P@1: 47.2
Papers with Code · CC BY-SA 4.0
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 )
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Dataset기록된 모델 예시MetricPaperCode
데이터셋
261개논문
Accuracy: 60.0
Accuracy: 66.5
Accuracy: 44.0
Accuracy: 62.7
Accuracy: 76.1
Accuracy: 52.4
라이브러리
Papers with Code 리더보드 row에 연결된 구현 저장소입니다.
하위 태스크
MQ
Mathematical Question Answering
ZV
Zero-Shot Video Question Answer
MC
Multiple Choice Question Answering (MCQA)
OQ
Open-Domain Question Answering
KB
Knowledge Base Question Answering
CQ
Cross-Lingual Question Answering
AS
Answer Selection
SQ
Science Question Answering
TQ
Temporal/Casual QA
GQ
Generative Question Answering
LR
Logical Reasoning Question Answering
CQ
Community Question Answering