3 citations · 5 across the 5 of their papers we have counts for
5 papers
FineRS: Fine-grained Reasoning and Segmentation of Small Objects with Reinforcement Learning
Lu Zhang, Jiazuo Yu, Haomiao Xiong +4
Multi-modal Large Language Models (MLLMs) have shown remarkable capabilities across a wide range of vision-language tasks. However, due to the restricted input resolutions, MLLMs f…
Regularizing Subspace Redundancy of Low-Rank Adaptation
Yue Zhu, Haiwen Diao, Shang Gao +8
Low-Rank Adaptation (LoRA) and its variants have delivered strong capability in Parameter-Efficient Transfer Learning (PETL) by minimizing trainable parameters and benefiting from…
Streaming Video Understanding and Multi-round Interaction with Memory-enhanced Knowledge
Haomiao Xiong, Zongxin Yang, Jiazuo Yu +4
Recent advances in Large Language Models (LLMs) have enabled the development of Video-LLMs, advancing multimodal learning by bridging video data with language tasks. However, curre…
LLMs Can Evolve Continually on Modality for X-Modal Reasoning
Jiazuo Yu, Haomiao Xiong, Lu Zhang +7
Multimodal Large Language Models (MLLMs) have gained significant attention due to their impressive capabilities in multimodal understanding. However, existing methods rely heavily…
Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters
Jiazuo Yu, Yunzhi Zhuge, Lu Zhang +4
Continual learning can empower vision-language models to continuously acquire new knowledge, without the need for access to the entire historical dataset. However, mitigating the p…