# Exploiting Sentence Order in Document Alignment

arXiv: https://arxiv.org/abs/2004.14523 · HTML: https://mlsanity.com/paper/2004.14523/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Apr 2020.

## Built on by (most cited first, 13 of 13)

- [Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric Into a Document-Level Metric](https://mlsanity.com/paper/2209.13654/) (2022)
- [A Shocking Amount of the Web is Machine Translated: Insights from Multi-Way Parallelism](https://mlsanity.com/paper/2401.05749/) (2024)
- [Dubbing in Practice: A Large Scale Study of Human Localization With Insights for Automatic Dubbing](https://mlsanity.com/paper/2212.12137/) (2022)
- [DEPLAIN: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplification](https://mlsanity.com/paper/2305.18939/) (2023)
- [Adapters for Altering LLM Vocabularies: What Languages Benefit the Most?](https://mlsanity.com/paper/2410.09644/) (2024)
- [Domain Adaptation of Machine Translation with Crowdworkers](https://mlsanity.com/paper/2210.15861/) (2022)
- [Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval](https://mlsanity.com/paper/2302.01626/) (2023)
- [End-to-End Single-Channel Speaker-Turn Aware Conversational Speech Translation](https://mlsanity.com/paper/2311.00697/) (2023)
- [BiMax: Bidirectional MaxSim Score for Document-Level Alignment](https://mlsanity.com/paper/2510.15577/) (2025)
- [Are the Best Multilingual Document Embeddings simply Based on Sentence Embeddings?](https://mlsanity.com/paper/2304.14796/) (2023)
- [Speaker Diarization of Scripted Audiovisual Content](https://mlsanity.com/paper/2308.02160/) (2023)
- [A Practical Evaluation Method for Long-Form Simultaneous Speech-to-Speech Translation](https://mlsanity.com/paper/2606.15059/) (2026)
- [Smart Bilingual Focused Crawling of Parallel Documents](https://mlsanity.com/paper/2405.14779/) (2024)

## Abstract (arXiv)

We present a simple document alignment method that incorporates sentence order information in both candidate generation and candidate re-scoring. Our method results in 61% relative reduction in error compared to the best previously published result on the WMT16 document alignment shared task. Our method improves downstream MT performance on web-scraped Sinhala--English documents from ParaCrawl, outperforming the document alignment method used in the most recent ParaCrawl release. It also outperforms a comparable corpora method which uses the same multilingual embeddings, demonstrating that exploiting sentence order is beneficial even if the end goal is sentence-level bitext.