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 8951–9000 of 10817 papers

TitleStatusHype
Stacked Latent Attention for Multimodal Reasoning—0
Toward Data-Driven Tutorial Question Answering with Deep Learning Conversational Models—0
Telling Stories with Soundtracks: An Empirical Analysis of Music in Film—0
Detecting and Resolving Shell Nouns in German—0
Neural Event Extraction from Movies Description—0
Multi-Sentence Compression with Word Vertex-Labeled Graphs and Integer Linear Programming—0
EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery—0
ELiRF-UPV at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge—0
ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings—0
FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System—0
Coarse Lexical Frame Acquisition at the Syntax--Semantics Interface Using a Latent-Variable PCFG Model—0
CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment—0
Jiangnan at SemEval-2018 Task 11: Deep Neural Network with Attention Method for Machine Comprehension Task—0
IUCM at SemEval-2018 Task 11: Similar-Topic Texts as a Comprehension Knowledge SourceCode0
NLP\_HZ at SemEval-2018 Task 9: a Nearest Neighbor Approach—0
A Multimodal Translation-Based Approach for Knowledge Graph Representation Learning—0
YNU-HPCC at Semeval-2018 Task 11: Using an Attention-based CNN-LSTM for Machine Comprehension using Commonsense Knowledge—0
SemEval-2018 Task 9: Hypernym Discovery—0
Talla at SemEval-2018 Task 7: Hybrid Loss Optimization for Relation Classification using Convolutional Neural Networks—0
SUNNYNLP at SemEval-2018 Task 10: A Support-Vector-Machine-Based Method for Detecting Semantic Difference using Taxonomy and Word Embedding FeaturesCode0
YNU-HPCC at SemEval-2018 Task 12: The Argument Reasoning Comprehension Task Using a Bi-directional LSTM with Attention Model—0
Self-Training for Jointly Learning to Ask and Answer Questions—0
Stacking with Auxiliary Features for Visual Question Answering—0
The Context-Dependent Additive Recurrent Neural Net—0
Syntactically Aware Neural Architectures for Definition Extraction—0
Verb Alternations and Their Impact on Frame Induction—0
SemEval 2018 Task 4: Character Identification on Multiparty Dialogues—0
Supervised Open Information Extraction—0
Visually Guided Spatial Relation Extraction from Text—0
Natural Answer Generation with Heterogeneous Memory—0
Challenging Reading Comprehension on Daily Conversation: Passage Completion on Multiparty Dialog—0
An Evaluation of Image-Based Verb Prediction Models against Human Eye-Tracking Data—0
ArgumenText: Searching for Arguments in Heterogeneous Sources—0
Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences—0
Learning Word Embeddings for Low-Resource Languages by PU Learning—0
Improve Neural Entity Recognition via Multi-Task Data Selection and Constrained Decoding—0
Inducing Temporal Relations from Time Anchor AnnotationCode0
Determining Event Durations: Models and Error Analysis—0
Learning to Collaborate for Question Answering and Asking—0
Pay-Per-Request Deployment of Neural Network Models Using Serverless Architectures—0
Domain-Sensitive Temporal Tagging By Jannik Str\"otgen, Michael Gertz—0
Tree Structured Dirichlet Processes for Hierarchical Morphological SegmentationCode0
Scaling Neural Machine TranslationCode0
Semantic Analysis of (Reflectional) Visual Symmetry: A Human-Centred Computational Model for Declarative Explainability—0
KG^2: Learning to Reason Science Exam Questions with Contextual Knowledge Graph Embeddings—0
Multi-hop Inference for Sentence-level TextGraphs: How Challenging is Meaningfully Combining Information for Science Question Answering?—0
Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information—0
Dependent Gated Reading for Cloze-Style Question Answering—0
Think Visually: Question Answering through Virtual ImageryCode0
R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question AnsweringCode1
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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