Large language models (LLMs) demonstrate remarkable multilingual capabilities without
being pre-trained on specially curated multilingual parallel corpora. It remains a challenging …

We assess how multilingual language models maintain a shared multilingual representation
space while still encoding language-sensitive information in each language. Using XLM-R …

The rapid global expansion of ChatGPT, which plays a crucial role in interactive knowledge
sharing and translation, underscores the importance of comparative performance …

We present SeaEval, a benchmark for multilingual foundation models. In addition to
characterizing how these models understand and reason with natural language, we also …

In task-oriented dialogue (ToD), a user holds a conversation with an artificial agent with the
aim of completing a concrete task. Although this technology represents one of the central …

Cross-lingual alignment, the meaningful similarity of representations across languages in
multilingual language models, has been an active field of research in recent years. We …

Bilingual Lexicon Induction (BLI) aims to map words in one language to their translations in
another, and is typically through learning linear projections to align monolingual word …

Many recent studies of Entity Alignment (EA) use Graph Neural Networks (GNNs) to
aggregate the neighborhood features of entities and achieve better performance. However …

Sentiment analysis has become popular when Natural Language Processing algorithms
were proven to be able to process complex sentences with good accuracy. Recently, pre …

We explore the impact of leveraging the relatedness of languages that belong to the same
family in NLP models using multilingual fine-tuning. We hypothesize and validate that …