The Mixture of Experts (MoE) is a widely known neural architecture where...
Large volumes of text data have contributed significantly to the develop...
Emergent properties have been widely adopted as a term to describe behav...
Massively multilingual models are promising for transfer learning across...
Parameter-efficient fine-tuning methods (PEFTs) offer the promise of ada...
We consider the problem of multilingual unsupervised machine translation...
This paper describes the methods behind the systems submitted by the
Uni...
Identifying factors that make certain languages harder to model than oth...
The lack of publicly available evaluation data for low-resource language...
Recent complementary strands of research have shown that leveraging
info...
In this paper, we present our approach for sentiment classification on
S...
Transfer learning, particularly approaches that combine multi-task learn...
Recent advances in the field of multilingual dependency parsing have bro...
In this paper, we introduce a trie-structured Bayesian model for unsuper...
Sparsity is one of the major problems in natural language processing. Th...