SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

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Showing 9801–9850 of 10817 papers

TitleStatusHype
Combining Natural Logic and Shallow Reasoning for Question Answering—0
Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text—0
Supersense Embeddings: A Unified Model for Supersense Interpretation, Prediction, and Utilization—0
Unanimous Prediction for 100\% Precision with Application to Learning Semantic Mappings—0
TransG : A Generative Model for Knowledge Graph Embedding—0
TranscRater: a Tool for Automatic Speech Recognition Quality Estimation—0
The Value of Semantic Parse Labeling for Knowledge Base Question Answering—0
Together we stand: Siamese Networks for Similar Question Retrieval—0
Speech Act Modeling of Written Asynchronous Conversations with Task-Specific Embeddings and Conditional Structured Models—0
Tables as Semi-structured Knowledge for Question Answering—0
Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question AnsweringCode0
Neural Contextual Conversation Learning with Labeled Question-Answering Pairs—0
An Empirical Evaluation of various Deep Learning Architectures for Bi-Sequence Classification Tasks—0
Attention-over-Attention Neural Networks for Reading ComprehensionCode0
Using Recurrent Neural Network for Learning Expressive Ontologies—0
Neural Semantic EncodersCode0
Estimating Uncertainty Online Against an Adversary—0
Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal KnowledgeCode0
Mapping distributional to model-theoretic semantic spaces: a baselineCode0
Annotation Methodologies for Vision and Language Dataset Creation—0
A Semi-supervised learning approach to enhance health care Community-based Question Answering: A case study in alcoholism—0
Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes—0
SelQA: A New Benchmark for Selection-based Question AnsweringCode0
Analyzing the Behavior of Visual Question Answering ModelsCode0
Automated Extraction of Number of Subjects in Randomised Controlled Trials—0
Deep Feature Fusion Network for Answer Quality Prediction in Community Question Answering—0
Semantic Parsing to Probabilistic Programs for Situated Question Answering—0
Question Relevance in VQA: Identifying Non-Visual And False-Premise Questions—0
DualNet: Domain-Invariant Network for Visual Question Answering—0
Full-Time Supervision based Bidirectional RNN for Factoid Question Answering—0
Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions?—0
FVQA: Fact-based Visual Question Answering—0
SQuAD: 100,000+ Questions for Machine Comprehension of TextCode1
No Need to Pay Attention: Simple Recurrent Neural Networks Work! (for Answering "Simple" Questions)—0
A Study of MatchPyramid Models on Ad-hoc RetrievalCode0
Query-Reduction Networks for Question AnsweringCode0
Dialog state tracking, a machine reading approach using Memory Network—0
Training Recurrent Answering Units with Joint Loss Minimization for VQA—0
Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions?—0
Simple Question Answering by Attentive Convolutional Neural Network—0
Key-Value Memory Networks for Directly Reading DocumentsCode0
Natural Language Comprehension with the EpiReader—0
CFO: Conditional Focused Neural Question Answering with Large-scale Knowledge Bases—0
Iterative Alternating Neural Attention for Machine ReadingCode0
Multimodal Residual Learning for Visual QACode0
Gated-Attention Readers for Text ComprehensionCode0
Generating Natural Language Inference Chains—0
Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Information—0
Answer-Type Prediction for Visual Question Answering—0
ArabTAG: from a Handcrafted to a Semi-automatically Generated TAG—0
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified