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Probing Cross-modal Semantics Alignment Capability from the Textual Perspective. (arXiv:2210.09550v1 [cs.CL])
Oct. 19, 2022, 1:17 a.m. | Zheng Ma, Shi Zong, Mianzhi Pan, Jianbing Zhang, Shujian Huang, Xinyu Dai, Jiajun Chen
cs.CL updates on arXiv.org arxiv.org
In recent years, vision and language pre-training (VLP) models have advanced
the state-of-the-art results in a variety of cross-modal downstream tasks.
Aligning cross-modal semantics is claimed to be one of the essential
capabilities of VLP models. However, it still remains unclear about the inner
working mechanism of alignment in VLP models. In this paper, we propose a new
probing method that is based on image captioning to first empirically study the
cross-modal semantics alignment of VLP models. Our probing method …
More from arxiv.org / cs.CL updates on arXiv.org
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