Modern large language models (LLMs) like ChatGPT have shown remarkable performance
on general language tasks but still struggle on complex reasoning tasks, which drives the …

Large language models (LLMs) that have been trained on multilingual but not parallel text
exhibit a remarkable ability to translate between languages. We probe this ability in an in …

Large language models (LLMs) have demonstrated impressive capabilities in general
scenarios, exhibiting a level of aptitude that approaches, in some aspects even surpasses …

AI tasks encompass a wide range of domains and fields. While numerous AI models have
been designed for specific tasks and applications, they often require considerable human …

Multilingual Large Language Models are capable of using powerful Large Language
Models to handle and respond to queries in multiple languages, which achieves remarkable …

Multilingual large language models (MLLMs) leverage advanced large language models to
process and respond to queries across multiple languages, achieving significant success in …

Resolving ambiguities through interaction is a hallmark of natural language, and modeling
this behavior is a core challenge in crafting AI assistants. In this work, we study such …

Benchmarking efforts for machine learning have often mimicked (or even explicitly used)
professional licensing exams to assess capabilities in a given area, focusing primarily on …

Effective communication is fundamental to any interaction, yet challenges arise when
participants do not share a common language. Automatic translation systems offer a …

In this paper, we compare two approaches to train a multilingual language model:(i) simple
multilingual learning using data-mixing, and (ii) meta-learning. We examine the performance …