Cultural biases in multilingual datasets pose significant challenges for their effectiveness as
global benchmarks. These biases stem not only from language but also from the cultural …

This paper presents the contributions of Charles University teams to the WMT24 General
Translation task (English to Czech, German and Russian, and Czech to Ukrainian), and the …

The NTTSU team's submission leverages several large language models developed
through a training procedure that includes continual pre-training and supervised fine-tuning …

Generic sentences express generalisations about the world without explicit quantification.
Although generics are central to everyday communication, building a precise semantic …

This year's MT metrics challenge set submission by DFKI expands on previous years'
linguistically motivated challenge sets. It includes 137,000 items extracted from 100 MT …

This paper illustrates the submission system of the IOL Research team for the WMT24
General Machine Translation shared task. We submitted translations for all translation …

Generic sentences express generalisations about the world without explicit quantification.
Although generics are central to everyday communication, building a precise semantic …

The emergent phenomena of large foundation models have revolutionized natural language
processing. However, evaluating these models presents significant challenges due to their …

Visual information has been introduced for enhancing machine translation (MT), and its
effectiveness heavily relies on the availability of large amounts of bilingual parallel sentence …

Reranking a list of candidates from a machine translation system with an external scoring
model and returning the highest-scoring candidate remains a simple and effective method …