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

Showing 26412650 of 10817 papers

TitleStatusHype
LEGAL-UQA: A Low-Resource Urdu-English Dataset for Legal Question AnsweringCode0
Answering Diverse Questions via Text Attached with Key Audio-Visual CluesCode0
Learning to Skim TextCode0
Learning Visual Question Answering by Bootstrapping Hard AttentionCode0
Answering Count Queries with Explanatory EvidenceCode0
Learning to Search in Long Documents Using Document StructureCode0
Learning to Represent Bilingual DictionariesCode0
Learning to Select from Multiple OptionsCode0
Learning What is Essential in QuestionsCode0
Less is More: Rejecting Unreliable Reviews for Product Question AnsweringCode0
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Benchmark Results

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