1 citations · 2 across the 4 of their papers we have counts for
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MM-Instruct: Generated Visual Instructions for Large Multimodal Model Alignment
Jihao Liu, Xin Huang, Jinliang Zheng +5
This paper introduces MM-Instruct, a large-scale dataset of diverse and high-quality visual instruction data designed to enhance the instruction-following capabilities of large mul…
Enhancing Vision-Language Model with Unmasked Token Alignment
Jihao Liu, Jinliang Zheng, Boxiao Liu +2
Contrastive pre-training on image-text pairs, exemplified by CLIP, becomes a standard technique for learning multi-modal visual-language representations. Although CLIP has demonstr…
Instruction-Guided Visual Masking
Jinliang Zheng, Jianxiong Li, Sijie Cheng +6
Instruction following is crucial in contemporary LLM. However, when extended to multimodal setting, it often suffers from misalignment between specific textual instruction and targ…
GLID: Pre-training a Generalist Encoder-Decoder Vision Model
Jihao Liu, Jinliang Zheng, Yu Liu +1
This paper proposes a GeneraLIst encoder-Decoder (GLID) pre-training method for better handling various downstream computer vision tasks. While self-supervised pre-training approac…