion-based approaches while unlocking new capabilities for concurrent generation, iterative refinement, and natural reasoning-like generation.
Code (0)
등록된 구현이 없습니다.
Tasks
Image GenerationSimilar Papers 제목 키워드 기반
OneFlow: Redesign the Distributed Deep Learning Framework from Scratch
Deep learning frameworks such as TensorFlow and PyTorch provide a productive interface for expressing and training a deep neural network (DNN) model on a single device or using data parallelism. Still, they may not be fl…
Deep LearningMedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants
Recent advancements in mixed-modal generative models have enabled flexible integration of information across image-text content. These models have opened new avenues for developing unified biomedical assistants capable o…
Image CaptioningQuestion AnsweringVisual Question AnsweringTowards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization
Unified vision-language models have made significant progress in multimodal understanding and generation, yet they largely fall short in producing multimodal interleaved outputs, which is a crucial capability for tasks l…
Text-to-Image GenerationReinforcement LearningVisual StorytellingVisual ReasoningOneFlow: One-class flow for anomaly detection based on a minimal volume region
We propose OneFlow - a flow-based one-class classifier for anomaly (outlier) detection that finds a minimal volume bounding region. Contrary to density-based methods, OneFlow is constructed in such a way that its result …
Anomaly DetectionOne-class classifierOutlier DetectionOrthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads
We introduce Orthus, an autoregressive (AR) transformer that excels in generating images given textual prompts, answering questions based on visual inputs, and even crafting lengthy image-text interleaved contents. Unlik…
GPULanguage ModelingLanguage ModellingMME+2