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Question Answering On Cnn Daily Mail

Metriken

CNN

Daily Mail

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	CNN	Daily Mail	Paper Title	Repository
Impatient Reader	63.8	68.0	Teaching Machines to Read and Comprehend	-
Classifier	67.9	68.3	A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task	-
GA Reader	77.9	80.9	Gated-Attention Readers for Text Comprehension	-
AoA Reader	74.4	-	Attention-over-Attention Neural Networks for Reading Comprehension	-
Attentive + relabling + ensemble	77.6	79.2	A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task	-
AIA	76.1	-	Iterative Alternating Neural Attention for Machine Reading	-
AS Reader (ensemble model)	75.4	77.7	Text Understanding with the Attention Sum Reader Network	-
AS Reader (single model)	69.5	73.9	Text Understanding with the Attention Sum Reader Network	-
EpiReader	74	-	Natural Language Comprehension with the EpiReader	-
GA+MAGE (32)	78.6	-	Linguistic Knowledge as Memory for Recurrent Neural Networks	-
Attentive Reader	63	69	Teaching Machines to Read and Comprehend	-
AttentiveReader + bilinear attention	72.4	75.8	A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task	-
MemNNs (ensemble)	69.4	-	Teaching Machines to Read and Comprehend	-
ReasoNet	74.7	76.6	ReasoNet: Learning to Stop Reading in Machine Comprehension	-
BiDAF	76.9	79.6	Bidirectional Attention Flow for Machine Comprehension	-
Dynamic Entity Repres. + w2v	72.9	-	-	-

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Question Answering On Cnn Daily Mail | SOTA | HyperAI