arXiv:2104.02756
공식 코드 · Papers with Code
Efficient transfer learning for NLP with ELECTRA
원문 초록
Clark et al. [2020] claims that the ELECTRA approach is highly efficient in NLP performances relative to computation budget. As such, this reproducibility study focus on this claim, summarized by the following question: Can we use ELECTRA to achieve close to SOTA performances for NLP in low-resource settings, in term of compute cost?
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
RaMen: Multi-Strategy Multi-Modal Learning for Bundle Construction
Best Practices for Large-Scale, Pixel-Wise Crop Mapping and Transfer Learning Workflows
Robust-Multi-Task Gradient Boosting
PSAT: Pediatric Segmentation Approaches via Adult Augmentations and Transfer Learning
A Survey on Prompt Tuning
DS@GT at CheckThat! 2025: Detecting Subjectivity via Transfer-Learning and Corrective Data Augmentation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.