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 8126–8150 of 10817 papers

TitleStatusHype
Results of the fifth edition of the BioASQ Challenge—0
Results of the seventh edition of the BioASQ Challenge—0
GigaPevt: Multimodal Medical Assistant—0
Reinforcement Learning for Optimizing RAG for Domain Chatbots—0
Reinforcement learning for question answering in programming domain using public community scoring as a human feedback—0
Comparative Analysis of CHATGPT and the evolution of language models—0
Reinforcement Learning of Question-Answering Dialogue Policies for Virtual Museum Guides—0
Reinforcement Learning of Two-Issue Negotiation Dialogue Policies—0
Get Your Model Puzzled: Introducing Crossword-Solving as a New NLP Benchmark—0
Legal Question-Answering in the Indian Context: Efficacy, Challenges, and Potential of Modern AI Models—0
Reinforcing Question Answering Agents with Minimalist Policy Gradient Optimization—0
From text to multimodal: a survey of adversarial example generation in question answering systems—0
Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models—0
Relational Graph Convolutional Neural Networks for Multihop Reasoning: A Comparative Study—0
Relational Graph Representation Learning for Open-Domain Question Answering—0
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation—0
Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structure—0
Assessing SRL Frameworks with Automatic Training Data Expansion—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
Get Large Language Models Ready to Speak: A Late-fusion Approach for Speech Generation—0
GermanQuAD and GermanDPR: Improving Non-English Question Answering and Passage Retrieval—0
Compact Tensor Pooling for Visual Question Answering—0
Relation/Entity-Centric Reading Comprehension—0
Relation Classification as Two-way Span-Prediction—0
German FinBERT: A German Pre-trained Language Model—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