arXiv:1906.01265
공식 코드 · Papers with Code
ChID: A Large-scale Chinese IDiom Dataset for Cloze Test
원문 초록
Cloze-style reading comprehension in Chinese is still limited due to the lack of various corpora. In this paper we propose a large-scale Chinese cloze test dataset ChID, which studies the comprehension of idiom, a unique language phenomenon in Chinese. In this corpus, the idioms in a passage are replaced by blank symbols and the correct answer needs to be chosen from well-designed candidate idioms. We carefully study how the design of candidate idioms and the representation of idioms affect the performance of state-of-the-art models. Results show that the machine accuracy is substantially worse than that of human, indicating a large space for further research.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
NLP and Education: using semantic similarity to evaluate filled gaps in a large-scale Cloze test in the classroom
DeRIS: Decoupling Perception and Cognition for Enhanced Referring Image Segmentation through Loopback Synergy
Chaining Event Spans for Temporal Relation Grounding
CoMuMDR: Code-mixed Multi-modal Multi-domain corpus for Discourse paRsing in conversations
Automatic Generation of Inference Making Questions for Reading Comprehension Assessments
Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.