ReVisiT is a decoding-time algorithm designed for language-vision models (LVLMs) that enhances visual grounding by utilizing internal vision tokens as references. It aligns text generation with visual semantics without altering the underlying model, requiring specific implementations for various Transformer versions. The repository offers setup instructions, evaluation scripts, and integration guidance for users looking to incorporate ReVisiT into their own environments.