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 8151–8175 of 10817 papers

TitleStatusHype
Bridging the Knowledge Gap: Enhancing Question Answering with World and Domain Knowledge—0
NumNet: Machine Reading Comprehension with Numerical ReasoningCode0
Enhancing the Transformer with Explicit Relational Encoding for Math Problem SolvingCode0
Efficiently Embedding Dynamic Knowledge Graphs—0
Answering Complex Open-domain Questions Through Iterative Query GenerationCode0
Structured Pruning of a BERT-based Question Answering Model—0
Whatcha lookin' at? DeepLIFTing BERT's Attention in Question AnsweringCode0
Neural Memory Plasticity for Anomaly Detection—0
Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge BaseCode0
Multi-modal Deep Analysis for Multimedia—0
Learning Analogy-Preserving Sentence Embeddings for Answer Selection—0
Multilingual Question Answering from Formatted Text applied to Conversational Agents—0
Domain-Relevant Embeddings for Medical Question Similarity—0
Modulated Self-attention Convolutional Network for VQA—0
Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context ExpansionCode0
Multi-hop Question Answering via Reasoning ChainsCode0
REMIND Your Neural Network to Prevent Catastrophic ForgettingCode0
Measuring Sentences Similarity: A Survey—0
Multi-level Gated Recurrent Neural Network for Dialog Act Classification—0
From Strings to Things: Knowledge-Enabled VQA Model That Can Read and Reason—0
Neural Question Generation using Interrogative Phrases—0
MMM: Multi-stage Multi-task Learning for Multi-choice Reading ComprehensionCode0
SegEQA: Video Segmentation Based Visual Attention for Embodied Question Answering—0
BERT for Question Generation—0
基於特徵粒度之訓練策略於中文口語問答系統之應用(A Feature-granularity Training Strategy for Chinese Spoken Question Answering)—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