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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5401–5450 of 10817 papers

TitleStatusHype
SemEval-2022 Task 9: R2VQ – Competence-based Multimodal Question Answering—0
MultiSpanQA: A Dataset for Multi-Span Question AnsweringCode1
Raccoons at SemEval-2022 Task 11: Leveraging Concatenated Word Embeddings for Named Entity Recognition—0
Permutation Invariant Strategy Using Transformer Encoders for Table Understanding—0
Ask Me Anything in Your Native Language—0
Zero-shot cross-lingual open domain question answering—0
Conditional Generation with a Question-Answering Blueprint—0
American == White in Multimodal Language-and-Image AI—0
Modern Question Answering Datasets and Benchmarks: A Survey—0
A Unified End-to-End Retriever-Reader Framework for Knowledge-based VQACode1
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks—0
What Can Secondary Predictions Tell Us? An Exploration on Question-Answering with SQuAD-v2.0Code0
EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answering—0
On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based MethodCode0
Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product Attribute Extraction—0
CC-Riddle: A Question Answering Dataset of Chinese Character RiddlesCode1
Kwame for Science: An AI Teaching Assistant Based on Sentence-BERT for Science Education in West Africa—0
Consistency-preserving Visual Question Answering in Medical ImagingCode1
Contextual embedding and model weighting by fusing domain knowledge on Biomedical Question AnsweringCode0
From Shallow to Deep: Compositional Reasoning over Graphs for Visual Question Answering—0
Evaluation of Semantic Answer Similarity MetricsCode0
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight ImportanceCode1
QAGAN: Adversarial Approach To Learning Domain Invariant Language FeaturesCode0
OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking ExperienceCode0
Surgical-VQA: Visual Question Answering in Surgical Scenes using TransformerCode1
VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason ObjectivesCode0
Tell Me the Evidence? Dual Visual-Linguistic Interaction for Answer Grounding—0
Grounding Answers for Visual Questions Asked by Visually Impaired People—0
SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts—0
EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RLCode1
0/1 Deep Neural Networks via Block Coordinate Descent—0
A Numerical Reasoning Question Answering System with Fine-grained Retriever and the Ensemble of Multiple Generators for FinQA—0
Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks—0
An Open-Domain QA System for e-Governance—0
Interpretable AMR-Based Question Decomposition for Multi-hop Question Answering—0
Zero-Shot Video Question Answering via Frozen Bidirectional Language ModelsCode1
MixGen: A New Multi-Modal Data AugmentationCode1
Coarse-to-Fine Vision-Language Pre-training with Fusion in the BackboneCode1
Test-Time Adaptation for Visual Document Understanding—0
CHQ-Summ: A Dataset for Consumer Healthcare Question SummarizationCode0
LAVENDER: Unifying Video-Language Understanding as Masked Language ModelingCode1
Task Transfer and Domain Adaptation for Zero-Shot Question AnsweringCode0
Memory-Based Model Editing at ScaleCode1
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization—0
Less Is More: Linear Layers on CLIP Features as Powerful VizWiz Model—0
Ask to Know More: Generating Counterfactual Explanations for Fake ClaimsCode1
Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems—0
Explanation as Question Answering based on a Task Model of the Agent's Design—0
Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval—0
Revealing Single Frame Bias for Video-and-Language LearningCode2
Show:102550
← PrevPage 109 of 217Next →
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