arXiv AI

Integrating Multi-Label Classification and Generative AI for Scalable Analysis of User Feedback

arXiv:2601. 23018v1 Announce Type: cross Abstract: In highly competitive software markets, user experience (UX) evaluation is crucial for ensuring software quality and fostering long-term product success.

arXiv AI
Jun 24

AI-PAVE-Br: Leveraging Large Language Models for Enhanced Product Attribute Value Extraction through a Golden Set Approach

arXiv:2606. 24655v1 Announce Type: cross Abstract: The explosive growth and complexity of product data within the dynamic Brazilian e-commerce landscape demand robust and specialized methods for structured information extraction.

By Murilo Gazzola, Hugo Gobato Souto, Samuel Silva, J\'ulia Schubert Peixoto, Felipe Siqueira, Andr\'e Luis Pedroso de Morais, Caio Gomes
arXiv AI
Jul 17

CatalogAgent: A Supervisor-mediated Self-Learning System Enabling Context Engineering for GenAI Models

arXiv:2607. 14396v1 Announce Type: new Abstract: Product catalogs are the backbone of e-commerce sites, yet a large number of structured attributes (SAs) -- such as material, color, and shape -- often have missing values.

By Zhu Cheng (Xuan), Zhenming Wang (Xuan), Yu (Xuan), Tang, Dan Liu, Bryan Zhang, Athanasios N. Nikolakopoulos, Pranav Souri Itabada, Jing Zhang, Chih-Chi Chou, Peng Gao, Fatemeh Mansoori, Bharat Bojja, Sarath Chander, Sameer Thombare, Umit Batur, Tarik Arici
arXiv Machine Learning
Jul 3

Bi-NAS: Towards Effective and Personalized Explanation for Recommender Systems via Bi-Level Neural Architecture Search

arXiv:2607. 01387v1 Announce Type: cross Abstract: Recommender systems are vital in helping users navigate vast amounts of information, offering personalized suggestions and effective explanations for these recommendations.

By Longfeng Wu, Yao Zhou, Tong Zeng, Zhimin Peng, Bhanu Pratap Singh Rawat, Lecheng Zheng, Giovanni Seni, Dawei Zhou