Open Domain Question Answering On Searchqa

Résultats

Résultats de performance de différents modèles sur ce benchmark

		Titre de l’article
SpanBERT	84.8	SpanBERT: Improving Pre-training by Representing and Predicting Spans
Denoising QA	64.5	Denoising Distantly Supervised Open-Domain Question Answering
DecaProp	63.6	Densely Connected Attention Propagation for Reading Comprehension
DECAPROP	-	Densely Connected Attention Propagation for Reading Comprehension
Locality-Sensitive Hashing	-	Reformer: The Efficient Transformer
Sparse Attention	-	Generating Long Sequences with Sparse Transformers
Multi-passage BERT	-	Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering
Cluster-Former (#C=512)	-	Cluster-Former: Clustering-based Sparse Transformer for Long-Range Dependency Encoding
Bi-Attention + DCU-LSTM	-	Multi-Granular Sequence Encoding via Dilated Compositional Units for Reading Comprehension
Focused Hierarchical RNN	-	Focused Hierarchical RNNs for Conditional Sequence Processing
AMANDA	-	A Question-Focused Multi-Factor Attention Network for Question Answering
ASR	-	Text Understanding with the Attention Sum Reader Network
R^3	55.3	R$^3$: Reinforced Reader-Ranker for Open-Domain Question Answering
DrQA	-	Reading Wikipedia to Answer Open-Domain Questions

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