🔥 Uni-Edit: Intelligent Editing Is A General Task For Unified Model Tuning

💡 The paper introduces Uni-Edit, a novel intelligent image editing task designed to enhance unified multimodal models' understanding, generation, and editing capabilities. Currently, these models are trained using complex multi-stage pipelines and mixed multi-task training, which can lead to performance trade-offs rather than mutual reinforcement. To address this issue, Uni-Edit proposes a single task, single training stage, and single dataset approach. The authors identify image editing as an ideal general task that naturally demands both visual understanding and generation. However, existing editing data relies on simplistic instructions, which underutilize a model's understanding capacity.

To overcome this limitation, the authors develop an automated and scalable data synthesis pipeline that transforms diverse visual question answering data into complex and effective editing instructions with embedded questions and nested logic. This pipeline yields Uni-Edit-148k, a dataset pairing diverse reasoning-intensive instructions with high-quality edited images. The authors conduct extensive experiments on two models, BAGEL and Janus-Pro, and demonstrate that tuning solely on Uni-Edit achieves comprehensive enhancements across all three capabilities without any auxiliary operations. The results show that Uni-Edit is a general task that can unify and improve the performance of unified multimodal models, making it a valuable contribution to the field of data science and artificial intelligence.

📅 Published on May 20

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2605.21487
• PDF: https://arxiv.org/pdf/2605.21487
• Project Page: https://zhengdian1.github.io/Uni-Edit-proj/

🤖 Models citing this paper:
• https://huggingface.co/Uni-Edit/Uni-Edit-BAGEL

📊 Datasets citing this paper:
• https://huggingface.co/datasets/Uni-Edit/Train-Data

━━━━━━━━━━━━━━━━━━━━━━━━
📢 By: https://xn--r1a.website/PaperNexus

#IntelligentImageEditing #UnifiedMultimodalModels #ImageEditingTasks #MultimodalModelTuning #MultitaskLearningApproaches