The rapid development of Large Language Models (LLMs) demonstrates remarkable
multilingual capabilities in natural language processing, attracting global attention in both …

While large language models (LLMs) like ChatGPT have shown impressive capabilities in
Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this …

Large language models (LLMs) have garnered significant interest in natural language
processing (NLP), particularly their remarkable performance in various downstream tasks in …

Data scarcity in low-resource languages can be addressed with word-to-word translations
from labeled task data in high-resource languages using bilingual lexicons. However …

In this paper, we investigate the use of decoder-based generative transformers for extracting
sentiment towards the named entities in Russian news articles. We study sentiment analysis …

Large Language Models (LLMs) are trained on massive amounts of data, enabling their
application across diverse domains and tasks. Despite their remarkable performance, most …

Cross-lingual sentiment analysis is crucial for understanding and interpreting emotions
expressed in text across diverse linguistic contexts. However, cross-lingual sentiment …

Abstract In 1959, Richard Feynman gave a famous lecture titled There is Plenty of Room at
the Bottom. This lecture is considered the birth of nanotechnology, which has become one of …

This paper evaluates the performance of Large Language Models, specifically StarCoder 2,
in non-English code summarization, with a focus on the Greek language. We establish a …

(RNN, BERT, XLM-R, and mBERT) on a distinct dataset consisting of code-mixed,
Malayalam, and Manglish (Malayalam written in Latin script). 22,449 entries make up the …