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 8301–8325 of 10817 papers

TitleStatusHype
Exploring Neural Net Augmentation to BERT for Question Answering on SQUAD 2.0—0
Simple and Effective Text Matching with Richer Alignment FeaturesCode0
ARS\_NITK at MEDIQA 2019:Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System—0
UU\_TAILS at MEDIQA 2019: Learning Textual Entailment in the Medical Domain—0
ChiMed: A Chinese Medical Corpus for Question AnsweringCode0
Predicting the Difficulty of Multiple Choice Questions in a High-stakes Medical Exam—0
Extending Neural Question Answering with Linguistic Input Features—0
A Paraphrase Generation System for EHR Question Answering—0
ANU-CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge—0
DUT-NLP at MEDIQA 2019: An Adversarial Multi-Task Network to Jointly Model Recognizing Question Entailment and Question Answering—0
DUT-BIM at MEDIQA 2019: Utilizing Transformer Network and Medical Domain-Specific Contextualized Representations for Question Answering—0
The Meaning of ``Most'' for Visual Question Answering Models—0
LasigeBioTM at MEDIQA 2019: Biomedical Question Answering using Bidirectional Transformers and Named Entity Recognition—0
Curio SmartChat : A system for Natural Language Question Answering for Self-Paced K-12 Learning—0
IIT-KGP at MEDIQA 2019: Recognizing Question Entailment using Sci-BERT stacked with a Gradient Boosting Classifier—0
Amharic Question Answering for Biography, Definition, and Description Questions—0
Learning Question-Guided Video Representation for Multi-Turn Video Question Answering—0
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation—0
LEAF-QA: Locate, Encode & Attend for Figure Question Answering—0
Reinforced Dynamic Reasoning for Conversational Question GenerationCode0
A mathematical model for universal semanticsCode0
An Empirical Study on Leveraging Scene Graphs for Visual Question Answering—0
Text-to-SQL Generation for Question Answering on Electronic Medical RecordsCode0
Careful Selection of Knowledge to solve Open Book Question Answering—0
SpanBERT: Improving Pre-training by Representing and Predicting SpansCode0
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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