Who Watches the Watchmen? Humans Disagree With Translation Metrics on Unseen Domains
Automatic evaluation metrics are central to the development of machine translation systems, yet their robustness under domain shift remains unclear. Most metrics are developed on the Workshop on Machine Translation (WMT) benchmarks, raising concerns about their robustness to unseen domains. Prior studies that analyze unseen domains vary translation systems, annotators, or evaluation conditions, confounding domain effects with human annotation noise. To address these biases, we introduce a systematic multi-annotator Cross-Domain Error-Span-Annotation dataset (CD-ESA), comprising 18.8k human error span annotations across three language pairs, where we fix annotators within each language pai...
| Authors | Finn Schmidt, Jan Philip Wahle, Terry Ruas et al. |
|---|---|
| Primary category | cs.CL |
| Published | 19 April 2026 |
| Last updated at source | 21 April 2026 |
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