18th Workshop on Building and Using Comparable Corpora

In the language engineering and linguistics communities, research in comparable corpora has been motivated by two main reasons. In language engineering, on the one hand, it is chiefly motivated by the need to use comparable corpora as training data for statistical NLP applications such as statistical and neural machine translation or cross-lingual retrieval. In linguistics, on the other hand, comparable corpora are of interest because they enable cross-language discoveries and comparisons. It is generally accepted in both communities that comparable corpora consist of documents that are comparable in content and form in various degrees and dimensions across several languages. Parallel corpora are on the one end of this spectrum, and unrelated corpora are on the other.

In recent years, the use of comparable corpora for pre-training Large Language Models (LLMs) has led to their impressive multilingual and cross-lingual abilities, which are relevant to a range of applications, including Information Retrieval, Machine Translation, Cross-lingual text classification, etc. The linguistic definitions and observations related to comparable corpora can improve methods to mine such corpora for applications of statistical NLP, for example, to extract parallel corpora from comparable corpora for neural MT or to improve cross-lingual transfer of LLMs. As such, it is of great interest to bring together builders and users of such corpora.