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

Showing 27312740 of 10817 papers

TitleStatusHype
Bias patterns in the application of LLMs for clinical decision support: A comprehensive studyCode0
Learning to Generalize for Cross-domain QACode0
bgGLUE: A Bulgarian General Language Understanding Evaluation BenchmarkCode0
Learning to Follow Object-Centric Image Editing Instructions FaithfullyCode0
An Open Source Contractual Language Understanding Application Using Machine LearningCode0
Learning to Deceive Knowledge Graph Augmented Models via Targeted PerturbationCode0
Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question AnsweringCode0
Learning to Compose Neural Networks for Question AnsweringCode0
An Ontology-Enabled Approach For User-Centered and Knowledge-Enabled Explanations of AI SystemsCode0
Learning to Perform Role-Filler Binding with Schematic KnowledgeCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94Unverified
2FPNet (ensemble)EM90.87Unverified
3IE-NetV2 (ensemble)EM90.86Unverified
4SA-Net on Albert (ensemble)EM90.72Unverified
5SA-Net-V2 (ensemble)EM90.68Unverified
6FPNet (ensemble)EM90.6Unverified
7Retro-Reader (ensemble)EM90.58Unverified
8EntitySpanFocusV2 (ensemble)EM90.52Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49Unverified
10EntitySpanFocus+AT (ensemble)EM90.45Unverified