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 9226–9250 of 10817 papers

TitleStatusHype
Improving Cross-Modal Understanding in Visual Dialog via Contrastive Learning—0
Improving Data Augmentation for Robust Visual Question Answering with Effective Curriculum Learning—0
Improving Data Augmentation in Low-resource Question Answering with Active Learning in Multiple Stages—0
Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control—0
Improving Event Coreference Resolution by Modeling Correlations between Event Coreference Chains and Document Topic Structures—0
Detecting Ongoing Events Using Contextual Word and Sentence Embeddings—0
Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging—0
Improving Generated and Retrieved Knowledge Combination Through Zero-shot Generation—0
Improving Implicit Discourse Relation Recognition with Discourse-specific Word Embeddings—0
Improving Implicit Discourse Relation Recognition Through Feature Set Optimization—0
Improving Knowledge Base Construction from Robust Infobox Extraction—0
Improving Large-Scale Fact-Checking using Decomposable Attention Models and Lexical Tagging—0
Improving Legal Information Retrieval by Distributional Composition with Term Order Probabilities—0
Improving Lexical Embeddings for Robust Question Answering—0
Improving LLM First-Token Predictions in Multiple-Choice Question Answering via Prefilling Attack—0
Improving Long Text Understanding with Knowledge Distilled from Summarization Model—0
Improving mitosis detection on histopathology images using large vision-language models—0
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain—0
Improving Numerical Reasoning Skills in the Modular Approach for Complex Question Answering on Text—0
Improving Opinion-based Question Answering Systems Through Label Error Detection and Overwrite—0
Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs—0
Improving Query Graph Generation for Complex Question Answering over Knowledge Base—0
Improving Question Answering by Commonsense-Based Pre-Training—0
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation—0
Improving Question Answering over Knowledge Graphs Using Graph Summarization—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