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 5851–5875 of 10817 papers

TitleStatusHype
On-the-fly Denoising for Data Augmentation in Natural Language UnderstandingCode0
(QA)^2: Question Answering with Questionable AssumptionsCode0
Defending Against Disinformation Attacks in Open-Domain Question AnsweringCode0
To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering—0
SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks—0
MULTI3NLU++: A Multilingual, Multi-Intent, Multi-Domain Dataset for Natural Language Understanding in Task-Oriented Dialogue—0
Tokenization Consistency Matters for Generative Models on Extractive NLP TasksCode0
MetaCLUE: Towards Comprehensive Visual Metaphors Research—0
KNIFE: Distilling Reasoning Knowledge From Free-Text Rationales—0
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension—0
Rethinking Label Smoothing on Multi-hop Question AnsweringCode0
Query Enhanced Knowledge-Intensive Conversation via Unsupervised Joint ModelingCode0
Source-Free Domain Adaptation for Question Answering with Masked Self-trainingCode0
Task Preferences across Languages on Community Question Answering Platforms—0
Towards leveraging latent knowledge and Dialogue context for real-world conversational question answering—0
AugTriever: Unsupervised Dense Retrieval and Domain Adaptation by Scalable Data AugmentationCode0
PolQA: Polish Question Answering Dataset—0
Natural Language Processing in Customer Service: A Systematic Review—0
SceneGATE: Scene-Graph based co-Attention networks for TExt visual question answering—0
Plansformer: Generating Symbolic Plans using Transformers—0
CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models—0
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference—0
Best-Answer Prediction in Q&A Sites Using User Information—0
Multi-VALUE: A Framework for Cross-Dialectal English NLP—0
CLIPPO: Image-and-Language Understanding from Pixels Only—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