Add our ICLR2025 work Dynamic-LLaVA #121
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Add paper "Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification" Dynamic-LLaVA is the first MLLM acceleration framework that simultaneously sparsifies both vision and language contexts while integrating inference efficiency optimization across different MLLM inference modes into a unified framework. In practice, Dynamic-LLaVA can achieve additional inference efficiency throughout the entire generation process, with negligible understanding and generation ability degradation or even performance gains compared to the full-context inference baselines. GitHub: https://github.com/Osilly/dynamic_llava
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Add paper "Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification" Dynamic-LLaVA is the first MLLM acceleration framework that simultaneously sparsifies both vision and language contexts while integrating inference efficiency optimization across different MLLM inference modes into a unified framework. In practice, Dynamic-LLaVA can achieve additional inference efficiency throughout the entire generation process, with negligible understanding and generation ability degradation or even performance gains compared to the full-context inference baselines. GitHub: https://github.com/Osilly/dynamic_llava