The article discusses using deep learning technology to evaluate the quality of patents. The researchers developed a model that combines patent text content to assess patent quality indicators. They trained the model using US patents and then transferred it to Chinese patents using active learning and transfer learning techniques. The collaborative training approach significantly improved the model's prediction accuracy and migration effectiveness. The study found that the Chinese patent quality evaluation model produced good results, providing valuable decision support for companies and guiding future research in the field.