Papers by Leticia Pinto-Alva
Using Visual Feature Space as a Pivot Across Languages (2020.findings-emnlp)
Copied to clipboard
| Challenge: | We show that models trained to generate textual captions in more than one language can leverage their jointly trained feature space during inference to pivot across languages. |
| Approach: | They show that models trained to generate captions in more than one language can leverage their jointly trained feature space during inference to pivot across languages. |
| Outcome: | The proposed approach improves quality of captions in German and English by leveraging captions from a second language. |