2026
Towards Multimodal Large Language Models with Both Training and Inference Efficiency
ICML 2026poster
Multimodal Large Language Models (MLLMs) mainly fall into two architectures, each involving a trade-off between training and inference efficiency: embedding space alignment (e.g. LLaVA series) is inefficient during inference, while cross-attention space alignment (e.g. Flamingo) is inefficient in tr…