2 citations · 3 across the 12 of their papers we have counts for
6 papers · 1 filter
There is No Theoretical Curse of Multilinguality For Embedding Space Structure
Niyati Bafna, Neha Verma, Vilém Zouhar +2
A central goal of multilingual NLP is to achieve high monolingual performance per language and cross-lingual alignment for large-scale language coverage with a multilingual model.…
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustness
Pinzhen Chen, Koel Dutta Chowdhury, Xiaoya Xu +20
Multilingual translation benchmarks are typically sourced in English and translated into other languages, treating language pairs as the unit of evaluation---a design that is prone…
Multilingual Reasoning Cascades Need More Context
Arnav Mazumder, Dengjia Zhang, Shuyue Stella Li +2
Translation cascades for reasoning translate the query from another language to English, reason in English, and translate the answer back to the original language. This is a compet…
Rashid: A Cipher-Based Framework for Exploring In-Context Language Learning
Niyati Bafna, Ryan Soh-Eun Shim, Barbara Plank +2
Where there is growing interest in in-context language learning (ICLL) for unseen languages with large language models, such languages usually suffer from the lack of NLP tools, da…
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…