Rank	Method	MAP	MRR	Paper	Year-Month
1	HyperQA	0.770	0.825	Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering	2017-7
2	PWIN	0.7588	0.8219	Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement	-
3	aNMM	0.750	0.811	aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model	2018-1
4	CNN	0.711	0.785	Deep Learning for Answer Sentence Selection	2014-12

Question Answering on TrecQA

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Rank	Method	MAP	MRR	Paper title	Year
1	HyperQA	0.770	0.825	Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering	2017
2	PWIN	0.7588	0.8219	Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement
3	aNMM	0.750	0.811	aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model	2018
4	CNN	0.711	0.785	Deep Learning for Answer Sentence Selection	2014

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