Multi-Agent AI Framework Aims to Improve Cultural Adaptation in AI Translation – slator.com

In a March 5, 2025 paper, researchers from Shahjalal University of Science and Technology and the University of Oklahoma proposed a multi-agent AI framework for culturally adaptive AI translation, particularly for low-resource languages. This multi-agent approach comes as the translation industry increasingly explores the limitless opportunities that agents can offer, along with the huge potential […]

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 […]

Unbabel Tackles Metric Bias in AI Translation – slator.com

In a March 11, 2025 paper, Unbabel introduced MINTADJUST, a method for more accurate and reliable machine translation (MT) evaluation.  MINTADJUST addresses metric interference (MINT), a phenomenon where using the same or related metrics for both model optimization and evaluation leads to over-optimistic performance estimates. The researchers identified two scenarios where MINT commonly occurs and […]

How to Balance Cost and Quality in AI Translation Evaluation – slator.com

As large language models (LLMs) gain prominence as state-of-the-art evaluators, prompt-based evaluation methods like GEMBA-MQM have emerged as powerful tools for assessing translation quality. However, LLM-based evaluation is expensive and computationally demanding, requiring vast amounts of tokens and incurring significant API call expenses. Scaling evaluation to large datasets quickly becomes impractical, raising a key question: […]

Language AI Briefing March 2025 – 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

Phrase Unveils Smarter AI for Global Content: Going Beyond Literal Translation – slator.com

The latest releases showcase enhanced contextual AI, next-generation machine translation capabilities, and new integrations. Boston, MA, United States–March 12, 2025—Phrase, a world leader in AI-led translation technology, today announced a significant expansion of its context-aware localization capabilities. The latest innovations include a notable update to Phrase Next GenMT, the general availability of Auto Adapt, and […]

memoQ CEO Peter Reynolds on Adaptive Generative Translation and AI – slator.com

Peter Reynolds, CEO of memoQ, joins SlatoPod to talk about the impact of AI on translation technology and how memoQ is enhancing its tools to meet the changing needs of enterprises, LSPs, and translators. Discussing AI, Peter recounts memoQ’s response to the rise of generative AI, leading to the launch of memoQ AGT (Adaptive Generative […]

Meet Tradutor, the First Open-Source AI Translation Model for European Portuguese – slator.com

Machine translation (MT) models often struggle with linguistic diversity, favoring dominant dialects and leaving many language varieties underserved. In a February 20, 2025 paper, researchers from the University of Porto, INESC TEC, Heidelberg University, University of Beira Interior, and Ci2 – Smart Cities Research Center introduced Tradutor, the first open-source AI translation model specifically tailored […]