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 87768800 of 10817 papers

TitleStatusHype
Deep Attentive Sentence Ordering Network0
Direct optimization of F-measure for retrieval-based personal question answering0
A Qualitative Comparison of CoQA, SQuAD 2.0 and QuACCode0
Learning Corresponded Rationales for Text Matching0
Learning to Coordinate Multiple Reinforcement Learning Agents for Diverse Query Reformulation0
Denoise while Aggregating: Collaborative Learning in Open-Domain Question Answering0
No One is Perfect: Analysing the Performance of Question Answering Components over the DBpedia Knowledge GraphCode0
ComQA: A Community-sourced Dataset for Complex Factoid Question Answering with Paraphrase Clusters0
Joint Multitask Learning for Community Question Answering Using Task-Specific Embeddings0
Stochastic Answer Networks for SQuAD 2.0Code0
Textually Enriched Neural Module Networks for Visual Question Answering0
Neural Approaches to Conversational AI0
Multimodal Dual Attention Memory for Video Story Question Answering0
A Quantitative Evaluation of Natural Language Question Interpretation for Question Answering Systems0
Symbolic Priors for RNN-based Semantic ParsingCode0
Multi-task Learning with Sample Re-weighting for Machine Reading ComprehensionCode0
Commonsense for Generative Multi-Hop Question Answering TasksCode0
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain0
Answering Science Exam Questions Using Query Rewriting with Background Knowledge0
Knowledge Based Machine Reading Comprehension0
The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA0
The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR0
Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions0
How much should you ask? On the question structure in QA systems0
Explicit Utilization of General Knowledge in Machine Reading Comprehension0
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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