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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5576–5600 of 10817 papers

TitleStatusHype
Discourse Parsing with Attention-based Hierarchical Neural Networks—0
Learning Rich Image Region Representation for Visual Question Answering—0
Learning Rich Representation of Keyphrases from Text—0
IIE-NLP-NUT at SemEval-2020 Task 4: Guiding PLM with Prompt Template Reconstruction Strategy for ComVE—0
LIORI at SemEval-2021 Task 2: Span Prediction and Binary Classification approaches to Word-in-Context Disambiguation—0
Learning Semantic Relatedness in Community Question Answering Using Neural Models—0
Learning Semantic Structure through First-Order-Logic Translation—0
Discovering Bias in Latent Space: An Unsupervised Debiasing Approach—0
Learning Semantic Textual Similarity with Structural Representations—0
Learning Sentiment Lexicons in Spanish—0
IIE-NLP-Eyas at SemEval-2021 Task 4: Enhancing PLM for ReCAM with Special Tokens, Re-Ranking, Siamese Encoders and Back Translation—0
IICONGRAPH: improved Iconographic and Iconological Statements in Knowledge Graphs—0
Learning Sparsity for Effective and Efficient Music Performance Question Answering—0
ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Fora—0
Learning Structures of Negations from Flat Annotations—0
Learning Term Embeddings for Taxonomic Relation Identification Using Dynamic Weighting Neural Network—0
Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning—0
IHS-RD-Belarus at SemEval-2016 Task 1: Multistage Approach for Measuring Semantic Similarity—0
Learning to Answer Ambiguous Questions with Knowledge Graph—0
Discovering the Real Association: Multimodal Causal Reasoning in Video Question Answering—0
Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds—0
Learning to Answer Multilingual and Code-Mixed Questions—0
Learning to answer questions—0
Learning to Answer Questions From Image Using Convolutional Neural Network—0
I Have Seen Enough: A Teacher Student Network for Video Classification Using Fewer Frames—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