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cs.CV2024
iLLaVA: An Image is Worth Fewer Than 1/3 Input Tokens in Large Multimodal Models
Lianyu Hu, Liqing Gao, Fanhua Shang +2
Recent methods have made notable progress in accelerating Large Vision-Language Models (LVLMs) by exploiting the inherent redundancy in visual inputs. Most existing approaches, how…
cs.CV2024
Deep Correlated Prompting for Visual Recognition with Missing Modalities
Lianyu Hu, Tongkai Shi, Wei Feng +2
Large-scale multimodal models have shown excellent performance over a series of tasks powered by the large corpus of paired multimodal training data. Generally, they are always ass…
cs.CV2024
Completed Feature Disentanglement Learning for Multimodal MRIs Analysis
Tianling Liu, Hongying Liu, Fanhua Shang +3
Multimodal MRIs play a crucial role in clinical diagnosis and treatment. Feature disentanglement (FD)-based methods, aiming at learning superior feature representations for multimo…