Papers by Chitwan Saharia
Non-Autoregressive Machine Translation with Latent Alignments (2020.emnlp-main)
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| Challenge: | Existing non-autoregressive machine translation methods are lacking in the field of latent alignments. |
| Approach: | They propose two strong methods for non-autoregressive machine translation that model latent alignments with dynamic programming. |
| Outcome: | The proposed models achieve state-of-the-art on the WMT’14 EnDe task, compared with the autoregressive Transformer baseline. |
Character-Aware Models Improve Visual Text Rendering (2023.acl-long)
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Rosanne Liu, Dan Garrette, Chitwan Saharia, William Chan, Adam Roberts, Sharan Narang, Irina Blok, Rj Mical, Mohammad Norouzi, Noah Constant
| Challenge: | Current image generation models struggle to produce well-formed visual text due to lack of character-level input features. |
| Approach: | They conduct a series of experiments to compare character-aware vs. character-blind text encoders to determine their spelling ability. |
| Outcome: | The character-aware models outperform character-blind models on a range of novel text rendering tasks. |