3 papers
cs.CV2025
LOP: Learning Optimal Pruning for Efficient On-Demand MLLMs Scaling
Zhihan Zhang, Xiang Pan, Hongchen Wei +1
Structural pruning techniques are essential for deploying multimodal large language models (MLLMs) across various hardware platforms, from edge devices to cloud servers. However, c…
cs.CV2025
Training-Free Reasoning and Reflection in MLLMs
Hongchen Wei, Zhenzhong Chen
Recent advances in Reasoning LLMs (e.g., DeepSeek-R1 and OpenAI-o1) have showcased impressive reasoning capabilities via reinforcement learning. However, extending these capabiliti…
cs.CV2023
Improving Generalization of Image Captioning with Unsupervised Prompt Learning
Hongchen Wei, Zhenzhong Chen
Pretrained visual-language models have demonstrated impressive zero-shot abilities in image captioning, when accompanied by hand-crafted prompts. Meanwhile, hand-crafted prompts ut…