Vision-language navigation requires agents to follow natural-language instructions to reach target locations, making high-quality language supervision essential. Since human annotation is costly, prior work has explored scalable data synthesis methods. However, existing methods typically either use separate models for...
Song-Ze Li, Hao-Ming Gu, Zi-Yang Gong et al.· 0 citations
Efficient multimodal instruction tuning requires reducing both training data volume and computational cost without substantially sacrificing downstream performance. Existing data selection methods can remove redundancy but cannot repair imperfect supervision or supplement under-represented capabilities. We propose SANe...
Han Lin, Yi Wang, Yi-Nan He et al.· Electronics· 0 citations
This work compares the student view and training fixed within each scale against three abstractions compiled offline, a named strategy, a method-independent framing, and a problem category, and against an answer-only control that keeps the destination but removes the path.
Kang-Hui Tian, Si-Yuan Liu, Tianxiang Jiang et al.· 2 citations
This work introduces VideoChat3, a fully open, efficient, and generalist video-centric MLLM, which surpasses prior open-source models with equal or larger parameter counts with only 4B parameters and higher efficiency.
