ProMax: Exploring the Potential of LLM-derived Profiles with Distribution Shaping for Recommender Systems.

Yi Zhang|Ting Bai|Yiwen Zhang|Ting Bai|Yiwen Zhang|Kai Zheng|Tong Chen|Hongzhi Yin


Anthology ID:DBLP:conf/sigir/ZhangZZCY26
Volume:Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, MelbourneVICAustralia, July 20-24, 2026
Year:2026
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:2431-2441
URL:https://doi.org/10.1145/3805712.3809600
DOI:https://doi.org/10.1145/3805712.3809600
DBLP:conf/sigir/ZhangZZCY26
BibTeX:
@inproceedings{zhang-2026-promax, author = {Yi Zhang and Ting Bai and Yiwen Zhang and Ting Bai and Yiwen Zhang and Kai Zheng and Tong Chen and Hongzhi Yin}, 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 = {{ProMax: Exploring the Potential of LLM-derived Profiles with Distribution Shaping for Recommender Systems}}, booktitle = {{Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, MelbourneVICAustralia, July 20-24, 2026}}, pages = {2431--2441}, publisher = {ACM}, year = {2026}, url = {https://doi.org/10.1145/3805712.3809600}, doi = {https://doi.org/10.1145/3805712.3809600} }