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 14911500 of 10817 papers

TitleStatusHype
Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language Models as AgentsCode1
Learning Neural Models for Natural Language Processing in the Face of Distributional ShiftCode1
Designing a Minimal Retrieve-and-Read System for Open-Domain Question AnsweringCode1
Bidirectional Attentive Memory Networks for Question Answering over Knowledge BasesCode1
CodeQueries: A Dataset of Semantic Queries over CodeCode1
Learning to Answer Visual Questions from Web VideosCode1
Big Bird: Transformers for Longer SequencesCode1
Learning to Attribute with AttentionCode1
A Symmetric Dual Encoding Dense Retrieval Framework for Knowledge-Intensive Visual Question AnsweringCode1
Detecting Hate Speech in Multi-modal MemesCode1
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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