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 7751–7800 of 10817 papers

TitleStatusHype
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation—0
CopyBERT: A Unified Approach to Question Generation with Self-Attention—0
How Self-Attention Improves Rare Class Performance in a Question-Answering Dialogue Agent—0
GLUECoS: An Evaluation Benchmark for Code-Switched NLP—0
BERTERS: Multimodal Representation Learning for Expert Recommendation System with Transformer—0
Correction of Faulty Background Knowledge based on Condition Aware and Revise Transformer for Question Answering—0
Knowledge-Aware Language Model Pretraining—0
Answer Ranking for Product-Related Questions via Multiple Semantic Relations Modeling—0
Improving VQA and its Explanations \\ by Comparing Competing Explanations—0
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance—0
Self-Segregating and Coordinated-Segregating Transformer for Focused Deep Multi-Modular Network for Visual Question Answering—0
AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types—0
NLPContributions: An Annotation Scheme for Machine Reading of Scholarly Contributions in Natural Language Processing LiteratureCode0
Match^2: A Matching over Matching Model for Similar Question Identification—0
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"—0
Memory TransformerCode0
IQA: Interactive Query Construction in Semantic Question Answering SystemsCode0
SqueezeBERT: What can computer vision teach NLP about efficient neural networks?Code0
Exploring the BERT Cross-Lingual Transferability: a Case Study in Reading Comprehension—0
CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization—0
SPARQL query generation for complex question answering with BERT and BiLSTM-based model—0
Results of the seventh edition of the BioASQ Challenge—0
Selective Question Answering under Domain ShiftCode0
Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering—0
ORD: Object Relationship Discovery for Visual Dialogue Generation—0
Mining Implicit Relevance Feedback from User Behavior for Web Question Answering—0
Video Understanding as Machine Translation—0
Exploring Weaknesses of VQA Models through Attribution Driven Insights—0
Estimating semantic structure for the VQA answer space—0
Foreseeing the Benefits of Incidental SupervisionCode0
Knowledge-Aided Open-Domain Question Answering—0
Language Models as Fact Checkers?—0
English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too—0
Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension—0
Open-Domain Question Answering with Pre-Constructed Question Spaces—0
BERT Based Multilingual Machine Comprehension in English and HindiCode0
Subjective Question Answering: Deciphering the inner workings of Transformers in the realm of subjectivityCode0
Question Answering on Scholarly Knowledge Graphs—0
Probing Emergent Semantics in Predictive Agents via Question Answering—0
Multimodal grid features and cell pointers for Scene Text Visual Question Answering—0
Building a Swedish Question-Answering ModelCode0
TA-Student VQA: Multi-Agents Training by Self-Questioning—0
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features—0
Counterfactual Vision and Language Learning—0
Conversational Machine Comprehension: a Literature Review—0
Context-based Transformer Models for Answer Sentence Selection—0
Efficient Deployment of Conversational Natural Language Interfaces over Databases—0
Improving Quality of a Post's Set of Answers in Stack OverflowCode0
Using Large Pretrained Language Models for Answering User Queries from Product Specifications—0
English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too—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