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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

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Showing 101–125 of 171 papers

TitleStatusHype
Joint Training of Candidate Extraction and Answer Selection for Reading Comprehension—0
CLINIQA: A Machine Intelligence Based Clinical Question Answering System—0
PhotoshopQuiA: A Corpus of Non-Factoid Questions and Answers for Why-Question Answering—0
Adversarial Training for Community Question Answer Selection Based on Multi-scale Matching—0
Question-Answer Selection in User to User Marketplace Conversations—0
Attentive Recurrent Tensor Model for Community Question Answering—0
MilkQA: a Dataset of Consumer Questions for the Task of Answer Selection—0
ADAPT Centre Cone Team at IJCNLP-2017 Task 5: A Similarity-Based Logistic Regression Approach to Multi-choice Question Answering in an Examinations Shared Task—0
JU NITM at IJCNLP-2017 Task 5: A Classification Approach for Answer Selection in Multi-choice Question Answering System—0
Learning to Rank Question-Answer Pairs using Hierarchical Recurrent Encoder with Latent Topic ClusteringCode1
The Effect of Negative Sampling Strategy on Capturing Semantic Similarity in Document Embeddings—0
Improved Answer Selection with Pre-Trained Word Embeddings—0
ISS-MULT: Intelligent Sample Selection for Multi-Task Learning in Question Answering—0
Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification—0
FuRongWang at SemEval-2017 Task 3: Deep Neural Networks for Selecting Relevant Answers in Community Question Answering—0
Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features for Community Question Answering—0
GW\_QA at SemEval-2017 Task 3: Question Answer Re-ranking on Arabic Fora—0
HCTI at SemEval-2017 Task 1: Use convolutional neural network to evaluate Semantic Textual Similarity—0
IIT-UHH at SemEval-2017 Task 3: Exploring Multiple Features for Community Question Answering and Implicit Dialogue IdentificationCode0
Exploring the Effectiveness of Convolutional Neural Networks for Answer Selection in End-to-End Question Answering—0
An Attention Mechanism for Answer Selection Using a Combined Global and Local View—0
End-to-End Non-Factoid Question Answering with an Interactive Visualization of Neural Attention Weights—0
EviNets: Neural Networks for Combining Evidence Signals for Factoid Question Answering—0
If You Can't Beat Them Join Them: Handcrafted Features Complement Neural Nets for Non-Factoid Answer Reranking—0
Task-Specific Attentive Pooling of Phrase Alignments Contributes to Sentence Matching—0
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