Summary of Ebbs: An Ensemble with Bi-level Beam Search For Zero-shot Machine Translation, by Yuqiao Wen et al.
EBBS: An Ensemble with Bi-Level Beam Search for Zero-Shot Machine Translation
by Yuqiao Wen, Behzad Shayegh, Chenyang Huang, Yanshuai Cao, Lili Mou
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed EBBS (ensemble method with bi-level beam search algorithm) outperforms direct and pivot translations on two popular multilingual translation datasets. The algorithm uses a novel “soft voting” mechanism to synchronize ensemble components, each exploring its own prediction step by step at the lower level. This medium-difficulty summary highlights the paper’s contributions in multilingual translation, including ensemble methods and knowledge distillation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper explores zero-shot translation in unseen directions, where a multilingual model can translate directly without being trained on those specific directions. The authors find that both direct and pivot translations are noisy and less accurate than expected. They propose a new ensemble method called EBBS, which uses a bi-level beam search algorithm to improve translation quality. Results show that EBBS outperforms existing methods and even improves inference efficiency when distilling knowledge back to the multilingual model. |
Keywords
* Artificial intelligence * Inference * Knowledge distillation * Translation * Zero shot
