Cross-modal Language Generation using Pivot Stabilization for Web-scale Language Coverage
Table 4: CIDEr scores on CC-1.1 validation set for bilingual and multilingual models.
['[BOLD] Lang', 'TTG', 'PLuGS-2L', 'TTG-5L', 'TTGlarge-5L', 'PLuGS-5L']
Across all languages, the TTG-5L models show a large gap in the CIDEr scores as compared to the TTG monolingual models. Using more capacity in the TTGlarge-5L model closes the gap only slightly. However, the effect of using pivot-language stabilizers tends to be consistently larger, in terms of CIDEr improvements, than the ones obtained by increasing the model capacity.