InternSVG: Towards Unified SVG Tasks with Multimodal Large Language Models

InternSVG is a new initiative designed to streamline the modeling of Scalable Vector Graphics (SVG) by leveraging multimodal large language models. It addresses the existing challenge of fragmented datasets in SVG tasks, which has hindered the transferability of methods across different applications. By introducing the InternSVG family, the initiative aims to provide a unified framework that enhances users’ ability to understand, edit, and generate SVG content more effectively. This approach is claimed to improve the overall user experience by offering a more cohesive and integrated solution. The use of multimodal large language models is central to this effort, enabling better handling of diverse SVG-related tasks within a single system. As a result, InternSVG promises to simplify workflows and promote consistency in SVG processing. The initiative reflects ongoing efforts in the AI community to unify fragmented methodologies and datasets for more robust and transferable solutions.