@article{wei2026,
title = {Inventory-Grounded Policy-Level Optimization for Training-Free AI Search},
author = {Zhou, Wei and Wu, Tiandeng and Ding, Jiandong and Fan, Zhufeng and Cao, Yi},
journal = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track},
year = {2026},
month = {Jan},
doi = {10.18653/2026.emnlp-industry.7},
url = {https://doi.org/10.18653/2026.emnlp-industry.7},
}
Zhou, Wei et al. (2026). Inventory-Grounded Policy-Level Optimization for Training-Free AI Search. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track. https://doi.org/10.18653/2026.emnlp-industry.7
Zhou, Wei, et al.. "Inventory-Grounded Policy-Level Optimization for Training-Free AI Search." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track, 2026, https://doi.org/10.18653/2026.emnlp-industry.7.
Zhou, Wei, et al.. "Inventory-Grounded Policy-Level Optimization for Training-Free AI Search." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track (2026). https://doi.org/10.18653/2026.emnlp-industry.7
Zhou, Wei et al., 2026. Inventory-Grounded Policy-Level Optimization for Training-Free AI Search. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track. Available at: <https://doi.org/10.18653/2026.emnlp-industry.7>.
TY - JOUR
TI - Inventory-Grounded Policy-Level Optimization for Training-Free AI Search
AU - Zhou, Wei
AU - Wu, Tiandeng
AU - Ding, Jiandong
AU - Fan, Zhufeng
AU - Cao, Yi
PY - 2026
JO - Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track
DO - 10.18653/2026.emnlp-industry.7
UR - https://doi.org/10.18653/2026.emnlp-industry.7
ER -