Papers by Andreas Guta
The Green KNIGHT: Green Machine Translation with Knowledge-Distilled, Narrow, Inexpensive, Greedy, Hybrid Transformers (2025.findings-emnlp)
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| Challenge: | State-of-the-art neural machine translation models deliver high-quality translations at the expense of high inference latency and energy consumption. |
| Approach: | They propose a hardware-agnostic collection of recipes to optimize translation speed and energy consumption. |
| Outcome: | The Green KNIGHT optimizes translation speed and energy consumption with a moderate trade-off in quality. |