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 21712180 of 10817 papers

TitleStatusHype
Explaining NLP Models via Minimal Contrastive Editing (MiCE)Code1
Explaining Question Answering Models through Text GenerationCode1
Exploiting Abstract Meaning Representation for Open-Domain Question AnsweringCode1
DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoningCode1
Designing a Minimal Retrieve-and-Read System for Open-Domain Question AnsweringCode1
CogMG: Collaborative Augmentation Between Large Language Model and Knowledge GraphCode1
DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data ProcessingCode1
ECONET: Effective Continual Pretraining of Language Models for Event Temporal ReasoningCode1
Exposing Shallow Heuristics of Relation Extraction Models with Challenge DataCode1
Learning Video Context as Interleaved Multimodal SequencesCode1
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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