Enhancement of LLMs-based Translation by Agentic Machine Translation in Thai Language

Boonrerng, Artid and Elmitwally, Nouh and Vakaj, Edlira and Basurra, Shadi (2025) Enhancement of LLMs-based Translation by Agentic Machine Translation in Thai Language. In: MIWAI 2024, 11th-15th November 2024, Thailand.

[thumbnail of paper_41.pdf] Text
paper_41.pdf - Accepted Version
Restricted to Repository staff only until 20 February 2026.

Download (602kB) | Request a copy

Abstract

This experiment has a focus on the enhancement capability of large language models (LLMs) for translation in low-resource languages, specifically Thai. Moreover, the experiment of translation by selected different LLMs, such as GPT-3.5 Turbo, Claude 3.5 Sonnet, SeaLLMs, and Typhoon, translating from English to Thai in general text, found that translation by specific lan-guages pre-trained LLMs such as Typhoon has more accuracy than multilin-gual pre-trained LLMs such as GPT-3.5 Turbo. Furthermore, attempt to im-plement Agentic Machine Translate to enhance translation, which is a pro-cess that uses 2 LLMs; first assign as translator and second assign as reflec-tor. This experiment has 2 methods, first using the same LLMs as translation and reflection, and second methods using different LLMs. Additionally, the results before and after translation by reflection were assessed by BERTScore, COMET, METEOR, and BLEU. By using different LLMs, the quality of translation increases with Typhoon as translator and Claude as re-flector. As a result, the efficiency of translation by agentic flow depends on the generated reflection prompt and pre-trained language. Although this ex-periment was not to confirm that agentic machine translation can enhance LLMs-based translation accuracy, it showed there is a challenge in leveraging LLMs-based translation instead of machine translation to improve translation in low-resource languages.

Item Type: Conference or Workshop Item (Paper)
Identification Number: 10.1007/978-981-96-0692-4_9
Dates:
Date
Event
11 November 2024
Accepted
20 February 2025
Published Online
Uncontrolled Keywords: Large Language Models, Translation Quality, Agentic Machine Translation
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions: Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User: Nouh Elmitwally
Date Deposited: 11 Feb 2025 10:40
Last Modified: 03 Mar 2025 15:50
URI: https://www.open-access.bcu.ac.uk/id/eprint/16138

Actions (login required)

View Item View Item

Research

In this section...