Skip to search form
Skip to main content
Skip to account menu
Semantic Scholar
Semantic Scholar's Logo
Search 205,704,951 papers from all fields of science
Search
Sign In
Create Free Account
Question answering
Known as:
Open-domain question answering
, Answer engine
, Question answering system
Expand
Question Answer (Q AND A) is a computer science discipline within the fields of information retrieval and natural language processing (NLP), which is…
Expand
Wikipedia
Create Alert
Alert
Related topics
Related topics
42 relations
Artificial intelligence
Artificial intelligence in fiction
Artificial neural network
Data redundancy
Expand
Broader (2)
Computational linguistics
Natural language processing
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2019
Highly Cited
2019
Natural Questions: A Benchmark for Question Answering Research
T. Kwiatkowski
,
Jennimaria Palomaki
,
+15 authors
Slav Petrov
TACL
2019
Corpus ID: 86611921
We present the Natural Questions corpus, a question answering data set. Questions consist of real anonymized, aggregated queries…
Expand
Highly Cited
2018
Highly Cited
2018
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Zhilin Yang
,
Peng Qi
,
+4 authors
Christopher D. Manning
EMNLP
2018
Corpus ID: 52822214
Existing question answering (QA) datasets fail to train QA systems to perform complex reasoning and provide explanations for…
Expand
Highly Cited
2016
Highly Cited
2016
Stacked Attention Networks for Image Question Answering
Zichao Yang
,
Xiaodong He
,
Jianfeng Gao
,
L. Deng
,
Alex Smola
IEEE Conference on Computer Vision and Pattern…
2016
Corpus ID: 8849206
This paper presents stacked attention networks (SANs) that learn to answer natural language questions from images. SANs use…
Expand
Highly Cited
2016
Highly Cited
2016
Hierarchical Question-Image Co-Attention for Visual Question Answering
Jiasen Lu
,
Jianwei Yang
,
Dhruv Batra
,
Devi Parikh
NIPS
2016
Corpus ID: 868693
A number of recent works have proposed attention models for Visual Question Answering (VQA) that generate spatial maps…
Expand
Highly Cited
2016
Highly Cited
2016
Visual7W: Grounded Question Answering in Images
Yuke Zhu
,
O. Groth
,
Michael S. Bernstein
,
Li Fei-Fei
IEEE Conference on Computer Vision and Pattern…
2016
Corpus ID: 5714907
We have seen great progress in basic perceptual tasks such as object recognition and detection. However, AI models still fail to…
Expand
Highly Cited
2015
Highly Cited
2015
VQA: Visual Question Answering
Aishwarya Agrawal
,
Jiasen Lu
,
+4 authors
Dhruv Batra
IEEE International Conference on Computer Vision…
2015
Corpus ID: 3180429
We propose the task of free-form and open-ended Visual Question Answering (VQA). Given an image and a natural language question…
Expand
Review
2003
Review
2003
DRAFT Overview of the TREC 2003 Question Answering Track
E. Voorhees
2003
Corpus ID: 57983124
The TREC 2003 question answering track contained two tasks, the passages task and the main task. In the passages task, systems…
Expand
Highly Cited
2002
Highly Cited
2002
Learning surface text patterns for a Question Answering System
Deepak Ravichandran
,
E. Hovy
ACL
2002
Corpus ID: 226541
In this paper we explore the power of surface text patterns for open-domain question answering systems. In order to obtain an…
Expand
Highly Cited
2001
Highly Cited
2001
Discovery of inference rules for question-answering
Dekang Lin
,
P. Pantel
Natural Language Engineering
2001
Corpus ID: 12363172
One of the main challenges in question-answering is the potential mismatch between the expressions in questions and the…
Expand
Review
1999
Review
1999
The TREC-8 Question Answering Track Report
E. Voorhees
TREC
1999
Corpus ID: 16944215
The TREC-8 Question Answering track was the first large-scale evaluation of domain-independent question answering systems. This…
Expand
By clicking accept or continuing to use the site, you agree to the terms outlined in our
Privacy Policy
,
Terms of Service
, and
Dataset License
ACCEPT & CONTINUE