English-centric large language models (LLMs) often show strong multilingual capabilities.
However, the multilingual performance of these models remains unclear and is not …

We introduce a novel analysis that leverages linguistic minimal pairs to probe the internal
linguistic representations of Large Language Models (LLMs). By measuring the similarity …

Large language models (LLMs) have multilingual capabilities and can solve tasks across
various languages. However, we show that current LLMs make key decisions in a …

Despite the growing global demand for large language models (LLMs) that serve users from
diverse linguistic backgrounds, most cutting-edge LLMs remain predominantly English …

Large language models (LLMs) demonstrate exceptional performance on complex
reasoning tasks. However, despite their strong reasoning capabilities in high-resource …

Large Language Models (LLMs) exhibit remarkable multilingual generalization despite
being predominantly trained on English-centric corpora. A fundamental question arises: how …

Large language models (LLMs) have shown significant multilingual capabilities. However,
the mechanisms underlying the development of these capabilities during pre-training are not …