arXiv:1801.06830
Neural Multi-task Learning in Automated Assessment
원문 초록
Grammatical error detection and automated essay scoring are two tasks in the area of automated assessment. Traditionally these tasks have been treated independently with different machine learning models and features used for each task. In this paper, we develop a multi-task neural network model that jointly optimises for both tasks, and in particular we show that neural automated essay scoring can be significantly improved. We show that while the essay score provides little evidence to inform grammatical error detection, the essay score is highly influenced by error detection.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
ARWI: Arabic Write and Improve
Robust-Multi-Task Gradient Boosting
SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation
SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning
CALM: Consensus-Aware Localized Merging for Multi-Task Learning
Training-free LLM Merging for Multi-task Learning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.