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 9526–9550 of 10817 papers

TitleStatusHype
ICE: Idiom and Collocation Extractor for Research and Education—0
Effective shared representations with Multitask Learning for Community Question Answering—0
Discriminative Information Retrieval for Question Answering Sentence SelectionCode0
Integrating Semantic Knowledge into Lexical Embeddings Based on Information Content MeasurementCode0
Improving Chinese Semantic Role Labeling using High-quality Surface and Deep Case Frames—0
On-demand Injection of Lexical Knowledge for Recognising Textual Entailment—0
Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model—0
Probabilistic Inference for Cold Start Knowledge Base Population with Prior World Knowledge—0
On the Need of Cross Validation for Discourse Relation Classification—0
If No Media Were Allowed inside the Venue, Was Anybody Allowed?—0
MT/IE: Cross-lingual Open Information Extraction with Neural Sequence-to-Sequence Models—0
Metaheuristic Approaches to Lexical Substitution and Simplification—0
Paraphrasing Revisited with Neural Machine Translation—0
Learning and Knowledge Transfer with Memory Networks for Machine Comprehension—0
If You Can't Beat Them Join Them: Handcrafted Features Complement Neural Nets for Non-Factoid Answer Reranking—0
Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?Code0
Reading Wikipedia to Answer Open-Domain QuestionsCode1
An Analysis of Visual Question Answering Algorithms—0
Question Answering from Unstructured Text by Retrieval and Comprehension—0
Multimodal Compact Bilinear Pooling for Multimodal Neural Machine Translation—0
Recurrent and Contextual Models for Visual Question Answering—0
VQABQ: Visual Question Answering by Basic Questions—0
Temporal Information Extraction for Question Answering Using Syntactic Dependencies in an LSTM-based Architecture—0
Legal Question Answering using Ranking SVM and Deep Convolutional Neural Network—0
Emergence of Grounded Compositional Language in Multi-Agent PopulationsCode1
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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