LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction.

Chenhao Fang|Ramakrishna Bairi|Sushant Kumar|Kannan Achan|Xiaohan Li|Ganesh Ramakrishnan|Zezhong Fan|Jianpeng Xu|Kaushiki Nag|Evren Körpeoglu|Ramakrishna Bairi|Sushant Kumar|Ganesh Ramakrishnan|Kannan Achan


Anthology ID:DBLP:conf/sigir/Fang0FXNKKA24
Volume:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024
Year:2024
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:2910-2914
URL:https://doi.org/10.1145/3626772.3661357
DOI:https://doi.org/10.1145/3626772.3661357
DBLP:conf/sigir/Fang0FXNKKA24
BibTeX:
@inproceedings{fang-2024-llmensemble, author = {Chenhao Fang and Ramakrishna Bairi and Sushant Kumar and Kannan Achan and Xiaohan Li and Ganesh Ramakrishnan and Zezhong Fan and Jianpeng Xu and Kaushiki Nag and Evren K\"{o}rpeoglu and Ramakrishna Bairi and Sushant Kumar and Ganesh Ramakrishnan and Kannan Achan}, editor = {Grace Hui Yang and Hongning Wang and Sam Han and Claudia Hauff and Guido Zuccon and Yi Zhang}, title = {{LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction}}, booktitle = {{Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024}}, pages = {2910--2914}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3626772.3661357}, doi = {https://doi.org/10.1145/3626772.3661357} }