7 citations · 8 across the 4 of their papers we have counts for
4 papers
OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration
Xinchen Zhang, Bowei Liu, Jiale Liu +7
Visual outcomes are increasingly central to multimodal large language models, making reliable and fine-grained verification essential for scaling generalist foundation models. In t…
Visual-Advantage On-Policy Distillation for Vision-Language Models
Ruiqi Liu, Xiaolei Lv, Gengsheng Li +8
On-policy knowledge distillation has proven effective for language models, yet its application to vision-language models (VLMs) remains underexplored. We observe that standard on-p…
Dense Connector for MLLMs
Huanjin Yao, Wenhao Wu, Taojiannan Yang +7
Do we fully leverage the potential of visual encoder in Multimodal Large Language Models (MLLMs)? The recent outstanding performance of MLLMs in multimodal understanding has garner…
Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer Learning
Huanjin Yao, Wenhao Wu, Zhiheng Li
Large pre-trained vision models achieve impressive success in computer vision. However, fully fine-tuning large models for downstream tasks, particularly in video understanding, ca…