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 4951–4975 of 10817 papers

TitleStatusHype
Analogical Math Word Problems Solving with Enhanced Problem-Solution AssociationCode0
Iterative Scene Graph Generation with Generative Transformers—0
Weisfeiler and Leman Go RelationalCode0
AIONER: All-in-one scheme-based biomedical named entity recognition using deep learningCode1
A Probabilistic-Logic based Commonsense Representation Framework for Modelling Inferences with Multiple Antecedents and Varying Likelihoods—0
A Pipeline for Generating, Annotating and Employing Synthetic Data for Real World Question AnsweringCode0
Domain Mismatch Doesn't Always Prevent Cross-Lingual Transfer Learning—0
Optimizing Explanations by Network Canonization and Hyperparameter Search—0
CREPE: Open-Domain Question Answering with False PresuppositionsCode1
Which Shortcut Solution Do Question Answering Models Prefer to Learn?Code0
Penalizing Confident Predictions on Largely Perturbed Inputs Does Not Improve Out-of-Distribution Generalization in Question Answering—0
Diverse Multi-Answer Retrieval with Determinantal Point Processes—0
Few-shot Query-Focused Summarization with Prefix-Merging—0
PiggyBack: Pretrained Visual Question Answering Environment for Backing up Non-deep Learning Professionals—0
A Survey on Conversational Search and Applications in Biomedicine—0
Frustratingly Easy Label Projection for Cross-lingual TransferCode1
Neuro-Symbolic Spatio-Temporal Reasoning—0
Understanding BLOOM: An empirical study on diverse NLP tasks—0
Combining Data Generation and Active Learning for Low-Resource Question AnsweringCode0
Question Answering and Question Generation for Finnish—0
Seeing What You Miss: Vision-Language Pre-training with Semantic Completion LearningCode1
TSGP: Two-Stage Generative Prompting for Unsupervised Commonsense Question AnsweringCode0
Self-supervised vision-language pretraining for Medical visual question answeringCode1
Look, Read and Ask: Learning to Ask Questions by Reading Text in Images—0
Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference—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