Abstract
This paper is submitted for SemEval-2027 task 7: Enhancing the Model’s Understanding and Generation of Numerical Values. The dataset for this task is NQuAD, which requires us to select the most suitable option number from four numerical options to fill in the blank in a news article based on the context. Based on the BertForMultipleChoice model, we proposed two new models, MC BERT and SSC BERT, and improved the model’s numerical understanding ability by pre-training the model on numerical comparison tasks. Ultimately, our best-performing model achieved an accuracy rate of 79.40%, which is 9.45% higher than the accuracy rate of NEMo.- Anthology ID:
- 2024.semeval-1.76
- Volume:
- Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 497–502
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.76
- DOI:
- 10.18653/v1/2024.semeval-1.76
- Cite (ACL):
- Xinyi Liu, Xintong Liu, and Hengyang Lu. 2024. JN666 at SemEval-2024 Task 7: NumEval: Numeral-Aware Language Understanding and Generation. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 497–502, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- JN666 at SemEval-2024 Task 7: NumEval: Numeral-Aware Language Understanding and Generation (Liu et al., SemEval 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.semeval-1.76.pdf