Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within
the field of NLP, aimed at addressing limitations in existing frameworks while aligning with …

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 …

There has recently been a growing interest in using Large Language Models (LLMs) to
evaluate NLP tasks automatically. Considerable research effort has been put into improving …

While quality estimation (QE) can play an important role in the translation process, its
effectiveness relies on the availability and quality of training data. For QE in particular, high …

Fine-tuning and testing a multilingual large language model is expensive and challenging
for low-resource languages (LRLs). While previous studies have predicted the performance …

We introduce a new, extensive multidimensional quality metrics (MQM) annotated dataset
covering 11 language pairs in the biomedical domain. We use this dataset to investigate …