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

To democratize large language models (LLMs) to most natural languages, it is imperative to
make these models capable of understanding and generating texts in many languages, in …

Researchers have recently argued that the capabilities of Large Language Models (LLMs)
can provide new insights into longstanding debates about the role of learning and/or …

In the universe of Natural Language Processing, Transformer-based language models like
BERT and (Chat) GPT have emerged as lexical superheroes with great power to solve open …

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

Lexical-syntactic flexibility, in the form of conversion (or zero-derivation) is a hallmark of
English morphology. In conversion, a word with one part of speech is placed in a non …

Large language models (LLMs) have demonstrated significant progress in various natural
language generation and understanding tasks. However, their linguistic generalization …

While pretrained language models (PLMs) have been shown to possess a plethora of
linguistic knowledge, the existing body of research has largely neglected extralinguistic …

We empirically study the ability of a Large Language Model (gpt-3.5-turbo-instruct) to
understand morphologically complex words. In our experiments, we looked at a variety of …

Abstract Large Language Models (LLMs) rely on subword vocabularies to process and
generate text. However, because subwords are marked as initial-or intra-word, we find that …