Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …

Transformers have revolutionized almost all natural language processing (NLP) tasks but
suffer from memory and computational complexity that scales quadratically with sequence …

Large language models are commonly trained on a mixture of filtered web data and
curated``high-quality''corpora, such as social media conversations, books, or technical …

Language models (LMs) have become ubiquitous in both NLP research and in commercial
product offerings. As their commercial importance has surged, the most powerful models …

The development of open-source, multilingual medical language models can benefit a wide,
linguistically diverse audience from different regions. To promote this domain, we present …

This research paper focuses on the challenges posed by hallucinations in large language
models (LLMs), particularly in the context of the medical domain. Hallucination, wherein …

This survey article proposes a clearer view of Natural Language Reasoning (NLR) in the
field of Natural Language Processing (NLP), both conceptually and practically …

Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …

Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …