We introduce SOLAR 10.7B, a large language model (LLM) with 10.7 billion parameters,
demonstrating superior performance in various natural language processing (NLP) tasks. …

Transfer learning or multilingual model is essential for low-resource neural machine translation
(NMT), but the applicability is limited to cognate languages by sharing their vocabularies. …

Document-level context has received lots of attention for compensating neural machine
translation (NMT) of isolated sentences. However, recent advances in document-level NMT …

We present effective pre-training strategies for neural machine translation (NMT) using
parallel corpora involving a pivot language, ie, source-pivot and pivot-target, leading to a …

Bearings play a vital role in all rotating machinery, and their failure is one of the significant
causes of machine breakdown leading to a profound loss of safety and property. Therefore, …

As development of large language models (LLM) progresses, aligning them with human
preferences has become increasingly important. We propose stepwise DPO (sDPO), an …

This paper studies the practicality of the current state-of-the-art unsupervised methods in neural
machine translation (NMT). In ten translation tasks with various data settings, we analyze …

Automated essay scoring (AES) aims to score essays written for a given prompt, which defines
the writing topic. Most existing AES systems assume to grade essays of the same prompt …

Back-translation - data augmentation by translating target monolingual data - is a crucial
component in modern neural machine translation (NMT). In this work, we reformulate back-…

Individuals’ beliefs about the malleability of emotions have been theorised to play a role in
their psychological distress by influencing emotion regulation processes, such as the use of …