WMAAdapter is a novel diffusion model watermarking plugin designed to seamlessly embed user-specified watermarks during the image generation process. It addresses the limitations of traditional post-hoc watermarking methods by integrating watermarking into the diffusion pipeline, ensuring high-quality image generation and robust watermarking. Key contributions include: 1. **Contextual Adapter Structure**: A lightweight, contextual adapter that takes both watermark bits and image features from the VAE decoder, enabling effective knowledge transfer from pre-trained models. 2. **Hybrid Finetuning Strategy**: An additional finetuning step that jointly fine-tunes the adapter and VAE decoder, enhancing image quality and eliminating artifacts. 3. **Efficiency and Robustness**: The plugin is easy to train and use, with a focus on maintaining high image quality and strong watermark robustness. Empirical results demonstrate that WMAAdapter offers strong flexibility, exceptional image generation quality, and competitive watermark robustness. It outperforms existing methods in terms of image quality and robustness, making it suitable for various applications, including copyright protection and image authentication.WMAAdapter is a novel diffusion model watermarking plugin designed to seamlessly embed user-specified watermarks during the image generation process. It addresses the limitations of traditional post-hoc watermarking methods by integrating watermarking into the diffusion pipeline, ensuring high-quality image generation and robust watermarking. Key contributions include: 1. **Contextual Adapter Structure**: A lightweight, contextual adapter that takes both watermark bits and image features from the VAE decoder, enabling effective knowledge transfer from pre-trained models. 2. **Hybrid Finetuning Strategy**: An additional finetuning step that jointly fine-tunes the adapter and VAE decoder, enhancing image quality and eliminating artifacts. 3. **Efficiency and Robustness**: The plugin is easy to train and use, with a focus on maintaining high image quality and strong watermark robustness. Empirical results demonstrate that WMAAdapter offers strong flexibility, exceptional image generation quality, and competitive watermark robustness. It outperforms existing methods in terms of image quality and robustness, making it suitable for various applications, including copyright protection and image authentication.