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 7201–7225 of 10817 papers

TitleStatusHype
Biomedical Event Extraction as Multi-turn Question AnsweringCode0
DSNDM: Deep Siamese Neural Discourse Model with Attention for Text Pairs Categorization and Ranking—0
On the effectiveness of small, discriminatively pre-trained language representation models for biomedical text mining—0
Multi-Task Learning using Dynamic Task Weighting for Conversational Question Answering—0
Deeply Embedded Knowledge Representation & Reasoning For Natural Language Question Answering: A Practitioner’s Perspective—0
Don’t Read Too Much Into It: Adaptive Computation for Open-Domain Question Answering—0
Enhancing Question Answering by Injecting Ontological Knowledge through Regularization—0
Do Transformers Dream of Inference, or Can Pretrained Generative Models Learn Implicit Inferential Rules?—0
How You Ask Matters: The Effect of Paraphrastic Questions to BERT Performance on a Clinical SQuAD Dataset—0
Zero-Shot Rationalization by Multi-Task Transfer Learning from Question AnsweringCode0
Open Domain Question Answering based on Text Enhanced Knowledge Graph with Hyperedge Infusion—0
Can Pre-training help VQA with Lexical Variations?—0
Towards Zero-Shot Conditional Summarization with Adaptive Multi-Task Fine-TuningCode0
Regularization of Distinct Strategies for Unsupervised Question GenerationCode0
Representation, Learning and Reasoning on Spatial Language for Downstream NLP Tasks—0
Question Answering with Long Multiple-Span AnswersCode1
The RELX Dataset and Matching the Multilingual Blanks for Cross-Lingual Relation ClassificationCode1
Event Extraction as Multi-turn Question Answering—0
ConceptBert: Concept-Aware Representation for Visual Question AnsweringCode1
Coarse-to-Fine Query Focused Multi-Document Summarization—0
Unsupervised Adaptation of Question Answering Systems via Generative Self-training—0
CapWAP: Image Captioning with a Purpose—0
Event Extraction as Machine Reading Comprehension—0
STL-CQA: Structure-based Transformers with Localization and Encoding for Chart Question Answering—0
PALM: Pre-training an Autoencoding\&Autoregressive Language Model for Context-conditioned Generation—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