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 8401–8450 of 10817 papers

TitleStatusHype
ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question AnsweringCode0
Towards Scalable and Reliable Capsule Networks for Challenging NLP ApplicationsCode0
Cross-Lingual Training for Automatic Question GenerationCode0
A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text MiningCode0
KERMIT: Generative Insertion-Based Modeling for Sequences—0
Episodic Memory in Lifelong Language LearningCode0
Generating Question Relevant Captions to Aid Visual Question Answering—0
Question Answering as an Automatic Evaluation Metric for News Article SummarizationCode0
CODAH: An Adversarially-Authored Question Answering Dataset for Common SenseCode0
CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering—0
FreebaseQA: A New Factoid QA Data Set Matching Trivia-Style Question-Answer Pairs with FreebaseCode0
Alignment over Heterogeneous Embeddings for Question AnsweringCode0
SemEval-2019 Task 10: Math Question AnsweringCode0
Fermi at SemEval-2019 Task 8: An elementary but effective approach to Question Discernment in Community QA Forums—0
Sequential Attention with Keyword Mask Model for Community-based Question AnsweringCode0
ProblemSolver at SemEval-2019 Task 10: Sequence-to-Sequence Learning and Expression Trees—0
Predicting Helpful Posts in Open-Ended Discussion Forums: A Neural Architecture—0
On Knowledge distillation from complex networks for response prediction—0
AiFu at SemEval-2019 Task 10: A Symbolic and Sub-symbolic Integrated System for SAT Math Question Answering—0
Natural Questions: a Benchmark for Question Answering Research—0
Promotion of Answer Value Measurement with Domain Effects in Community Question Answering Systems—0
Enhancing Key-Value Memory Neural Networks for Knowledge Based Question Answering—0
DiffQue: Estimating Relative Difficulty of Questions in Community Question Answering ServicesCode0
BLCU\_NLP at SemEval-2019 Task 8: A Contextual Knowledge-enhanced GPT Model for Fact Checking—0
Dynamic Fusion With Intra- and Inter-Modality Attention Flow for Visual Question Answering—0
DUTH at SemEval-2019 Task 8: Part-Of-Speech Features for Question Classification—0
DOMLIN at SemEval-2019 Task 8: Automated Fact Checking exploiting Ratings in Community Question Answering Forums—0
Litigation Analytics: Extracting and querying motions and orders from US federal courts—0
SolomonLab at SemEval-2019 Task 8: Question Factuality and Answer Veracity Prediction in Community Forums—0
Annotating and Characterizing Clinical Sentences with Explicit Why-QA CuesCode0
Is It Dish Washer Safe? Automatically Answering ``Yes/No'' Questions Using Customer Reviews—0
Automated assessment of knowledge hierarchy evolution: comparing directed acyclic graphs—0
AUTOHOME-ORCA at SemEval-2019 Task 8: Application of BERT for Fact-Checking in Community Forums—0
Social-IQ: A Question Answering Benchmark for Artificial Social Intelligence—0
Improving Knowledge Base Construction from Robust Infobox Extraction—0
Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting—0
ImageTTR: Grounding Type Theory with Records in Image Classification for Visual Question Answering—0
Grounded Word Sense Translation—0
TueFact at SemEval 2019 Task 8: Fact checking in community question answering forums: context matters—0
ColumbiaNLP at SemEval-2019 Task 8: The Answer is Language Model Fine-tuning—0
Out of Sight But Not Out of Mind: An Answer Set Programming Based Online Abduction Framework for Visual Sensemaking in Autonomous Driving—0
A Simple but Effective Method to Incorporate Multi-turn Context with BERT for Conversational Machine Comprehension—0
Threshold-Based Retrieval and Textual Entailment Detection on Legal Bar Exam Questions—0
What Can Neural Networks Reason About?Code0
A Compare-Aggregate Model with Latent Clustering for Answer Selection—0
A Generalized Framework of Sequence Generation with Application to Undirected Sequence ModelsCode0
Large Scale Question Paraphrase Retrieval with Smoothed Deep Metric Learning—0
Vision-to-Language Tasks Based on Attributes and Attention Mechanism—0
TMLab SRPOL at SemEval-2019 Task 8: Fact Checking in Community Question Answering Forums—0
Leveraging Medical Visual Question Answering with Supporting Facts—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