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 9301–9350 of 10817 papers

TitleStatusHype
Generating titles for millions of browse pages on an e-Commerce site—0
Deception Detection in News Reports in the Russian Language: Lexics and Discourse—0
From Shakespeare to Twitter: What are Language Styles all about?—0
deepCybErNet at EmoInt-2017: Deep Emotion Intensities in Tweets—0
Multimedia Summary Generation from Online Conversations: Current Approaches and Future Directions—0
Constructing an Alias List for Named Entities during an Event—0
Coarse-to-Fine Attention Models for Document Summarization—0
Using Question-Answering Techniques to Implement a Knowledge-Driven Argument Mining Approach—0
Rhetorical relations markers in Russian RST Treebank—0
Sheffield MultiMT: Using Object Posterior Predictions for Multimodal Machine Translation—0
Spatial Language Understanding with Multimodal Graphs using Declarative Learning based Programming—0
Story Comprehension for Predicting What Happens Next—0
Sparsity and Noise: Where Knowledge Graph Embeddings Fall ShortCode0
Neural Semantic Parsing with Type Constraints for Semi-Structured TablesCode0
From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems—0
Learning Contextually Informed Representations for Linear-Time Discourse Parsing—0
No Need to Pay Attention: Simple Recurrent Neural Networks Work!—0
CROWD-IN-THE-LOOP: A Hybrid Approach for Annotating Semantic Roles—0
Accurate Supervised and Semi-Supervised Machine Reading for Long Documents—0
Neural Net Models of Open-domain Discourse Coherence—0
QUINT: Interpretable Question Answering over Knowledge Bases—0
Joint Embeddings of Chinese Words, Characters, and Fine-grained Subcharacter Components—0
Ranking Kernels for Structures and Embeddings: A Hybrid Preference and Classification Model—0
Latent Space Embedding for Retrieval in Question-Answer Archives—0
A Question Answering Approach for Emotion Cause Extraction—0
Beyond Sentential Semantic Parsing: Tackling the Math SAT with a Cascade of Tree Transducers—0
Exploiting Morphological Regularities in Distributional Word Representations—0
Question Generation for Question Answering—0
Inter-Weighted Alignment Network for Sentence Pair Modeling—0
Classification of telicity using cross-linguistic annotation projectionCode0
Dimensions of Interpersonal Relationships: Corpus and Experiments—0
Recovering Question Answering Errors via Query Revision—0
Identifying the Provision of Choices in Privacy Policy Text—0
Importance sampling for unbiased on-demand evaluation of knowledge base population—0
An End-to-End Deep Framework for Answer Triggering with a Novel Group-Level Objective—0
Context-Aware Representations for Knowledge Base Relation ExtractionCode0
MinIE: Minimizing Facts in Open Information ExtractionCode0
A Joint Sequential and Relational Model for Frame-Semantic Parsing—0
A Short Survey on Taxonomy Learning from Text Corpora: Issues, Resources and Recent Advances—0
Order-Planning Neural Text Generation From Structured DataCode0
R^3: Reinforced Reader-Ranker for Open-Domain Question AnsweringCode0
TableQA: Question Answering on Tabular Data—0
Learning Fine-Grained Knowledge about Contingent Relations between Everyday Events—0
Subspace Approximation for Approximate Nearest Neighbor Search in NLP—0
Learning to Paraphrase for Question Answering—0
A Question Answering Approach to Emotion Cause Extraction—0
Natural Language Processing: State of The Art, Current Trends and ChallengesCode0
VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic SegmentationCode0
Mining Deep And-Or Object Structures via Cost-Sensitive Question-Answer-Based Active Annotations—0
Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual 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