Papers with NMT of conditional computation over time
Revisiting Character-Based Neural Machine Translation with Capacity and Compression (D18-1)
Copied to clipboard
| Challenge: | Translating characters instead of words or word-fragments can simplify the processing pipeline but results in longer sequences . |
| Approach: | They propose to use sequence-to-sequence architectures of sufficient depth to solve the problem . they also evaluate the performance versus computation time tradeoffs they offer . |
| Outcome: | The proposed models outperform models operating over word fragments in character-level NMT, the authors show . they also show that the proposed models do not match the performance of their deep character baseline model . |