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
Hi, how can I help you?: Automating enterprise IT support help desks—0
Context-Efficient Retrieval with Factual Decomposition—0
High Quality Dependency Selection from Automatic Parses—0
Multi-Modal Fusion Transformer for Visual Question Answering in Remote Sensing—0
A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends—0
A Survey of Vision-Language Pre-training from the Lens of Multimodal Machine Translation—0
Multimodal Graph Transformer for Multimodal Question Answering—0
Multimodal grid features and cell pointers for Scene Text Visual Question Answering—0
Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models—0
Multi-Modal Instruction-Tuning Small-Scale Language-and-Vision Assistant for Semiconductor Electron Micrograph Analysis—0
Multimodal Integration of Human-Like Attention in Visual Question Answering—0
Multimodal Intelligence: Representation Learning, Information Fusion, and Applications—0
Accommodate Knowledge Conflicts in Retrieval-augmented LLMs: Towards Reliable Response Generation in the Wild—0
Multi-modality Latent Interaction Network for Visual Question Answering—0
Higher-order Lexical Semantic Models for Non-factoid Answer Reranking—0
Enhancing Post-Hoc Attributions in Long Document Comprehension via Coarse Grained Answer Decomposition—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
High Accuracy Rule-based Question Classification using Question Syntax and Semantics—0
Context-Dependent Semantic Parsing for Temporal Relation Extraction—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