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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 101–125 of 171 papers

TitleStatusHype
Learning to Collaborate for Question Answering and Asking—0
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
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
IIT-UHH at SemEval-2017 Task 3: Exploring Multiple Features for Community Question Answering and Implicit Dialogue IdentificationCode0
Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features for Community Question Answering—0
FuRongWang at SemEval-2017 Task 3: Deep Neural Networks for Selecting Relevant Answers in Community Question Answering—0
Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification—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
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
EviNets: Neural Networks for Combining Evidence Signals for Factoid Question Answering—0
End-to-End Non-Factoid Question Answering with an Interactive Visualization of Neural Attention Weights—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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