6 papers
Campaign-2-PT-RAG: LLM-Guided Semantic Product Type Attribution for Scalable Campaign Ranking
Yiming Che, Mansi Ranjit Mane, Keerthi Gopalakrishnan +8
E-commerce campaign ranking models require large-scale training labels indicating which users purchased due to campaign influence. However, generating these labels is challenging b…
Latent Customer Segmentation and Value-Based Recommendation Leveraging a Two-Stage Model with Missing Labels
Keerthi Gopalakrishnan, Tianning Dong, Chia-Yen Ho +5
The success of businesses depends on their ability to convert consumers into loyal customers. A customer's value proposition is a primary determinant in this process, requiring a b…
LLM-driven Constrained Copy Generation through Iterative Refinement
Varun Vasudevan, Faezeh Akhavizadegan, Abhinav Prakash +5
Crafting a marketing message (copy), or copywriting is a challenging generation task, as the copy must adhere to various constraints. Copy creation is inherently iterative for huma…
Chaining text-to-image and large language model: A novel approach for generating personalized e-commerce banners
Shanu Vashishtha, Abhinav Prakash, Lalitesh Morishetti +4
Text-to-image models such as stable diffusion have opened a plethora of opportunities for generating art. Recent literature has surveyed the use of text-to-image models for enhanci…
A Real-Time Whole Page Personalization Framework for E-Commerce
Aditya Mantha, Anirudha Sundaresan, Shashank Kedia +6
E-commerce platforms consistently aim to provide personalized recommendations to drive user engagement, enhance overall user experience, and improve business metrics. Most e-commer…
A Large-Scale Deep Architecture for Personalized Grocery Basket Recommendations
Aditya Mantha, Yokila Arora, Shubham Gupta +4
With growing consumer adoption of online grocery shopping through platforms such as Amazon Fresh, Instacart, and Walmart Grocery, there is a pressing business need to provide relev…