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 6901–6950 of 10817 papers

TitleStatusHype
Contextual Dropout: An Efficient Sample-Dependent Dropout ModuleCode0
AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph DocumentsCode1
Graph-Based Tri-Attention Network for Answer Ranking in CQA—0
Advances in Multi-turn Dialogue Comprehension: A Survey—0
Visual Question Answering: which investigated applications?Code0
Weakly-Supervised Open-Retrieval Conversational Question AnsweringCode0
A Linguistic Study on Relevance Modeling in Information Retrieval—0
Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues—0
Logic Embeddings for Complex Query AnsweringCode1
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections—0
Natural Language Video Localization: A Revisit in Span-based Question Answering Framework—0
PharmKE: Knowledge Extraction Platform for Pharmaceutical Texts using Transfer Learning—0
IIE-NLP-Eyas at SemEval-2021 Task 4: Enhancing PLM for ReCAM with Special Tokens, Re-Ranking, Siamese Encoders and Back Translation—0
Multichannel LSTM-CNN for Telugu Technical Domain Identification—0
OneStop QAMaker: Extract Question-Answer Pairs from Text in a One-Stop Approach—0
A Relational Tsetlin Machine with Applications to Natural Language Understanding—0
Learning Compositional Representation for Few-shot Visual Question Answering—0
Multilingual Answer Sentence Reranking via Automatically Translated Data—0
Less is More: Pre-train a Strong Text Encoder for Dense Retrieval Using a Weak DecoderCode1
SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question AnsweringCode1
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual ConceptsCode1
NoiseQA: Challenge Set Evaluation for User-Centric Question AnsweringCode1
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies—0
User-Inspired Posterior Network for Recommendation Reason Generation—0
KnowledgeCheckR: Intelligent Techniques for Counteracting Forgetting—0
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations—0
PAQ: 65 Million Probably-Asked Questions and What You Can Do With ThemCode1
A Large Batch Optimizer Reality Check: Traditional, Generic Optimizers Suffice Across Batch Sizes—0
Optimizing Inference Performance of Transformers on CPUs—0
Less is More: ClipBERT for Video-and-Language Learning via Sparse SamplingCode1
Biomedical Question Answering: A Survey of Approaches and Challenges—0
Information Extraction From Co-Occurring Similar Entities—0
Decontextualization: Making Sentences Stand-Alone—0
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-AttentionCode1
Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering—0
Model Agnostic Answer Reranking System for Adversarial Question Answering—0
Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge—0
Unifying Vision-and-Language Tasks via Text GenerationCode1
ChainCQG: Flow-Aware Conversational Question GenerationCode1
Answer Questions with Right Image Regions: A Visual Attention Regularization ApproachCode0
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics—0
Do Question Answering Modeling Improvements Hold Across Benchmarks?—0
Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision Users—0
Self-Teaching Machines to Read and Comprehend with Large-Scale Multi-Subject Question-Answering Data—0
Commonsense Knowledge Mining from Term DefinitionsCode0
[Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base EmbeddingsCode1
An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games—0
Modeling Context in Answer Sentence Selection Systems on a Latency Budget—0
VX2TEXT: End-to-End Learning of Video-Based Text Generation From Multimodal Inputs—0
Weakly Supervised Neuro-Symbolic Module Networks for Numerical Reasoning—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