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 9201–9250 of 10817 papers

TitleStatusHype
Soft Seeded SSL Graphs for Unsupervised Semantic Similarity-based Retrieval—0
Relation Extraction : A SurveyCode0
Contextualized Word Representations for Reading ComprehensionCode0
Stochastic Answer Networks for Machine Reading ComprehensionCode0
A Deep Network Model for Paraphrase Detection in Short Text Messages—0
Strong Baselines for Simple Question Answering over Knowledge Graphs with and without Neural Networks—0
Learning by Asking Questions—0
Incorporating External Knowledge to Answer Open-Domain Visual Questions with Dynamic Memory Networks—0
MappSent at IJCNLP-2017 Task 5: A Textual Similarity Approach Applied to Multi-choice Question Answering in Examinations—0
IJCNLP-2017 Task 5: Multi-choice Question Answering in Examinations—0
Chinese Answer Extraction Based on POS Tree and Genetic Algorithm—0
JU NITM at IJCNLP-2017 Task 5: A Classification Approach for Answer Selection in Multi-choice Question Answering System—0
Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question AnsweringCode0
ADAPT Centre Cone Team at IJCNLP-2017 Task 5: A Similarity-Based Logistic Regression Approach to Multi-choice Question Answering in an Examinations Shared Task—0
Multimodal Learning and Reasoning for Visual Question Answering—0
ALS at IJCNLP-2017 Task 5: Answer Localization System for Multi-Choice Question Answering in Exams—0
Question Retrieval with Distributed Representations and Participant Reputation in Community Question Answering—0
Forewords—0
YNUDLG at IJCNLP-2017 Task 5: A CNN-LSTM Model with Attention for Multi-choice Question Answering in Examinations—0
YNU-HPCC at IJCNLP-2017 Task 4: Attention-based Bi-directional GRU Model for Customer Feedback Analysis Task of English—0
YNU-HPCC at IJCNLP-2017 Task 5: Multi-choice Question Answering in Exams Using an Attention-based LSTM Model—0
Embodied Question AnsweringCode0
Hyper-dimensional computing for a visual question-answering system that is trainable end-to-end—0
Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams—0
A Deep Relevance Matching Model for Ad-hoc RetrievalCode0
Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce—0
Locally Smoothed Neural NetworksCode0
Visual Question Answering as a Meta Learning Task—0
Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning—0
Recurrent Relational NetworksCode0
Adversarial Attacks Beyond the Image Space—0
Intelligent Assistant for People with Low Vision AbilitiesCode0
Acquiring Common Sense Spatial Knowledge through Implicit Spatial TemplatesCode0
Co-attending Regions and Detections with Multi-modal Multiplicative Embedding for VQACode0
ADVISE: Symbolism and External Knowledge for Decoding Advertisements—0
Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)—0
Learning to Organize Knowledge and Answer Questions with N-Gram Machines—0
A Generative Approach to Question Answering—0
FusionNet: Fusing via Fully-Aware Attention with Application to Machine ComprehensionCode0
A Novel Framework for Robustness Analysis of Visual QA Models—0
CMU LiveMedQA at TREC 2017 LiveQA: A Consumer Health Question Answering System—0
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question AnsweringCode0
A Deep Learning Approach for Expert Identification in Question Answering Communities—0
Supervised and Unsupervised Transfer Learning for Question Answering—0
Fast Reading Comprehension with ConvNetsCode0
High-Order Attention Models for Visual Question AnsweringCode0
RubyStar: A Non-Task-Oriented Mixture Model Dialog System—0
Hi, how can I help you?: Automating enterprise IT support help desks—0
Efficiency-aware Answering of Compositional Questions using Answer Type Prediction—0
Integrating Subject, Type, and Property Identification for Simple Question Answering over Knowledge Base—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