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 6651–6675 of 10817 papers

TitleStatusHype
Language bias in Visual Question Answering: A Survey and Taxonomy—0
Language-aware Visual Semantic Distillation for Video Question Answering—0
Designing a Robust Radiology Report Generation System—0
Multi-Modal Fusion Transformer for Visual Question Answering in Remote Sensing—0
Backward and Forward Language Modeling for Constrained Sentence Generation—0
Langforia: Language Pipelines for Annotating Large Collections of Documents—0
LaMP-QA: A Benchmark for Personalized Long-form Question Answering—0
Multimodal grid features and cell pointers for Scene Text Visual Question Answering—0
Designing a Communication Bridge between Communities: Participatory Design for a Question-Answering AI Agent—0
Back to Basics for Monolingual Alignment: Exploiting Word Similarity and Contextual Evidence—0
LaFFi: Leveraging Hybrid Natural Language Feedback for Fine-tuning Language Models—0
Multimodal Intelligence: Representation Learning, Information Fusion, and Applications—0
Label Embedding for Zero-shot Fine-grained Named Entity Typing—0
Multi-modality Latent Interaction Network for Visual Question Answering—0
Design and Development of Rule-based open-domain Question-Answering System on SQuAD v2.0 Dataset—0
Backpropagation-Free Multi-modal On-Device Model Adaptation via Cloud-Device Collaboration—0
Multimodal Learning and Reasoning for Visual Question Answering—0
Scene Graph Reasoning with Prior Visual Relationship for Visual Question Answering—0
Multimodal Machine Learning: Integrating Language, Vision and Speech—0
Multimodal Multi-Hop Question Answering Through a Conversation Between Tools and Efficiently Finetuned Large Language Models—0
Multimodal Multihop Source Retrieval for Web Question Answering—0
Multimodal Neural Graph Memory Networks for Visual Question Answering—0
Multimodal Neural Machine Translation for Low-resource Language Pairs using Synthetic Data—0
A Neural Approach to KGQA via SPARQL Silhouette Generation—0
Adversarial and Safely Scaled Question Generation—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