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LLMs generate image quality labels to boost e-commerce sales

Researchers have developed a method called Image Score to evaluate image quality for e-commerce platforms like Mercari. This approach utilizes Large Language Models (LLMs) with Chain-of-Thought prompting to generate aesthetic labels for product images. The LLM-generated labels correlate with user behavior and are more cost-effective than human evaluation, leading to improved customer journey optimization and a significant increase in sales during online experimentation. AI

影响 This LLM-driven image quality assessment could improve product discovery and sales conversion on e-commerce platforms.

排序理由 This is a research paper detailing a new method for image quality assessment using LLMs.

在 arXiv cs.CV 阅读 →

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LLMs generate image quality labels to boost e-commerce sales

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Chingis Oinar, Miao Cao, Shanshan Fu ·

    Image Score: Learning and Evaluating Human Preferences for Mercari Search

    arXiv:2408.11349v2 Announce Type: replace Abstract: Mercari is the largest C2C e-commerce marketplace in Japan, having more than 20 million active monthly users. Search being the fundamental way to discover desired items, we have always had a substantial amount of data with impli…