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Open Domain Question Answering On Searchqa

Metrics

F1

Results

Performance results of various models on this benchmark

Model Name
F1
Paper TitleRepository
SpanBERT84.8SpanBERT: Improving Pre-training by Representing and Predicting Spans-
Denoising QA64.5Denoising Distantly Supervised Open-Domain Question Answering
DecaProp63.6Densely 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^355.3R$^3$: Reinforced Reader-Ranker for Open-Domain Question Answering-
DrQA-Reading Wikipedia to Answer Open-Domain Questions-
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Open Domain Question Answering On Searchqa | SOTA | HyperAI