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 39213930 of 10817 papers

TitleStatusHype
Using Weak Supervision and Data Augmentation in Question Answering0
Tackling VQA with Pretrained Foundation Models without Further Training0
Question answering using deep learning in low resource Indian language Marathi0
MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering0
Zero-Shot and Few-Shot Video Question Answering with Multi-Modal PromptsCode1
Fine-tuning and aligning question answering models for complex information extraction tasks0
Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning0
Question-Answering Approach to Evaluating Legal SummariesCode0
Legal Question-Answering in the Indian Context: Efficacy, Challenges, and Potential of Modern AI Models0
QASports: A Question Answering Dataset about SportsCode0
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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