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 9601–9625 of 10817 papers

TitleStatusHype
MarioQA: Answering Questions by Watching Gameplay Videos—0
Probabilistic Neural Programs—0
Neural Attention for Learning to Rank Questions in Community Question Answering—0
Constraint-Based Question Answering with Knowledge GraphCode0
Dialog-based Language Learning—0
ENIAM: Categorial Syntactic-Semantic Parser for Polish—0
CogALex-V Shared Task: CGSRC - Classifying Semantic Relations using Convolutional Neural Networks—0
Global Inference to Chinese Temporal Relation Extraction—0
Implicit Discourse Relation Recognition with Context-aware Character-enhanced Embeddings—0
Large-Scale Acquisition of Commonsense Knowledge via a Quiz Game on a Dialogue System—0
Different Contexts Lead to Different Word Embeddings—0
Mongolian Named Entity Recognition System with Rich Features—0
From Entity Linking to Question Answering -- Recent Progress on Semantic Grounding Tasks—0
A Hierarchical Neural Network for Information Extraction of Product Attribute and Condition Sentences—0
A Supervised Approach for Enriching the Relational Structure of Frame Semantics in FrameNet—0
Categorization of Semantic Roles for Dictionary Definitions—0
Multilingual Supervision of Semantic Annotation—0
Distributional Hypernym Generation by Jointly Learning Clusters and Projections—0
Pairwise Relation Classification with Mirror Instances and a Combined Convolutional Neural Network—0
Pairing Wikipedia Articles Across Languages—0
CATENA: CAusal and TEmporal relation extraction from NAtural language textsCode0
Reading and Thinking: Re-read LSTM Unit for Textual Entailment Recognition—0
High Accuracy Rule-based Question Classification using Question Syntax and Semantics—0
Multilingual Aliasing for Auto-Generating Proposition Banks—0
Annotation and Analysis of Discourse Relations, Temporal Relations and Multi-Layered Situational Relations in Japanese Texts—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