3 papers
cs.CV2025
From Holistic to Localized: Local Enhanced Adapters for Efficient Visual Instruction Fine-Tuning
Pengkun Jiao, Bin Zhu, Jingjing Chen +2
Efficient Visual Instruction Fine-Tuning (EVIT) seeks to adapt Multimodal Large Language Models (MLLMs) to downstream tasks with minimal computational overhead. However, as task di…
cs.CV2024
RoDE: Linear Rectified Mixture of Diverse Experts for Food Large Multi-Modal Models
Pengkun Jiao, Xinlan Wu, Bin Zhu +3
Large Multi-modal Models (LMMs) have significantly advanced a variety of vision-language tasks. The scalability and availability of high-quality training data play a pivotal role i…
cs.CV2024
Retrieval Augmented Recipe Generation
Guoshan Liu, Hailong Yin, Bin Zhu +3
Given the potential applications of generating recipes from food images, this area has garnered significant attention from researchers in recent years. Existing works for recipe ge…