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Answer Selection

Answer Selection is the task of identifying the correct answer to a question from a pool of candidate answers. This task can be formulated as a classification or a ranking problem.

Source: Learning Analogy-Preserving Sentence Embeddings for Answer Selection

Papers

Showing 126–150 of 171 papers

TitleStatusHype
Representation Learning for Answer Selection with LSTM-Based Importance WeightingCode0
FastHybrid: A Hybrid Model for Efficient Answer Selection—0
A Compare-Aggregate Model for Matching Text SequencesCode0
Learning Recurrent Span Representations for Extractive Question AnsweringCode0
Learning to Answer Questions from Wikipedia Infoboxes—0
Hierarchical Memory Networks for Answer Selection on Unknown WordsCode0
Skipping Word: A Character-Sequential Representation based Framework for Question Answering—0
A Sentence Interaction Network for Modeling Dependence between Sentences—0
Inner Attention based Recurrent Neural Networks for Answer Selection—0
Learning Semantic Relatedness in Community Question Answering Using Neural Models—0
Improved Representation Learning for Question Answer Matching—0
Gated-Attention Readers for Text ComprehensionCode0
ITNLP-AiKF at SemEval-2016 Task 3 a quesiton answering system using community QA repository—0
Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement—0
SLS at SemEval-2016 Task 3: Neural-based Approaches for Ranking in Community Question Answering—0
Why and How to Pay Different Attention to Phrase Alignments of Different Intensities—0
M^2S-Net: Multi-Modal Similarity Metric Learning based Deep Convolutional Network for Answer SelectionCode0
Attentive Pooling NetworksCode0
ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence PairsCode0
Neural Variational Inference for Text ProcessingCode0
LSTM-based Deep Learning Models for Non-factoid Answer SelectionCode0
Distributed Deep Learning for Question Answering—0
WikiQA: A Challenge Dataset for Open-Domain Question Answering—0
Applying Deep Learning to Answer Selection: A Study and An Open TaskCode0
Answer Selection in Arabic Community Question Answering: A Feature-Rich Approach—0
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