3 papers
cs.LG2025
RollingQ: Reviving the Cooperation Dynamics in Multimodal Transformer
Haotian Ni, Yake Wei, Hang Liu +4
Multimodal learning faces challenges in effectively fusing information from diverse modalities, especially when modality quality varies across samples. Dynamic fusion strategies, s…
cs.CV2025
MokA: Multimodal Low-Rank Adaptation for MLLMs
Yake Wei, Yu Miao, Dongzhan Zhou +1
In this paper, we reveal that most current efficient multimodal fine-tuning methods are hindered by a key limitation: they are directly borrowed from LLMs, often neglecting the int…
cs.MM2024
Enhancing Modality Representation and Alignment for Multimodal Cold-start Active Learning
Meng Shen, Yake Wei, Jianxiong Yin +3
Training multimodal models requires a large amount of labeled data. Active learning (AL) aim to reduce labeling costs. Most AL methods employ warm-start approaches, which rely on s…