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 | 73 | 7.89% |
Sentiment Analysis | 40 | 4.32% |
Named Entity Recognition (NER) | 38 | 4.11% |
Language Modelling | 37 | 4.00% |
NER | 34 | 3.68% |
General Classification | 30 | 3.24% |
Text Classification | 29 | 3.14% |
Classification | 24 | 2.59% |
Question Answering | 17 | 1.84% |