Aug. 24, 2022, 1:14 a.m. | Estelle Aflalo, Meng Du, Shao-Yen Tseng, Yongfei Liu, Chenfei Wu, Nan Duan, Vasudev Lal

cs.CL updates on arXiv.org arxiv.org

Breakthroughs in transformer-based models have revolutionized not only the
NLP field, but also vision and multimodal systems. However, although
visualization and interpretability tools have become available for NLP models,
internal mechanisms of vision and multimodal transformers remain largely
opaque. With the success of these transformers, it is increasingly critical to
understand their inner workings, as unraveling these black-boxes will lead to
more capable and trustworthy models. To contribute to this quest, we propose
VL-InterpreT, which provides novel interactive visualizations for …

arxiv cv interactive language tool transformers vision visualization

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