LLaSA: Large Language and E-Commerce Shopping Assistant
Shuo Zhang, Boci Peng, Xinping Zhao, Boren Hu, Yun Zhu, Yanjia Zeng,, Xuming Hu

TL;DR
This paper introduces LLaSA, a large language model-based e-commerce shopping assistant trained on a diverse dataset, demonstrating strong performance and generalization across multiple tasks and winning top rankings in a major challenge.
Contribution
The paper presents LLaSA, a novel omnipotent shopping assistant built with instruction tuning on a large, diverse dataset, addressing task-specificity and generalization issues of prior models.
Findings
LLaSA achieved 3rd place in the Amazon KDD Cup 2024 Challenge.
LLaSA secured top-5 rankings across all challenge tracks.
Instruction tuning on EshopInstruct enhances multi-task performance.
Abstract
The e-commerce platform has evolved rapidly due to its widespread popularity and convenience. Developing an e-commerce shopping assistant for customers is crucial to aiding them in quickly finding desired products and recommending precisely what they need. However, most previous shopping assistants face two main problems: (1) task-specificity, which necessitates the development of different models for various tasks, thereby increasing development costs and limiting effectiveness; and (2) poor generalization, where the trained model performs inadequately on up-to-date products. To resolve these issues, we employ Large Language Models (LLMs) to construct an omnipotent assistant, leveraging their adeptness at handling multiple tasks and their superior generalization capability. Nonetheless, LLMs lack inherent knowledge of e-commerce concepts. To address this, we create an instruction…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMobile Agent-Based Network Management · Data Mining Algorithms and Applications · Service-Oriented Architecture and Web Services
