EcomGPT: Instruction-Tuning Large Language Models with Chain-of-Task Tasks for E-commerce
DOI:
https://doi.org/10.1609/aaai.v38i17.29820Keywords:
NLP: (Large) Language Models, NLP: Applications, NLP: Information Extraction, NLP: OtherAbstract
Recently, instruction-following Large Language Models (LLMs) , represented by ChatGPT, have exhibited exceptional performance in general Natural Language Processing (NLP) tasks. However, the unique characteristics of E-commerce data pose significant challenges to general LLMs. An LLM tailored specifically for E-commerce scenarios, possessing robust cross-dataset/task generalization capabilities, is a pressing necessity. To solve this issue, in this work, we proposed the first E-commerce instruction dataset EcomInstruct, with a total of 2.5 million instruction data. EcomInstruct scales up the data size and task diversity by constructing atomic tasks with E-commerce basic data types, such as product information, user reviews. Atomic tasks are defined as intermediate tasks implicitly involved in solving a final task, which we also call Chain-of-Task tasks. We developed EcomGPT with different parameter scales by training the backbone model BLOOMZ with the EcomInstruct. Benefiting from the fundamental semantic understanding capabilities acquired from the Chain-of-Task tasks, EcomGPT exhibits excellent zero-shot generalization capabilities. Extensive experiments and human evaluations demonstrate that EcomGPT outperforms ChatGPT in term of cross-dataset/task generalization on E-commerce tasks. The EcomGPT will be public at https://github.com/Alibaba-NLP/EcomGPT.Downloads
Published
2024-03-24
How to Cite
Li, Y., Ma, S., Wang, X., Huang, S., Jiang, C., Zheng, H.-T., Xie, P., Huang, F., & Jiang, Y. (2024). EcomGPT: Instruction-Tuning Large Language Models with Chain-of-Task Tasks for E-commerce. Proceedings of the AAAI Conference on Artificial Intelligence, 38(17), 18582-18590. https://doi.org/10.1609/aaai.v38i17.29820
Issue
Section
AAAI Technical Track on Natural Language Processing II