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 6201–6250 of 10817 papers

TitleStatusHype
Exploiting Numerical-Contextual Knowledge to Improve Numerical Reasoning in Question Answering—0
Explicit Graph Reasoning Fusing Knowledge and Contextual Information for Multi-hop Question AnsweringCode0
Zero-shot cross-lingual open domain question answering—0
Capturing Conversational Interaction for Question Answering via Global History ReasoningCode0
Transfer Learning and Masked Generation for Answer Verbalization—0
PINGAN_AI at SemEval-2022 Task 9: Recipe knowledge enhanced model applied in Competence-based Multimodal Question Answering—0
Dynamic Multistep Reasoning based on Video Scene Graph for Video Question Answering—0
Samsung Research Poland (SRPOL) at SemEval-2022 Task 9: Hybrid Question Answering Using Semantic Roles—0
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks.—0
Logical Story Representations via FrameNet + Semantic Parsing—0
Permutation Invariant Strategy Using Transformer Encoders for Table Understanding—0
Seeing the wood for the trees: a contrastive regularization method for the low-resource Knowledge Base Question AnsweringCode0
A New Concept of Knowledge based Question Answering (KBQA) System for Multi-hop Reasoning—0
Knowledge Transfer between Structured and Unstructured Sources for Complex Question Answering—0
An Encoder Attribution Analysis for Dense Passage Retriever in Open-Domain Question Answering—0
Raccoons at SemEval-2022 Task 11: Leveraging Concatenated Word Embeddings for Named Entity Recognition—0
VGNMN: Video-grounded Neural Module Networks for Video-Grounded Dialogue Systems—0
On Curriculum Learning for Commonsense ReasoningCode0
Contrastive Data and Learning for Natural Language Processing—0
PerKGQA: Question Answering over Personalized Knowledge Graphs—0
HIT&QMUL at SemEval-2022 Task 9: Label-Enclosed Generative Question Answering (LEG-QA)—0
Constraint-based Multi-hop Question Answering with Knowledge Graph—0
Conditional Generation with a Question-Answering Blueprint—0
American == White in Multimodal Language-and-Image AI—0
UFRGSent at SemEval-2022 Task 10: Structured Sentiment Analysis using a Question Answering Model—0
Ask Me Anything in Your Native Language—0
Modern Question Answering Datasets and Benchmarks: A Survey—0
EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answering—0
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks—0
What Can Secondary Predictions Tell Us? An Exploration on Question-Answering with SQuAD-v2.0Code0
On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based MethodCode0
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product Attribute Extraction—0
Kwame for Science: An AI Teaching Assistant Based on Sentence-BERT for Science Education in West Africa—0
Contextual embedding and model weighting by fusing domain knowledge on Biomedical Question AnsweringCode0
From Shallow to Deep: Compositional Reasoning over Graphs for Visual Question Answering—0
Evaluation of Semantic Answer Similarity MetricsCode0
QAGAN: Adversarial Approach To Learning Domain Invariant Language FeaturesCode0
OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking ExperienceCode0
VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason ObjectivesCode0
Tell Me the Evidence? Dual Visual-Linguistic Interaction for Answer Grounding—0
SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts—0
Grounding Answers for Visual Questions Asked by Visually Impaired People—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
A Numerical Reasoning Question Answering System with Fine-grained Retriever and the Ensemble of Multiple Generators for FinQA—0
Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks—0
An Open-Domain QA System for e-Governance—0
Interpretable AMR-Based Question Decomposition for Multi-hop Question Answering—0
Test-Time Adaptation for Visual Document Understanding—0
CHQ-Summ: A Dataset for Consumer Healthcare Question SummarizationCode0
Task Transfer and Domain Adaptation for Zero-Shot Question AnsweringCode0
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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