ReflectSumm: A Benchmark for Course Reflection Summarization
Yang Zhong, Mohamed Elaraby, Diane Litman, Ahmed Ashraf Butt, Muhsin Menekse
Abstract
This paper introduces ReflectSumm, a novel summarization dataset specifically designed for summarizing students’ reflective writing. The goal of ReflectSumm is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, with potential implications in the opinion summarization domain in general and the educational domain in particular. The dataset encompasses a diverse range of summarization tasks and includes comprehensive metadata, enabling the exploration of various research questions and supporting different applications. To showcase its utility, we conducted extensive evaluations using multiple state-of-the-art baselines. The results provide benchmarks for facilitating further research in this area.- Anthology ID:
- 2024.lrec-main.1207
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 13819–13846
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.1207
- DOI:
- Cite (ACL):
- Yang Zhong, Mohamed Elaraby, Diane Litman, Ahmed Ashraf Butt, and Muhsin Menekse. 2024. ReflectSumm: A Benchmark for Course Reflection Summarization. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 13819–13846, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- ReflectSumm: A Benchmark for Course Reflection Summarization (Zhong et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.lrec-main.1207.pdf