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Question Answering On Cnn Daily Mail

Metrics

CNN
Daily Mail

Results

Performance results of various models on this benchmark

Paper Title
GA+MAGE (32)78.6-Linguistic Knowledge as Memory for Recurrent Neural Networks
GA Reader77.980.9Gated-Attention Readers for Text Comprehension
Attentive + relabling + ensemble77.679.2A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
BiDAF76.979.6Bidirectional Attention Flow for Machine Comprehension
AIA76.1-Iterative Alternating Neural Attention for Machine Reading
AS Reader (ensemble model)75.477.7Text Understanding with the Attention Sum Reader Network
ReasoNet74.776.6ReasoNet: Learning to Stop Reading in Machine Comprehension
AoA Reader74.4-Attention-over-Attention Neural Networks for Reading Comprehension
EpiReader74-Natural Language Comprehension with the EpiReader
Dynamic Entity Repres. + w2v 72.9--
AttentiveReader + bilinear attention72.475.8A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
AS Reader (single model) 69.573.9Text Understanding with the Attention Sum Reader Network
MemNNs (ensemble)69.4-Teaching Machines to Read and Comprehend
Classifier67.968.3A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
Impatient Reader63.868.0Teaching Machines to Read and Comprehend
Attentive Reader6369Teaching Machines to Read and Comprehend
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Question Answering On Cnn Daily Mail | SOTA | HyperAI