G-CoS: An Interpretable Gain-Cost Framework for User Satisfaction Estimation in Generative Information Retrieval.

@inproceedings{shi-2026-gcos, author = {Jia-Ling Shi and Abigail Z. Jacobs and Zhijing Wu and Asia J. Biega and Yidong Liang and Xian-Ling Mao}, editor = {Hannah Bast and Alistair Moffat and Falk Scholer and Marc Najork and Min Zhang and Hannah Bast and Marc Najork and Min Zhang}, title = {{G-CoS: An Interpretable Gain-Cost Framework for User Satisfaction Estimation in Generative Information Retrieval}}, booktitle = {{Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, MelbourneVICAustralia, July 20-24, 2026}}, pages = {4110--4115}, publisher = {ACM}, year = {2026}, url = {https://doi.org/10.1145/3805712.3809934}, doi = {https://doi.org/10.1145/3805712.3809934} }