A Bidirectional LSTM, or biLSTM, is a sequence processing model that consists of two LSTMs: one taking the input in a forward direction, and the other in a backwards direction. BiLSTMs effectively increase the amount of information available to the network, improving the context available to the algorithm (e.g. knowing what words immediately follow and precede a word in a sentence).
Image Source: Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks, Cornegruta et al
Paper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Sentence | 75 | 8.00% |
Sentiment Analysis | 39 | 4.16% |
Language Modelling | 38 | 4.06% |
Named Entity Recognition (NER) | 38 | 4.06% |
NER | 34 | 3.63% |
General Classification | 31 | 3.31% |
Text Classification | 29 | 3.09% |
Classification | 24 | 2.56% |
Question Answering | 17 | 1.81% |