Large Language Model Relevance Assessors Agree With One Another More Than With Human Assessors.

Maik Fröbe|Andrew Parry|Ferdinand Schlatt|Sean MacAvaney|Benno Stein|Martin Potthast|Matthias Hagen


Anthology ID:DBLP:conf/sigir/FrobePSM0PH25
Volume:Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025
Year:2025
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:2858-2863
URL:https://doi.org/10.1145/3726302.3730218
DOI:https://doi.org/10.1145/3726302.3730218
DBLP:conf/sigir/FrobePSM0PH25
BibTeX:
@inproceedings{frobe-2025-large, author = {Maik Fr\"{o}be and Andrew Parry and Ferdinand Schlatt and Sean MacAvaney and Benno Stein and Martin Potthast and Matthias Hagen}, editor = {Nicola Ferro and Maria Maistro and Gabriella Pasi and Omar Alonso and Andrew Trotman and Suzan Verberne}, title = {{Large Language Model Relevance Assessors Agree With One Another More Than With Human Assessors}}, booktitle = {{Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025}}, pages = {2858--2863}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3726302.3730218}, doi = {https://doi.org/10.1145/3726302.3730218} }