xcomet: Transparent machine translation evaluation through fine-grained error detection
Widely used learned metrics for machine translation evaluation, such as COMET and
BLEURT, estimate the quality of a translation hypothesis by providing a single sentence …
BLEURT, estimate the quality of a translation hypothesis by providing a single sentence …
Towards explainable evaluation metrics for machine translation
Unlike classical lexical overlap metrics such as BLEU, most current evaluation metrics for
machine translation (for example, COMET or BERTScore) are based on black-box large …
machine translation (for example, COMET or BERTScore) are based on black-box large …
Machine translation meta evaluation through translation accuracy challenge sets
Recent machine translation (MT) metrics calibrate their effectiveness by correlating with
human judgement. However, these results are often obtained by averaging predictions …
human judgement. However, these results are often obtained by averaging predictions …
Aligning translation-specific understanding to general understanding in large language models
Although large language models (LLMs) have shown surprising language understanding
and generation capabilities, they have yet to gain a revolutionary advancement in the field of …
and generation capabilities, they have yet to gain a revolutionary advancement in the field of …
xcomet: Transparent Machine Translation Evaluation through Fine-grained Error Detection
Widely used learned metrics for machine translation evaluation, such as Comet and Bleurt,
estimate the quality of a translation hypothesis by providing a single sentence-level score …
estimate the quality of a translation hypothesis by providing a single sentence-level score …
[PDF][PDF] xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection
Widely used learned metrics for machine translation evaluation, such as COMET and
BLEURT, estimate the quality of a translation hypothesis by providing a single sentence …
BLEURT, estimate the quality of a translation hypothesis by providing a single sentence …
xTower: A Multilingual LLM for Explaining and Correcting Translation Errors
While machine translation (MT) systems are achieving increasingly strong performance on
benchmarks, they often produce translations with errors and anomalies. Understanding …
benchmarks, they often produce translations with errors and anomalies. Understanding …
Cyber Risks of Machine Translation Critical Errors: Arabic Mental Health Tweets as a Case Study
With the advent of Neural Machine Translation (NMT) systems, the MT output has reached
unprecedented accuracy levels which resulted in the ubiquity of MT tools on almost all …
unprecedented accuracy levels which resulted in the ubiquity of MT tools on almost all …
Chasing COMET: Leveraging Minimum Bayes Risk Decoding for Self-Improving Machine Translation
K Guttmann, M Pokrywka, A Charkiewicz… - arXiv preprint arXiv …, 2024 - arxiv.org
This paper explores Minimum Bayes Risk (MBR) decoding for self-improvement in machine
translation (MT), particularly for domain adaptation and low-resource languages. We …
translation (MT), particularly for domain adaptation and low-resource languages. We …
Original Research Article A comparative analysis of lexical-based automatic evaluation metrics for different Indic language pairs
K Kaur, S Chauhan - Journal of Autonomous Intelligence, 2024 - jai.front-sci.com
With the rise of machine translation systems, it has become essential to evaluate the quality
of translations produced by these systems. However, the existing evaluation metrics …
of translations produced by these systems. However, the existing evaluation metrics …