AI Translation Improves for Indic Languages. Preserving Sentiment Still a Challenge – slator.com
In an April 2, 2025 paper researchers from the Transitional Artificial Intelligence Research Group at UNSW Sydney and the Centre for Artificial Intelligence and Innovation at Pingla Institute, Sydney, evaluated how large language models (LLMs) fare with complex, culturally and emotionally rich Indian texts. The study compared the performance of OpenAI’s GPT-3.5 and GPT-4o, Google’s […]
Generative AI Takes Localization from Cost Center to Growth Driver – slator.com
Generative AI, a.k.a. GenAI, has made the leap from digital experimentation “sandboxes” to daily use and C-suite plans for the year ahead. But beyond the point of pride that comes with displaying “AI” prominently on a website, the question remains: How can AI — and more specifically, large language models (LLMs) and GenAI — translate […]
Translationese Remains a Challenge for Large Language Models, Study Finds – slator.com
In a March 6, 2025 paper, researchers from China-based institutions the Shanghai AI Laboratory, Westlake University (Hangzhou), and Northeastern University (Shenyang) demonstrated that large language models (LLMs) still suffer from “translationese” — overly literal and unnatural translations that deviate from native linguistic norms. They explained that while previous research has explored translationese in traditional machine […]
Alibaba Says Large Reasoning Models Are Redefining AI Translation – slator.com
In a March 14, 2025 paper, researchers from Alibaba‘s MarcoPolo Team explored the translation capabilities of large reasoning models (LRMs) like OpenAI’s o1 and o3, DeepSeeks’s R1, Anthropic’s Claude 3.7 Sonnet, or xAI’s Grok 3, positioning them as “the next evolution” in translation beyond neural machine translation (NMT) and large language models (LLMs). They explained […]
New Research Explores How to Boost Large Language Models’ Multilingual Performance – slator.com
In a February 20, 2025 paper, researchers Danni Liu and Jan Niehues from the Karlsruhe Institute of Technology proposed a way to improve how large language models (LLMs) perform across different languages. They explained that LLMs like Llama 3 and Qwen 2.5, show strong performance in tasks like machine translation (MT) but often struggle with […]
Which Parts of a Prompt Should Be Translated to Improve Large Language Models? – slator.com
On February 13, 2025, researchers Itai Mondshine, Tzuf Paz-Argaman, and Reut Tsarfaty from Bar-Ilan University suggested that translating only specific components of a prompt can improve the performance of multilingual large language models (LLMs) across various natural language processing (NLP) tasks. This research builds on prior work by Google, Alibaba, the Pune Institute of Computer […]
Appen Sees ‘Significant Experimentation’ in Large Language Model Market – slator.com
Slator is the leading source of research and market intelligence for translation, localization, interpreting, and language AI. Slator’s Advisory practice is a trusted partner to clients looking for M&A services and independent analysis. Slator has offices in Zurich (HQ) and London, and Analysts based in Asia, Europe, and the US. Source link
Xiaomi’s Training Recipe for Better Multilingual AI Translation – slator.com
In a February 7, 2025 paper, researchers from Chinese tech company Xiaomi benchmarked the capabilities of open-source large language models (LLMs) with under ten billion parameters for multilingual machine translation (MT) tasks. They proposed the “best data recipe” to enhance AI translation performance. The researchers explained that open-source LLMs have shown improvements in multilingual capabilities, […]
Research Pits Traditional Machine Translation Against LLM-Powered AI Translation – slator.com
As large language models (LLMs) continue to transform translation workflows, a new study underscores the ongoing importance of conventional, domain-specific machine translation (MT) models. While recognizing the impact of LLMs on translation processes, the researchers emphasize the need for careful evaluation of workflows to ensure optimal outcomes. Previous research has shown that MT systems often […]
The Most Popular Language Industry Stories of 2024 – slator.com
As 2024 comes to a close, it is time to reflect on the most popular stories, trends, innovations, and themes that made the Slator headlines throughout the year, highlighting key developments in the language industry. Here is a selection of stories that attracted the most attention and engagement from our readers around the world. Will […]