373 citations · 404 across the 6 of their papers we have counts for
6 papers
MENLO: From Preferences to Proficiency -- Evaluating and Modeling Native-like Quality Across 47 Languages
Chenxi Whitehouse, Sebastian Ruder, Tony Lin +6
Ensuring native-like quality of large language model (LLM) responses across many languages is challenging. To address this, we introduce MENLO, a framework that operationalizes the…
FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data
Haoran Sun, Renren Jin, Shaoyang Xu +10
Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
Seamless Communication, Loïc Barrault, Yu-An Chung +65
What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages? While recent breakthroughs in text-based models have pushed…
HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine Translation
David Dale, Elena Voita, Janice Lam +6
Hallucinations in machine translation are translations that contain information completely unrelated to the input. Omissions are translations that do not include some of the input…
No Language Left Behind: Scaling Human-Centered Machine Translation
NLLB Team, Marta R. Costa-jussà, James Cross +36
Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today. However,…
Consistent Human Evaluation of Machine Translation across Language Pairs
Daniel Licht, Cynthia Gao, Janice Lam +3
Obtaining meaningful quality scores for machine translation systems through human evaluation remains a challenge given the high variability between human evaluators, partly due to…