Answer Selection
47 papers with code • 6 benchmarks • 10 datasets
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
Benchmarks
These leaderboards are used to track progress in Answer Selection
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
WikiQA
TrecQA
UDC
InsuranceQA
CICERO
SelQA
Most implemented papers
Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering
Second, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), while KBQA can be improved by learning contextual information from answer selection.
Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
malllabiisc/EmbedKGQA
•
•
ACL 2020
In a separate line of research, KG embedding methods have been proposed to reduce KG sparsity by performing missing link prediction.
Raven's Progressive Matrices Completion with Latent Gaussian Process Priors
fudanvi/generative-abstract-reasoning
•
•
In this paper we aim to solve the latter one by proposing a deep latent variable model, in which multiple Gaussian processes are employed as priors of latent variables to separately learn underlying abstract concepts from RPMs; thus the proposed model is interpretable in terms of concept-specific latent variables.
M$^2$S-Net: Multi-Modal Similarity Metric Learning based Deep Convolutional Network for Answer Selection
Recent works using artificial neural networks based on distributed word representation greatly boost performance on various natural language processing tasks, especially the answer selection problem.
Hierarchical Memory Networks for Answer Selection on Unknown Words
Recently, end-to-end memory networks have shown promising results on Question Answering task, which encode the past facts into an explicit memory and perform reasoning ability by making multiple computational steps on the memory.
Learning Recurrent Span Representations for Extractive Question Answering
In this paper, we focus on this answer extraction task, presenting a novel model architecture that efficiently builds fixed length representations of all spans in the evidence document with a recurrent network.
IIT-UHH at SemEval-2017 Task 3: Exploring Multiple Features for Community Question Answering and Implicit Dialogue Identification
In this paper we present the system for Answer Selection and Ranking in Community Question Answering, which we build as part of our participation in SemEval-2017 Task 3.
Question Condensing Networks for Answer Selection in Community Question Answering
Answer selection is an important subtask of community question answering (CQA).
Document Modeling with External Attention for Sentence Extraction
shashiongithub/Document-Models-with-Ext-Information
•
•
ACL 2018
Document modeling is essential to a variety of natural language understanding tasks.
