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

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Showing 7376–7400 of 10817 papers

TitleStatusHype
Transformers in Vision: A Survey—0
Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answering—0
Benchmarking Knowledge-Enhanced Commonsense Question Answering via Knowledge-to-Text Transformation—0
RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge—0
Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering—0
UnitedQA: A Hybrid Approach for Open Domain Question Answering—0
Pretrain Knowledge-Aware Language Models—0
Cluster-Former: Clustering-based Sparse Transformer for Question Answering—0
ChemistryQA: A Complex Question Answering Dataset from Chemistry—0
PABI: A Unified PAC-Bayesian Informativeness Measure for Incidental Supervision Signals—0
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned—0
Erasure for Advancing: Dynamic Self-Supervised Learning for Commonsense Reasoning—0
Env-QA: A Video Question Answering Benchmark for Comprehensive Understanding of Dynamic Environments—0
Multi-task Retrieval for Knowledge-Intensive Tasks—0
MULTI-SPAN QUESTION ANSWERING USING SPAN-IMAGE NETWORK—0
Video Question Answering Using Language-Guided Deep Compressed-Domain Video Feature—0
Block Skim Transformer for Efficient Question Answering—0
Memory Representation in Transformer—0
Linguistically Routing Capsule Network for Out-of-Distribution Visual Question Answering—0
Predicting the impact of dataset composition on model performance—0
Learning to Generate Questions by Recovering Answer-containing Sentences—0
Learning Contextualized Knowledge Graph Structures for Commonsense Reasoning—0
Differentiable End-to-End Program Executor for Sample and Computationally Efficient VQA—0
Unshuffling Data for Improved Generalization in Visual Question Answering—0
Symbol-Shift Equivariant Neural Networks—0
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified