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 9276–9300 of 10817 papers

TitleStatusHype
Variational Reasoning for Question Answering with Knowledge GraphCode0
Abductive Matching in Question Answering—0
Globally Normalized ReaderCode0
Simple Recurrent Units for Highly Parallelizable RecurrenceCode2
A Unified Query-based Generative Model for Question Generation and Question Answering—0
Understanding the Logical and Semantic Structure of Large Documents—0
Memory Augmented Neural Networks for Natural Language Processing—0
Do Not Trust the Trolls: Predicting Credibility in Community Question Answering ForumsCode0
MappSent: a Textual Mapping Approach for Question-to-Question Similarity—0
Applying Deep Neural Network to Retrieve Relevant Civil Law Articles—0
Bootstrapping a Romanian Corpus for Medical Named Entity Recognition—0
Joint Unsupervised Learning of Semantic Representation of Words and Roles in Dependency Trees—0
Measuring the Limit of Semantic Divergence for English Tweets.—0
A Domain and Language Independent Named Entity Classification Approach Based on Profiles and Local Information—0
Improved Recognition and Normalisation of Polish Temporal Expressions—0
Same same, but different: Compositionality of paraphrase granularity levelsCode0
Word Embeddings as Features for Supervised Coreference Resolution—0
The Effect of Negative Sampling Strategy on Capturing Semantic Similarity in Document Embeddings—0
oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain—0
A Diachronic Corpus for Romanian (RoDia)—0
Document retrieval and question answering in medical documents. A large-scale corpus challenge.—0
Neural Paraphrase Generation using Transfer Learning—0
Generating Answering Patterns from Factoid Arabic Questions—0
From Shakespeare to Twitter: What are Language Styles all about?—0
Coarse-to-Fine Attention Models for Document Summarization—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