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 7601–7650 of 10817 papers

TitleStatusHype
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks—0
Hierarchical Poset Decoding for Compositional Generalization in Language—0
A Graph Representation of Semi-structured Data for Web Question Answering—0
F1 is Not Enough! Models and Evaluation Towards User-Centered Explainable Question AnsweringCode0
Does my multimodal model learn cross-modal interactions? It's harder to tell than you might think!—0
A Wrong Answer or a Wrong Question? An Intricate Relationship between Question Reformulation and Answer Selection in Conversational Question AnsweringCode0
Neural, Symbolic and Neural-Symbolic Reasoning on Knowledge Graphs—0
End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering SystemsCode0
BioMegatron: Larger Biomedical Domain Language Model—0
Towards Accurate and Reliable Energy Measurement of NLP ModelsCode0
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise TasksCode0
Localizing Open-Ontology QA Semantic Parsers in a Day Using Machine TranslationCode0
Beyond Language: Learning Commonsense from Images for ReasoningCode0
Interpretable Neural Computation for Real-World Compositional Visual Question Answering—0
Artificial Intelligence (AI) in Action: Addressing the COVID-19 Pandemic with Natural Language Processing (NLP)—0
Relation Classification as Two-way Span-Prediction—0
Characterizing Datasets for Social Visual Question Answering, and the New TinySocial Dataset—0
On the importance of pre-training data volume for compact language models—0
Unsupervised Evaluation for Question Answering with Transformers—0
DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling—0
Learning a Cost-Effective Annotation Policy for Question AnsweringCode0
Improving QA Generalization by Concurrent Modeling of Multiple BiasesCode0
Finding the Evidence: Localization-aware Answer Prediction for Text Visual Question Answering—0
Pathological Visual Question Answering—0
Multi-Fact Correction in Abstractive Text Summarization—0
Efficient Meta Lifelong-Learning with Limited Memory—0
BERT Knows Punta Cana is not just beautiful, it's gorgeous: Ranking Scalar Adjectives with Contextualised RepresentationsCode0
Joint Semantics and Data-Driven Path Representation for Knowledge Graph Inference—0
DaNetQA: a yes/no Question Answering Dataset for the Russian Language—0
Context Modeling with Evidence Filter for Multiple Choice Question Answering—0
Attention Guided Semantic Relationship Parsing for Visual Question Answering—0
Reading Comprehension as Natural Language Inference: A Semantic Analysis—0
When in Doubt, Ask: Generating Answerable and Unanswerable Questions, UnsupervisedCode0
Tell Me How to Ask Again: Question Data Augmentation with Controllable Rewriting in Continuous SpaceCode0
CAPTION: Correction by Analyses, POS-Tagging and Interpretation of Objects using only Nouns—0
ARES: A Reading Comprehension Ensembling Service—0
Mongolian Questions Classification Based on Mulit-Head Attention—0
Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling—0
LiveQA: A Question Answering Dataset over Sports LiveCode0
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
ISAAQ -- Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention—0
CoSaTa: A Constraint Satisfaction Solver and Interpreted Language for Semi-Structured Tables of SentencesCode0
A Technical Question Answering System with Transfer LearningCode0
How State-Of-The-Art Models Can Deal With Long-Form Question Answering—0
Combining Impression Feature Representation for Multi-turn Conversational Question Answering—0
Case-Based Abductive Natural Language Inference—0
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension—0
Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks—0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension—0
Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network—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