Are Large Language Models Good at Utility Judgments?-Reference-Cited by-同舟云学术

Are Large Language Models Good at Utility Judgments?

Published:2024-07-10 Issue: Volume:35 Page:1941-1951
ISSN:
Container-title:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Zhang Hengran¹^ORCID,Zhang Ruqing¹^ORCID,Guo Jiafeng¹^ORCID,de Rijke Maarten²^ORCID,Fan Yixing¹^ORCID,Cheng Xueqi¹^ORCID

Affiliation:

1. CAS Key Lab of Network Data Science and Technology, ICT, CAS & University of Chinese Academy of Sciences, Beijing, China

2. University of Amsterdam, Amsterdam, Netherlands

Funder

Youth Innovation Promotion Association CAS

Strategic Priority Research Program of the CAS

LESSEN

FINDHR

Lenovo-CAS Joint Lab Youth Scientist Project

National Key Research and Development Program of China

National Natural Science Foundation of China (NSFC)

10-year

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626772.3657784

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3. Nick Craswell. 2009. Mean Reciprocal Rank. Encyclopedia of Database Systems 1703 (2009).

4. Guglielmo Faggioli, Laura Dietz, Charles LA Clarke, Gianluca Demartini, Matthias Hagen, Claudia Hauff, Noriko Kando, Evangelos Kanoulas, Martin Potthast, Benno Stein, et al. 2023. Perspectives on Large Language Models for Relevance Judgment. In SIGIR. 39--50.

5. Run-Ze Fan, Yixing Fan, Jiangui Chen, Jiafeng Guo, Ruqing Zhang, and Xueqi Cheng. 2024. RIGHT: Retrieval-Augmented Generation for Mainstream Hashtag Recommendation. In European Conference on Information Retrieval. Springer, 39--55.

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