9 papers
PolyFact: Comparing Consistency-Driven Post-training Methods for Cross-Lingual Factual Recall
Jonathan von Rad, Louis Arts, George Burgess +6
Large language models (LLMs) trained predominantly on English data encode substantial world knowledge, yet often fail to express it reliably in other languages, a phenomenon known…
Omnilingual MT: Machine Translation for 1,600 Languages
Omnilingual MT Team, Belen Alastruey, Niyati Bafna +29
High-quality machine translation (MT) can scale to hundreds of languages, setting a high bar for multilingual systems. However, compared to the world's 7,000 languages, current sys…
Translate, then Detect: Leveraging Machine Translation for Cross-Lingual Toxicity Classification
Samuel J. Bell, Eduardo Sánchez, David Dale +3
Multilingual toxicity detection remains a significant challenge due to the scarcity of training data and resources for many languages. While prior work has leveraged the translate-…
LCFO: Long Context and Long Form Output Dataset and Benchmarking
Marta R. Costa-jussÃ, Pierre Andrews, Mariano Coria Meglioli +10
This paper presents the Long Context and Form Output (LCFO) benchmark, a novel evaluation framework for assessing gradual summarization and summary expansion capabilities across di…
BOUQuET: dataset, Benchmark and Open initiative for Universal Quality Evaluation in Translation
The Omnilingual MT Team, Pierre Andrews, Mikel Artetxe +14
BOUQuET is a multi-way, multicentric and multi-register/domain dataset and benchmark, and a broader collaborative initiative. This dataset is handcrafted in 8 non-English languages…
On the Role of Speech Data in Reducing Toxicity Detection Bias
Samuel J. Bell, Mariano Coria Meglioli, Megan Richards +6
Text toxicity detection systems exhibit significant biases, producing disproportionate rates of false positives on samples mentioning demographic groups. But what about toxicity de…