Categories: FAANG

Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs

Translating text that contains entity names is a challenging task, as cultural-related references can vary significantly across languages. These variations may also be caused by transcreation, an adaptation process that entails more than transliteration and word-for-word translation. In this paper, we address the problem of cross-cultural translation on two fronts: (i) we introduce XC-Translate, the first large-scale, manually-created benchmark for machine translation that focuses on text that contains potentially culturally-nuanced entity names, and (ii) we propose KG-MT, a novel end-to-end…
AI Generated Robotic Content

Recent Posts

SamsungCam UltraReal – Qwen-Image LoRA

Hey everyone, Just dropped the first version of a LoRA I've been working on: SamsungCam…

1 hour ago

40 Best Early Amazon Prime Day Deals on WIRED-Tested Gear (2025)

Amazon Prime Day is back, starting on October 7, but we’ve already found good deals…

2 hours ago

These little robots literally walk on water

HydroSpread, a breakthrough fabrication method, lets scientists build ultrathin soft robots directly on water. These…

2 hours ago

VHS filters work great with AI footage (WAN 2.2 + NTSC-RS)

submitted by /u/mtrx3 [link] [comments]

1 day ago

Algorithm Showdown: Logistic Regression vs. Random Forest vs. XGBoost on Imbalanced Data

Imbalanced datasets are a common challenge in machine learning.

1 day ago

Unlock global AI inference scalability using new global cross-Region inference on Amazon Bedrock with Anthropic’s Claude Sonnet 4.5

Organizations are increasingly integrating generative AI capabilities into their applications to enhance customer experiences, streamline…

1 day ago