3 papers
cs.CV2026
Efficient Multimodal Large Language Models: A Survey
Yizhang Jin, Jian Li, Yexin Liu +10
In the past year, Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in tasks such as visual question answering, visual understanding and reasoning.…
cs.CV2025
Unveiling the Ignorance of MLLMs: Seeing Clearly, Answering Incorrectly
Yexin Liu, Zhengyang Liang, Yueze Wang +8
Multimodal Large Language Models (MLLMs) have displayed remarkable performance in multi-modal tasks, particularly in visual comprehension. However, we reveal that MLLMs often gener…
cs.CV2024
SynArtifact: Classifying and Alleviating Artifacts in Synthetic Images via Vision-Language Model
Bin Cao, Jianhao Yuan, Yexin Liu +4
In the rapidly evolving area of image synthesis, a serious challenge is the presence of complex artifacts that compromise perceptual realism of synthetic images. To alleviate artif…