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 6501–6550 of 10817 papers

TitleStatusHype
Recursive Tree-Structured Self-Attention for Answer Sentence Selection—0
DESCGEN: A Distantly Supervised Datasetfor Generating Entity DescriptionsCode0
Zero-shot Event Extraction via Transfer Learning: Challenges and Insights—0
In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering—0
xMoCo: Cross Momentum Contrastive Learning for Open-Domain Question Answering—0
COSY: COunterfactual SYntax for Cross-Lingual UnderstandingCode0
Addressing Semantic Drift in Generative Question Answering with Auxiliary Extraction—0
Continuous Language Generative FlowCode1
BiQuAD: Towards QA based on deeper text understanding—0
LIORI at SemEval-2021 Task 2: Span Prediction and Binary Classification approaches to Word-in-Context Disambiguation—0
UoR at SemEval-2021 Task 4: Using Pre-trained BERT Token Embeddings for Question Answering of Abstract Meaning—0
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes—0
Automatic Claim Review for Climate Science via Explanation Generation—0
An Online Question Answering System based on Sub-graph Searching—0
QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension—0
Greedy Gradient Ensemble for Robust Visual Question AnsweringCode1
Thought Flow Nets: From Single Predictions to Trains of Model Thought—0
One Question Answering Model for Many Languages with Cross-lingual Dense Passage RetrievalCode1
Hybrid Autoregressive Inference for Scalable Multi-hop Explanation RegenerationCode0
X-GGM: Graph Generative Modeling for Out-of-Distribution Generalization in Visual Question AnsweringCode0
The Effectiveness of Intermediate-Task Training for Code-Switched Natural Language Understanding—0
CogME: A Cognition-Inspired Multi-Dimensional Evaluation Metric for Story Understanding—0
Separating Skills and Concepts for Novel Visual Question AnsweringCode1
Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision—0
A Discriminative Semantic Ranker for Question Retrieval—0
Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan—0
Exploiting Rich Syntax for Better Knowledge Base Question Answering—0
A Survey of Knowledge Graph Embedding and Their Applications—0
MarIA: Spanish Language ModelsCode1
Applications of knowledge graphs for food science and industry—0
Human Attention during Goal-directed Reading Comprehension Relies on Task OptimizationCode0
How Much Can CLIP Benefit Vision-and-Language Tasks?Code1
Graphhopper: Multi-Hop Scene Graph Reasoning for Visual Question AnsweringCode1
PonderNet: Learning to PonderCode1
Zero-shot Visual Question Answering using Knowledge GraphCode1
Answer Complex Questions: Path Ranker Is All You NeedCode0
Similar Cases Recommendation using Legal Knowledge GraphsCode0
DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question AnsweringCode1
An Initial Investigation of Non-Native Spoken Question-Answering—0
Benchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERTCode1
Joint Models for Answer Verification in Question Answering Systems—0
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic HardwareCode1
Robustifying Multi-hop QA through Pseudo-Evidentiality Training—0
MedGPT: Medical Concept Prediction from Clinical Narratives—0
MuVAM: A Multi-View Attention-based Model for Medical Visual Question Answering—0
Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review—0
Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linking—0
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question AnsweringCode1
A Knowledge-based Approach for Answering Complex Questions in Persian—0
Training Adaptive Computation for Open-Domain Question Answering with Computational ConstraintsCode1
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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