Summary of Bangla Ai: a Framework For Machine Translation Utilizing Large Language Models For Ethnic Media, by Md Ashraful Goni et al.
Bangla AI: A Framework for Machine Translation Utilizing Large Language Models for Ethnic Media
by MD Ashraful Goni, Fahad Mostafa, Kerk F. Kee
First submitted to arxiv on: 21 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research paper explores the potential integration of large language models (LLMs) and multi-lingual machine translations (MMTs) within the ethnic media industry. The study focuses on the transformative impact of using LLMs in MMT for various aspects of news translation, search, and categorization. A theoretical framework is proposed to integrate LLMs and MMT into news searching and translation processes for ethnic media. Additionally, the paper briefly touches upon potential ethical challenges associated with incorporating LLMs and MMT in news translation procedures. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research looks at how big language models can help make it easier for people to access news from their own languages when they’re living in a different country. Right now, ethnic media outlets provide news in the immigrant community’s native language, rather than the language of the host country. The study wants to see if using these language models and translation tools can improve how people find and understand news in multiple languages. It also thinks about some potential problems that might come up when using these tools. |
Keywords
* Artificial intelligence * Translation
