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 791800 of 10817 papers

TitleStatusHype
Does Vision-and-Language Pretraining Improve Lexical Grounding?Code1
Dynamic Semantic Graph Construction and Reasoning for Explainable Multi-hop Science Question AnsweringCode1
Empirical Study of Zero-Shot NER with ChatGPTCode1
Empower Entity Set Expansion via Language Model ProbingCode1
Ditch the Gold Standard: Re-evaluating Conversational Question AnsweringCode1
Answering Questions by Meta-Reasoning over Multiple Chains of ThoughtCode1
AfriQA: Cross-lingual Open-Retrieval Question Answering for African LanguagesCode1
Answering Questions on COVID-19 in Real-TimeCode1
Diversify Question Generation with Retrieval-Augmented Style TransferCode1
Distilling Knowledge from Reader to Retriever for Question AnsweringCode1
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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