Large language models (LLMs) have emerged as powerful tools capable of accomplishing a
broad spectrum of tasks. Their abilities span numerous areas, and one area where they …

Recent breakthroughs in large language models (LLMs) have centered around a handful of
data-rich languages. What does it take to broaden access to breakthroughs beyond first …

Large Language Models (LLMs) have become effective tools for natural language
processing and have been used in many different fields. This essay offers a succinct …

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

Despite the progress we have recorded in the last few years in multilingual natural language
processing, evaluation is typically limited to a small set of languages with available datasets …

In recent years, with the advancement of natural language processing techniques and the
release of models like ChatGPT, how language models understand questions has become a …

In this paper we discuss how AI can contribute to support the documentation and vitalization
of Indigenous languages and how that involves a delicate balancing of ensuring social …

To enable the pre-trained models to be fine-tuned with local data on edge devices without
sharing data with the cloud, we design an efficient split fine-tuning (SFT) framework for edge …

Cross-lingual information retrieval (CLIR) continues to be an actively studied topic in
information retrieval (IR), and there have been consistent efforts in curating test collections to …

Pre-trained models (PTMs) have achieved great success in various Software Engineering
(SE) downstream tasks following the``pre-train then fine-tune''paradigm. As fully fine-tuning …