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 7351–7400 of 10817 papers

TitleStatusHype
Reading Comprehension as Natural Language Inference: A Semantic Analysis—0
CAPTION: Correction by Analyses, POS-Tagging and Interpretation of Objects using only Nouns—0
MultiCQA: Zero-Shot Transfer of Self-Supervised Text Matching Models on a Massive ScaleCode1
LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentionCode1
Autoregressive Entity RetrievalCode1
Mongolian Questions Classification Based on Mulit-Head Attention—0
基于多头注意力和BiLSTM改进DAM模型的中文问答匹配方法(Chinese question answering method based on multi-head attention and BiLSTM improved DAM model)—0
Combining Impression Feature Representation for Multi-turn Conversational Question Answering—0
How State-Of-The-Art Models Can Deal With Long-Form Question Answering—0
ARES: A Reading Comprehension Ensembling Service—0
CoSaTa: A Constraint Satisfaction Solver and Interpreted Language for Semi-Structured Tables of SentencesCode0
A Technical Question Answering System with Transfer LearningCode0
Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling—0
LiveQA: A Question Answering Dataset over Sports LiveCode0
Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a SummaryCode1
ISAAQ -- Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention—0
Interpreting Graph Neural Networks for NLP With Differentiable Edge MaskingCode1
Case-Based Abductive Natural Language Inference—0
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension—0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension—0
Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks—0
Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network—0
Spatial Attention as an Interface for Image Captioning Models—0
Neural Retrieval for Question Answering with Cross-Attention Supervised Data Augmentation—0
MaP: A Matrix-based Prediction Approach to Improve Span Extraction in Machine Reading Comprehension—0
Sequence-to-Sequence Learning for Indonesian Automatic Question GeneratorCode1
A Survey on Semantic Parsing from the perspective of Compositionality—0
VECO: Variable Encoder-decoder Pre-training for Cross-lingual Understanding and Generation—0
Multi-Relational Embedding for Knowledge Graph Representation and AnalysisCode1
SPARTA: Efficient Open-Domain Question Answering via Sparse Transformer Matching RetrievalCode1
What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical ExamsCode2
Answering Complex Open-Domain Questions with Multi-Hop Dense RetrievalCode1
Unsupervised Pre-training for Biomedical Question Answering—0
Hierarchical Deep Multi-modal Network for Medical Visual Question AnsweringCode0
XTE: Explainable Text Entailment—0
AliMe KG: Domain Knowledge Graph Construction and Application in E-commerce—0
Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases—0
Multiple interaction learning with question-type prior knowledge for constraining answer search space in visual question answeringCode0
X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal TransformersCode1
Using the Hammer Only on Nails: A Hybrid Method for Evidence Retrieval for Question Answering—0
SQuARE: Semantics-based Question Answering and Reasoning Engine—0
Regularizing Attention Networks for Anomaly Detection in Visual Question Answering—0
UCD-CS at W-NUT 2020 Shared Task-3: A Text to Text Approach for COVID-19 Event Extraction on Social MediaCode1
Can questions summarize a corpus? Using question generation for characterizing COVID-19 researchCode1
Looking Beyond Sentence-Level Natural Language Inference for Downstream Tasks—0
Tradeoffs in Sentence Selection Techniques for Open-Domain Question Answering—0
MUTANT: A Training Paradigm for Out-of-Distribution Generalization in Visual Question AnsweringCode1
Self-supervised pre-training and contrastive representation learning for multiple-choice video QA—0
On the Transferability of Minimal Prediction Preserving Inputs in Question Answering—0
Multi-modal Summarization for Video-containing DocumentsCode1
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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