Abstract
We describe our implementation and evaluation of the Hotel Highlights system which has been deployed live by trivago. This system leverages a large language model (LLM) to generate a set of highlights from accommodation descriptions and reviews, enabling travellers to quickly understand its unique aspects. In this paper, we discuss our motivation for building this system and the human evaluation we conducted, comparing the generated highlights against the source input to assess the degree of hallucinations and/or contradictions present. Finally, we outline the lessons learned and the improvements needed.- Anthology ID:
- 2024.inlg-main.23
- Volume:
- Proceedings of the 17th International Natural Language Generation Conference
- Month:
- September
- Year:
- 2024
- Address:
- Tokyo, Japan
- Editors:
- Saad Mahamood, Nguyen Le Minh, Daphne Ippolito
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 280–288
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2024.inlg-main.23/
- DOI:
- Cite (ACL):
- Srinivas Ramesh Kamath, Fahime Same, and Saad Mahamood. 2024. Generating Hotel Highlights from Unstructured Text using LLMs. In Proceedings of the 17th International Natural Language Generation Conference, pages 280–288, Tokyo, Japan. Association for Computational Linguistics.
- Cite (Informal):
- Generating Hotel Highlights from Unstructured Text using LLMs (Kamath et al., INLG 2024)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2024.inlg-main.23.pdf