SignLLM

SignLLM is an open-source framework designed to bring large language model capabilities to sign language understanding and generation. It focuses on bridging the gap between spoken/written language models and sign language communication by working directly with sign language sequences. The tool supports tasks such as sign language recognition, translation, and generation, enabling researchers and developers to build systems that can interpret and produce sign content in a structured, model-friendly format.

SignLLM provides standardized data representations for sign language, along with model architectures and training pipelines tailored to the unique spatial-temporal nature of signing. It is built to integrate with existing LLM ecosystems, allowing multimodal workflows where sign language can be processed alongside text and other modalities. Key features include support for multiple sign languages, modular components for preprocessing and feature extraction, and benchmark datasets and evaluation protocols for reproducible research.