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 6751–6775 of 10817 papers

TitleStatusHype
Multivalent Entailment Graphs for Question Answering—0
Multi-VALUE: A Framework for Cross-Dialectal English NLP—0
Multi-View Approach to Suggest Moderation Actions in Community Question Answering Sites—0
Multi-view Content-aware Indexing for Long Document Retrieval—0
Dependency Parsing for Weibo: An Efficient Probabilistic Logic Programming Approach—0
KSAnswer: Question-answering System of Kangwon National University and Sogang University in the 2016 BioASQ Challenge—0
Dependency Extraction for Knowledge-based Domain Classification—0
An Ensemble Approach to Question Classification: Integrating Electra Transformer, GloVe, and LSTM—0
KOSMOS-2.5: A Multimodal Literate Model—0
MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text—0
MuRAR: A Simple and Effective Multimodal Retrieval and Answer Refinement Framework for Multimodal Question Answering—0
KOSAC: A Full-Fledged Korean Sentiment Analysis Corpus—0
Dependency-Based Open Information Extraction—0
KorQuAD1.0: Korean QA Dataset for Machine Reading Comprehension—0
MUST-VQA: MUltilingual Scene-text VQA—0
KorMedMCQA: Multi-Choice Question Answering Benchmark for Korean Healthcare Professional Licensing Examinations—0
Korean TimeBank Including Relative Temporal Information—0
A Zero-Shot Claim Detection Framework Using Question Answering—0
An English-Portuguese parallel corpus of questions: translation guidelines and application in SMT—0
A Compare-Aggregate Model with Latent Clustering for Answer Selection—0
Kongzi: A Historical Large Language Model with Fact Enhancement—0
KoGNER: A Novel Framework for Knowledge Graph Distillation on Biomedical Named Entity Recognition—0
A Zero-shot and Few-shot Study of Instruction-Finetuned Large Language Models Applied to Clinical and Biomedical Tasks—0
KodeXv0.1: A Family of State-of-the-Art Financial Large Language Models—0
KoBigBird-large: Transformation of Transformer for Korean Language Understanding—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