602 citations · 879 across the 7 of their papers we have counts for
5 papers · 1 filter
MaXM: Towards Multilingual Visual Question Answering
Soravit Changpinyo, Linting Xue, Michal Yarom +5
Visual Question Answering (VQA) has been primarily studied through the lens of the English language. Yet, tackling VQA in other languages in the same manner would require a conside…
nmT5 -- Is parallel data still relevant for pre-training massively multilingual language models?
Mihir Kale, Aditya Siddhant, Noah Constant +3
Recently, mT5 - a massively multilingual version of T5 - leveraged a unified text-to-text format to attain state-of-the-art results on a wide variety of multilingual NLP tasks. In…
ByT5: Towards a token-free future with pre-trained byte-to-byte models
Linting Xue, Aditya Barua, Noah Constant +5
Most widely-used pre-trained language models operate on sequences of tokens corresponding to word or subword units. By comparison, token-free models that operate directly on raw te…
Towards Zero-Shot Multilingual Synthetic Question and Answer Generation for Cross-Lingual Reading Comprehension
Siamak Shakeri, Noah Constant, Mihir Sanjay Kale +1
We propose a simple method to generate multilingual question and answer pairs on a large scale through the use of a single generative model. These synthetic samples can be used to…
mT5: A massively multilingual pre-trained text-to-text transformer
Linting Xue, Noah Constant, Adam Roberts +5
The recent "Text-to-Text Transfer Transformer" (T5) leveraged a unified text-to-text format and scale to attain state-of-the-art results on a wide variety of English-language NLP t…