Toward Related Work Generation with Structure and Novelty Statement
Kazuya Nishimura, Kuniaki Saito, Tosho Hirasawa, Yoshitaka Ushiku
Abstract
To help readers understand the novelty and the research context, an excellent related work section is structured (i.e., the section consists of paragraphs determined by categorizing papers into several topics) and includes descriptions of novelty. However, previous studies viewed related work generation as multi-document summarization, and the structure and novelty statement are ignored in such studies. In this paper, we redefine the related work generation task as summarization with structure (i.e., multiple paragraphs with citation) and novelty statement. For this task, we propose a quality-oriented dataset and evaluation metrics. Experiments evaluated the state-of-the-art language models on our tasks, and we confirmed the issues with the current models and the validity of the evaluation indicators.- Anthology ID:
- 2024.sdp-1.5
- Volume:
- Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Tirthankar Ghosal, Amanpreet Singh, Anita Waard, Philipp Mayr, Aakanksha Naik, Orion Weller, Yoonjoo Lee, Shannon Shen, Yanxia Qin
- Venues:
- sdp | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 38–57
- Language:
- URL:
- https://aclanthology.org/2024.sdp-1.5
- DOI:
- Cite (ACL):
- Kazuya Nishimura, Kuniaki Saito, Tosho Hirasawa, and Yoshitaka Ushiku. 2024. Toward Related Work Generation with Structure and Novelty Statement. In Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024), pages 38–57, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Toward Related Work Generation with Structure and Novelty Statement (Nishimura et al., sdp-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.sdp-1.5.pdf