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Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
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2026-03-03 23:23:00
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Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models Chuofan Ma 1 ,    Yi Jiang 2† ,    Jiannan Wu 1 ,    Zehuan Yuan 2 ,    Xiaojuan Qi 1† ,    1 The University of Hong Kong,    2 ByteDance Inc. Paper Code 🤗 Demo (Comming Soon) Abstract We introduce Groma, a Multimodal Large Language Model (MLLM) with grounded and fine-grained visual perception ability. Beyond holistic image understanding, Groma is adept at region-level tasks such as region captioning and visual grounding. Such capabilities are built upon a localized visual tokenization mechanism, where an image is decomposed into regions of interest and subsequently encoded into region tokens. By integrating region tokens into user instructions and model responses...
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