Moderate-sized large language models (LLMs)--those with 7B or 13B parameters--exhibit
promising machine translation (MT) performance. However, even the top-performing 13B …

The exponential growth of textual data across various domains necessitates the
development of efficient and accurate summarization techniques to facilitate quick …

Transformer architectures have revolutionized natural language processing through their
ability to handle longrange dependencies and generate contextually coherent text. Despite …

Foundational large language models (LLMs) can be instruction-tuned to perform open-
domain question answering, facilitating applications like chat assistants. While such efforts …

As large language models become integral to various applications, ensuring the reliability
and impartiality of their outputs is of paramount importance. The proposed methodologies for …

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

Natural language processing models, particularly those based on deep learning
architectures, have demonstrated remarkable capabilities in generating coherent and …

Artificial intelligence systems increasingly require robust evaluation techniques to ensure
their logical reasoning capabilities align with practical applications. This research introduces …

Large language models (LLMs) often produce text with inaccuracies, logical inconsistencies,
or fabricated information, known as structural hallucinations, which undermine their …

The ability of artificial intelligence to understand and generate human language has
transformed various applications, enhancing interactions and decision-making processes …