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 7826–7850 of 10817 papers

TitleStatusHype
Question Answering over Freebase with Multi-Column Convolutional Neural Networks—0
CompMix: A Benchmark for Heterogeneous Question Answering—0
Question Answering over Knowledge Base using Factual Memory Networks—0
Question Answering over Knowledge Base using Language Model Embeddings—0
Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Information—0
Question Answering over Knowledge Graphs via Structural Query Patterns—0
Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linking—0
Question Answering over Linked Data Using First-order Logic—0
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization—0
Question Answering Over Spatio-Temporal Knowledge Graph—0
GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation—0
Question-Answering (QA) Model for a Personalized Learning Assistant for Arabic Language—0
Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matrices—0
Fine-tuning Smaller Language Models for Question Answering over Financial Documents—0
Question-Answering System for Bangla: Fine-tuning BERT-Bangla for a Closed Domain—0
Fine-tuning Strategies for Domain Specific Question Answering under Low Annotation Budget Constraints—0
Question Answering Systems Approaches and Challenges—0
Question answering systems for health professionals at the point of care -- a systematic review—0
Question Answering System using Multiple Information Source and Open Type Answer Merge—0
Fine-tuning Transformer-based Encoder for Turkish Language Understanding Tasks—0
Question answering using deep learning in low resource Indian language Marathi—0
Question Answering Using Enhanced Lexical Semantic Models—0
Question Answering Using Hierarchical Attention on Top of BERT Features—0
Question Answering via Integer Programming over Semi-Structured Knowledge—0
GPT-4V Explorations: Mining Autonomous Driving—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