# Quality Estimation Using Round-trip Translation with Sentence Embeddings

arXiv: https://arxiv.org/abs/2111.00554 · HTML: https://mlsanity.com/paper/2111.00554/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 18 references that are in the map.
- First posted on arXiv 31 Oct 2021.

## Builds on (most cited first, 7 of 7)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Universal Sentence Encoder](https://mlsanity.com/paper/1803.11175/) (2018)
- [The FLoRes Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English](https://mlsanity.com/paper/1902.01382/) (2019)
- [Revisiting Round-Trip Translation for Quality Estimation](https://mlsanity.com/paper/2004.13937/) (2020)
- [TransQuest at WMT2020: Sentence-Level Direct Assessment](https://mlsanity.com/paper/2010.05318/) (2020)

## Built on by (most cited first, 2 of 2)

- [Rethinking Round-Trip Translation for Machine Translation Evaluation](https://mlsanity.com/paper/2209.07351/) (2022)
- [Lost In Translation: Generating Adversarial Examples Robust to Round-Trip Translation](https://mlsanity.com/paper/2307.12520/) (2023)

## Abstract (arXiv)

Estimating the quality of machine translation systems has been an ongoing challenge for researchers in this field. Many previous attempts at using round-trip translation as a measure of quality have failed, and there is much disagreement as to whether it can be a viable method of quality estimation. In this paper, we revisit round-trip translation, proposing a system which aims to solve the previous pitfalls found with the approach. Our method makes use of recent advances in language representation learning to more accurately gauge the similarity between the original and round-trip translated sentences. Experiments show that while our approach does not reach the performance of current state of the art methods, it may still be an effective approach for some language pairs.