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 44814490 of 10817 papers

TitleStatusHype
Deep Learning in Semantic Kernel Spaces0
Deep Learning in Event Detection in Polish0
AviationGPT: A Large Language Model for the Aviation Domain0
Deep learning evaluation using deep linguistic processing0
An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games0
MMPKUBase: A Comprehensive and High-quality Chinese Multi-modal Knowledge Graph0
Improving Zero-Shot Event Extraction via Sentence Simplification0
Deep Learning Approaches for Improving Question Answering Systems in Hepatocellular Carcinoma Research0
AVATAR: Robust Voice Search Engine Leveraging Autoregressive Document Retrieval and Contrastive Learning0
Deep Learning applications for COVID-190
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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