Densely Connected Attention Propagation for Reading Comprehension

NeurIPS 2018 Yi TayLuu Anh TuanSiu Cheung HuiJian Su

We propose DecaProp (Densely Connected Attention Propagation), a new densely connected neural architecture for reading comprehension (RC). There are two distinct characteristics of our model... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Question Answering NarrativeQA DecaProp BLEU-1 44.35 # 1
Question Answering NarrativeQA DecaProp BLEU-4 27.61 # 1
Question Answering NarrativeQA DecaProp METEOR 21.80 # 1
Question Answering NarrativeQA DecaProp Rouge-L 44.69 # 2
Question Answering NewsQA DecaProp F1 66.3 # 1
Question Answering NewsQA DecaProp EM 53.1 # 1
Open-Domain Question Answering Quasar DecaProp EM (Quasar-T) 38.6 # 2
Open-Domain Question Answering Quasar DecaProp F1 (Quasar-T) 46.9 # 2
Open-Domain Question Answering SearchQA DecaProp Unigram Acc 62.2 # 1
Open-Domain Question Answering SearchQA DecaProp N-gram F1 70.8 # 1
Open-Domain Question Answering SearchQA DecaProp EM 56.8 # 2
Open-Domain Question Answering SearchQA DecaProp F1 63.6 # 2