2 papers
cs.CV2025
Enhancing Scientific Visual Question Answering via Vision-Caption aware Supervised Fine-Tuning
Janak Kapuriya, Anwar Shaikh, Arnav Goel +8
In this study, we introduce Vision-Caption aware Supervised FineTuning (VCASFT), a novel learning paradigm designed to enhance the performance of smaller Vision Language Models(VLM…
cs.CV2025
Empowering Large Language Model for Continual Video Question Answering with Collaborative Prompting
Chen Cai, Zheng Wang, Jianjun Gao +4
In recent years, the rapid increase in online video content has underscored the limitations of static Video Question Answering (VideoQA) models trained on fixed datasets, as they s…