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 9351–9375 of 10817 papers

TitleStatusHype
A Diachronic Corpus for Romanian (RoDia)—0
Classification of telicity using cross-linguistic annotation projectionCode0
Rhetorical relations markers in Russian RST Treebank—0
Accurate Supervised and Semi-Supervised Machine Reading for Long Documents—0
Exploiting Morphological Regularities in Distributional Word Representations—0
Same same, but different: Compositionality of paraphrase granularity levelsCode0
Coarse-to-Fine Attention Models for Document Summarization—0
R^3: Reinforced Reader-Ranker for Open-Domain Question AnsweringCode0
Learning Fine-Grained Knowledge about Contingent Relations between Everyday Events—0
TableQA: Question Answering on Tabular Data—0
Subspace Approximation for Approximate Nearest Neighbor Search in NLP—0
Learning to Paraphrase for Question Answering—0
A Question Answering Approach to Emotion Cause Extraction—0
Natural Language Processing: State of The Art, Current Trends and ChallengesCode0
VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic SegmentationCode0
Mining Deep And-Or Object Structures via Cost-Sensitive Question-Answer-Based Active Annotations—0
Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual Question AnsweringCode0
Learning to Disambiguate by Asking Discriminative Questions—0
Robust Computer Algebra, Theorem Proving, and Oracle AI—0
ISS-MULT: Intelligent Sample Selection for Multi-Task Learning in Question Answering—0
Asking Too Much? The Rhetorical Role of Questions in Political Discourse—0
Automatic Question-Answering Using A Deep Similarity Neural Network—0
MemexQA: Visual Memex Question AnsweringCode0
Multi-modal Factorized Bilinear Pooling with Co-Attention Learning for Visual Question AnsweringCode0
A Simple Loss Function for Improving the Convergence and Accuracy of Visual Question Answering ModelsCode0
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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