Core Viewpoint - Li Auto has made significant strides in AI technology, particularly with its QR-LoRA framework, which enhances the customization of generative models while maintaining high-quality output and feature independence [3][41]. Group 1: Research Achievements - Li Auto had 8 papers accepted at ICCV 2025, with 3 from the base model team, showcasing its commitment to technological innovation [3]. - The QR-LoRA framework introduces a new paradigm for image customization, allowing for faster fine-tuning with half the training parameters of traditional methods [3][4]. Group 2: Technical Insights - The QR-LoRA framework addresses the "feature entanglement" problem found in traditional LoRA methods, which often leads to mixed results when combining different styles and contents [9][32]. - By fixing the common foundation and only learning the personalized combinations, QR-LoRA effectively separates content and style, avoiding confusion in generated outputs [19][32]. Group 3: Mathematical Foundation - QR-LoRA employs SVD and QR decomposition to create a structure that naturally incorporates a "common foundation + personalized combination" approach, enhancing the model's efficiency and effectiveness [20][35]. - The mathematical properties of QR-LoRA ensure minimal intervention during parameter updates, which helps avoid overfitting and maintains statistical independence among features [36][37]. Group 4: Practical Applications - QR-LoRA demonstrates strong potential for various applications, enabling independent control and combination of multiple visual features, thus expanding the creative possibilities for users [42][44]. - The framework is adaptable across different generative models and can be integrated into various network layers, ensuring its relevance in future technological advancements [40][41]. Group 5: Future Directions - The introduction of QR-LoRA marks a significant step towards achieving true content and style separation in AI-generated outputs, paving the way for more innovative applications in the field [44][45].