most citedLearn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning

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cs.CL2025

Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model

Wenke Huang, Jian Liang, Xianda Guo +14

Multi-modal Large Language Models (MLLMs) integrate visual and linguistic reasoning to address complex tasks such as image captioning and visual question answering. While MLLMs dem…

cs.CL2024★ 1 cited

Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning

Wenke Huang, Jian Liang, Zekun Shi +6

Multimodal Large Language Model (MLLM) have demonstrated strong generalization capabilities across diverse distributions and tasks, largely due to extensive pre-training datasets.…