The paper presents a two‑stage large language model pipeline for e‑commerce attribute extraction. First, it discovers a compact, ranked set of purchase‑discriminative attributes for each product category; second, it extracts those attribute values from catalog text using a fine‑tuned Qwen3‑4B model with Hyper‑Parallel Decoding. The approach attains 85% extraction accuracy while cutting inference costs by 92%, enabling scalable production use and producing consistent, comparable product knowledge bases.
By Nikhita Vedula, Dushyanta Dhyani, Bryan Wang, Shervin Malmasi
arXiv:2607. 07469v1 Announce Type: cross Abstract: Fine-tuning large language models (LLMs) for e-commerce attribute extraction requires labeled data representative across thousands of product types, attributes, and multiple languages.
By Andrea Scarinci, Virginia Negri, Brayan Impata, Suleiman Khan, Victor Martinez, Marcello Federico
arXiv:2609.15205v1 Announce Type: cross
Abstract: Table extraction from texts is an important task for information systems, and recent approaches that prompt large language models (LLMs) with instruc...
By Tong Li, Shuye Ding, Jiachuan Wang, Yongqi Zhang, Shuangyin Li, Lei Chen, Bo Li
The paper "Query Brand Entity Linking in E-Commerce Search" addresses the challenge of matching short, unstructured user search queries to the correct brand entities in large e‑commerce catalogs. It proposes two scalable solutions: a cascaded pipeline that first detects brand mentions and then disambiguates them, and a single‑stage extreme multiclass classifier that directly maps queries to brand identifiers. Extensive multilingual evaluation and an online experiment show that both methods significantly improve brand recall while preserving high precision, resulting in measurable gains in customer engagement.
By Dong Liu, Sreyashi Nag
arXiv:2609.07334v1 Announce Type: new
Abstract: The Asset Administration Shell (AAS) is a cornerstone of Industry 4.0 and the Digital Product Passport, providing standardized digital representations...
By Janek Gro{\ss}, Jens Heidrich
arXiv:2606. 04387v1 Announce Type: cross Abstract: Sales lead conversion in high-stakes domains (e.
By Chenyu Zhang, Yiwen Liu, Yin Sun, Xinyuan Zhang, Yuji Cao, Junming Jiao, Juyi Qiao