Multi-Stage Pre-training for Automated Chinese Essay Scoring
Wei Song, Kai Zhang, Ruiji Fu, Lizhen Liu, Ting Liu, Miaomiao Cheng
Abstract
This paper proposes a pre-training based automated Chinese essay scoring method. The method involves three components: weakly supervised pre-training, supervised cross- prompt fine-tuning and supervised target- prompt fine-tuning. An essay scorer is first pre- trained on a large essay dataset covering diverse topics and with coarse ratings, i.e., good and poor, which are used as a kind of weak supervision. The pre-trained essay scorer would be further fine-tuned on previously rated es- says from existing prompts, which have the same score range with the target prompt and provide extra supervision. At last, the scorer is fine-tuned on the target-prompt training data. The evaluation on four prompts shows that this method can improve a state-of-the-art neural essay scorer in terms of effectiveness and domain adaptation ability, while in-depth analysis also reveals its limitations..- Anthology ID:
- 2020.emnlp-main.546
- Volume:
- Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 6723–6733
- Language:
- URL:
- https://aclanthology.org/2020.emnlp-main.546
- DOI:
- 10.18653/v1/2020.emnlp-main.546
- Cite (ACL):
- Wei Song, Kai Zhang, Ruiji Fu, Lizhen Liu, Ting Liu, and Miaomiao Cheng. 2020. Multi-Stage Pre-training for Automated Chinese Essay Scoring. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6723–6733, Online. Association for Computational Linguistics.
- Cite (Informal):
- Multi-Stage Pre-training for Automated Chinese Essay Scoring (Song et al., EMNLP 2020)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2020.emnlp-main.546.pdf