Attentive Pooling Networks

11 Feb 2016Cicero dos SantosMing TanBing XiangBowen Zhou

In this work, we propose Attentive Pooling (AP), a two-way attention mechanism for discriminative model training. In the context of pair-wise ranking or classification with neural networks, AP enables the pooling layer to be aware of the current input pair, in a way that information from the two input items can directly influence the computation of each other's representations... (read more)

PDF Abstract

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Question Answering SemEvalCQA AP-CNN [email protected] 0.755 # 2
MAP 0.771 # 5
Question Answering WikiQA AP-CNN MAP 0.6886 # 9
MRR 0.6957 # 12
Question Answering YahooCQA AP-BiLSTM [email protected] 0.568 # 3
MRR 0.731 # 4
Question Answering YahooCQA AP-CNN [email protected] 0.560 # 4
MRR 0.726 # 5