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 29612970 of 10817 papers

TitleStatusHype
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language ModelsCode0
Integrating Multimodal Information in Large Pretrained TransformersCode0
Latent Alignment of Procedural Concepts in Multimodal RecipesCode0
LayoutLMv3: Pre-training for Document AI with Unified Text and Image MaskingCode0
Learning Action-Effect Dynamics for Hypothetical Vision-Language Reasoning TaskCode0
DragonVerseQA: Open-Domain Long-Form Context-Aware Question-AnsweringCode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
Did the Model Understand the Question?Code0
Large Models in Dialogue for Active Perception and Anomaly DetectionCode0
Dice Loss for Data-imbalanced NLP TasksCode0
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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