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
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
Intelligent Assistant for People with Low Vision AbilitiesCode0
Adversarial Attacks Beyond the Image Space—0
Co-attending Regions and Detections with Multi-modal Multiplicative Embedding for VQACode0
Acquiring Common Sense Spatial Knowledge through Implicit Spatial TemplatesCode0
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
A Novel Framework for Robustness Analysis of Visual QA Models—0
FusionNet: Fusing via Fully-Aware Attention with Application to Machine ComprehensionCode0
CMU LiveMedQA at TREC 2017 LiveQA: A Consumer Health Question Answering System—0
A Deep Learning Approach for Expert Identification in Question Answering Communities—0
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question AnsweringCode0
Supervised and Unsupervised Transfer Learning for Question Answering—0
High-Order Attention Models for Visual Question AnsweringCode0
Fast Reading Comprehension with ConvNetsCode0
RubyStar: A Non-Task-Oriented Mixture Model Dialog System—0
Hi, how can I help you?: Automating enterprise IT support help desks—0
A Crowdsourcing Approach for Annotating Causal Relation Instances in Wikipedia—0
Integrating Vision and Language Datasets to Measure Word Concreteness—0
A Telecom-Domain Online Customer Service Assistant Based on Question Answering with Word Embedding and Intent Classification—0
Automated Historical Fact-Checking by Passage Retrieval, Word Statistics, and Virtual Question-Answering—0
Dual Constrained Question Embeddings with Relational Knowledge Bases for Simple Question Answering—0
Assessing the Verifiability of Attributions in News Text—0
An Exploration of Data Augmentation and RNN Architectures for Question Ranking in Community Question Answering—0
Enabling Transitivity for Lexical Inference on Chinese Verbs Using Probabilistic Soft Logic—0
Lexical Simplification with the Deep Structured Similarity Model—0
Guess What: A Question Answering Game via On-demand Knowledge Validation—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
Learning Transferable Representation for Bilingual Relation Extraction via Convolutional Neural Networks—0
Summarizing Lengthy Questions—0
Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification—0
Comparing Recurrent and Convolutional Architectures for English-Hindi Neural Machine Translation—0
A Method to Generate a Machine-Labeled Data for Biomedical Named Entity Recognition with Various Sub-Domains—0
Paraphrase Generation with Deep Reinforcement Learning—0
DCN+: Mixed Objective and Deep Residual Coattention for Question AnsweringCode0
Fast Linear Model for Knowledge Graph EmbeddingsCode0
Indirect Supervision for Relation Extraction using Question-Answer PairsCode1
Graph Attention NetworksCode1
A Hybrid Approach using Ontology Similarity and Fuzzy Logic for Semantic Question Answering—0
Simple and Effective Multi-Paragraph Reading ComprehensionCode1
Phase Conductor on Multi-layered Attentions for Machine Comprehension—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