谷歌研究指出，单次人工翻译评估容易产生“噪音”，影响模型间的质量对比。为此，团队在MQM框架中引入二次标注环节，即由另一评估员复核已有标注。实验表明，该方法能显著提升评分一致性与可靠性，尤其在人机协作流程中可平衡质量与成本。研究同时提醒，需防范评估者过度依赖初次标注，专家监督仍不可或缺。

Sequencing efforts have provided us with detailed information about the genetic content of various organisms across all three domains of life. As genomic sciences continue to evolve we can anticipate ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Annotation involves labelling data sets to make them more valuable to human readers or machines. As a result, annotation is quickly becoming an important sub-discipline within machine learning, where ...

Data science and machine learning teams face a hidden productivity killer: annotation errors. Recent research from Apple analyzing production machine learning (ML ...

TOKYO, Dec. 25, 2025 /PRNewswire/ -- transcosmos today announced the release of highly specialized AI training and data annotation services in Chinese, Japanese, and Korean languages. The service ...

Jason Cipriani is based out of beautiful Colorado and has been covering mobile technology news and reviewing the latest gadgets for the last six years. His work can also be found on sister site CNET ...