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cs.CL2024
Optimus: Accelerating Large-Scale Multi-Modal LLM Training by Bubble Exploitation
Weiqi Feng, Yangrui Chen, Shaoyu Wang +3
Multimodal large language models (MLLMs) have extended the success of large language models (LLMs) to multiple data types, such as image, text and audio, achieving significant perf…
cs.CL2024
CATP: Cross-Attention Token Pruning for Accuracy Preserved Multimodal Model Inference
Ruqi Liao, Chuqing Zhao, Jin Li +4
In response to the rising interest in large multimodal models, we introduce Cross-Attention Token Pruning (CATP), a precision-focused token pruning method. Our approach leverages c…