3 citations · 4 across the 4 of their papers we have counts for
5 papers
MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO
Yicheng Xiao, Lin Song, Yukang Chen +7
Recent text-to-image systems face limitations in handling multimodal inputs and complex reasoning tasks. We introduce MindOmni, a unified multimodal large language model that addre…
ATP-LLaVA: Adaptive Token Pruning for Large Vision Language Models
Xubing Ye, Yukang Gan, Yixiao Ge +2
Large Vision Language Models (LVLMs) have achieved significant success across multi-modal tasks. However, the computational cost of processing long visual tokens can be prohibitive…
VoCo-LLaMA: Towards Vision Compression with Large Language Models
Xubing Ye, Yukang Gan, Xiaoke Huang +2
Vision-Language Models (VLMs) have achieved remarkable success in various multi-modal tasks, but they are often bottlenecked by the limited context window and high computational co…
HRLAIF: Improvements in Helpfulness and Harmlessness in Open-domain Reinforcement Learning From AI Feedback
Ang Li, Qiugen Xiao, Peng Cao +12
Reinforcement Learning from AI Feedback (RLAIF) has the advantages of shorter annotation cycles and lower costs over Reinforcement Learning from Human Feedback (RLHF), making it hi…
LLaMA Pro: Progressive LLaMA with Block Expansion
Chengyue Wu, Yukang Gan, Yixiao Ge +5
Humans generally acquire new skills without compromising the old; however, the opposite holds for Large Language Models (LLMs), e.g., from LLaMA to CodeLLaMA. To this end, we propo…