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cs.CV2024
Treat Visual Tokens as Text? But Your MLLM Only Needs Fewer Efforts to See
Zeliang Zhang, Phu Pham, Wentian Zhao +6
By treating visual tokens from visual encoders as text tokens, Multimodal Large Language Models (MLLMs) have achieved remarkable progress across diverse visual understanding tasks,…
cs.CV2024
Multimodal Instruction Tuning with Hybrid State Space Models
Jianing Zhou, Han Li, Shuai Zhang +5
Handling lengthy context is crucial for enhancing the recognition and understanding capabilities of multimodal large language models (MLLMs) in applications such as processing high…