---
title: "Machine Translation"
description: "1 posts about Machine Translation, summarised, each linking to the original."
---

# Machine Translation
> 1 posts about Machine Translation, summarised, each linking to the original.

## Articles

### [Large Language Models for Machine Translation Quality Annotation: Humans and Models Are Both Challenged](https://yomu.fyi/post/large-language-models-for-machine-translation-quality-annotation-human.md)
- Company: [Apple](https://yomu.fyi/company/apple.md)
- Published: Oct 12, 2026
- Type: Benchmark

The paper evaluates LLMs as alternatives to human judgment for machine translation quality annotation, comparing agreement with human annotators on two schemes: Multidimensional Quality Metrics (MQM) and Error Span Annotation (ESA). Tests cover a long-context set of 70 language pairs plus WMT23 and WMT25 data, examining both score and error span annotation agreement across language pairs and domains. Results show LLM-human agreement sometimes exceeds human-human agreement, but both vary substantially across annotation schemes, language pairs, and domains and remain unreliable for most settings. Humans are particularly challenged by fine-grained MQM annotations and low-resource language pairs, while LLMs struggle with minor errors, wrong language variants, and error span annotation. The authors suggest human-LLM collaborative annotation pipelines as a way to address the reliability issues identified in this work.