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 831840 of 10817 papers

TitleStatusHype
Distilling Knowledge from Reader to Retriever for Question AnsweringCode1
Explicit Planning Helps Language Models in Logical ReasoningCode1
Ditch the Gold Standard: Re-evaluating Conversational Question AnsweringCode1
Exploring and Predicting Transferability across NLP TasksCode1
DocNLI: A Large-scale Dataset for Document-level Natural Language InferenceCode1
Does Vision-and-Language Pretraining Improve Lexical Grounding?Code1
Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding SpaceCode1
Exploring Sequence-to-Sequence Models for SPARQL Pattern CompositionCode1
A-OKVQA: A Benchmark for Visual Question Answering using World KnowledgeCode1
Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence AnnotationCode1
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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