@inproceedings{kamath-etal-2024-generating-hotel,
title = "Generating Hotel Highlights from Unstructured Text using {LLM}s",
author = "Kamath, Srinivas Ramesh and
Same, Fahime and
Mahamood, Saad",
editor = "Mahamood, Saad and
Minh, Nguyen Le and
Ippolito, Daphne",
booktitle = "Proceedings of the 17th International Natural Language Generation Conference",
month = sep,
year = "2024",
address = "Tokyo, Japan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.inlg-main.23",
pages = "280--288",
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.",
}
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%0 Conference Proceedings
%T Generating Hotel Highlights from Unstructured Text using LLMs
%A Kamath, Srinivas Ramesh
%A Same, Fahime
%A Mahamood, Saad
%Y Mahamood, Saad
%Y Minh, Nguyen Le
%Y Ippolito, Daphne
%S Proceedings of the 17th International Natural Language Generation Conference
%D 2024
%8 September
%I Association for Computational Linguistics
%C Tokyo, Japan
%F kamath-etal-2024-generating-hotel
%X 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.
%U https://aclanthology.org/2024.inlg-main.23
%P 280-288
Markdown (Informal)
[Generating Hotel Highlights from Unstructured Text using LLMs](https://aclanthology.org/2024.inlg-main.23) (Kamath et al., INLG 2024)
ACL