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cs.CV2024
LIME: Less Is More for MLLM Evaluation
King Zhu, Qianbo Zang, Shian Jia +18
Multimodal Large Language Models (MLLMs) are evaluated on various benchmarks, such as image captioning, visual question answering, and reasoning. However, many of these benchmarks…
cs.CV2023★ 1 cited
LRRU: Long-short Range Recurrent Updating Networks for Depth Completion
Yufei Wang, Bo Li, Ge Zhang +3
Existing deep learning-based depth completion methods generally employ massive stacked layers to predict the dense depth map from sparse input data. Although such approaches greatl…