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Label-Dependencies Aware Recurrent Neural Networks
[article]
2017
arXiv
pre-print
In the last few years, Recurrent Neural Networks (RNNs) have proved effective on several NLP tasks. Despite such great success, their ability to model sequence labeling is still limited. This lead research toward solutions where RNNs are combined with models which already proved effective in this domain, such as CRFs. In this work we propose a solution far simpler but very effective: an evolution of the simple Jordan RNN, where labels are re-injected as input into the network, and converted
arXiv:1706.01740v1
fatcat:nm7rb5wsevfddaecpenp6goeh4