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 17211730 of 10817 papers

TitleStatusHype
Designing a Minimal Retrieve-and-Read System for Open-Domain Question AnsweringCode1
Describe Anything Model for Visual Question Answering on Text-rich ImagesCode1
Densely Connected Attention Propagation for Reading ComprehensionCode1
Can Language Models Solve Graph Problems in Natural Language?Code1
PathVQA: 30000+ Questions for Medical Visual Question AnsweringCode1
Are self-explanations from Large Language Models faithful?Code1
Can't Remember Details in Long Documents? You Need Some R&RCode1
Can large language models reason about medical questions?Code1
Dense Passage Retrieval for Open-Domain Question AnsweringCode1
Detecting and Preventing Hallucinations in Large Vision Language ModelsCode1
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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