activity
20232026
most citedLeveraging Large Language Models for Enhanced Product Descriptions in eCommerce

8 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Many Steps into One: Reasoning Contraction and the Limits of Safe Memory Reuse for LLM Agents

Jianghong Zhou, Hao Rong, Chen Lin +1

Thought templates, skill libraries, agent memories and caches turn many reasoning steps into one. We call this reasoning contraction. A contracted memory saves reasoning steps and…

cs.IR2025

Semantic Ads Retrieval at Walmart eCommerce with Language Models Progressively Trained on Multiple Knowledge Domains

Zhaodong Wang, Weizhi Du, Md Omar Faruk Rokon +6

Sponsored search in e-commerce poses several unique and complex challenges. These challenges stem from factors such as the asymmetric language structure between search queries and…

cs.AI2023

Enhanced E-Commerce Attribute Extraction: Innovating with Decorative Relation Correction and LLAMA 2.0-Based Annotation

Jianghong Zhou, Weizhi Du, Md Omar Faruk Rokon +5

The rapid proliferation of e-commerce platforms accentuates the need for advanced search and retrieval systems to foster a superior user experience. Central to this endeavor is the…

cs.CL2023★ 8 cited

Leveraging Large Language Models for Enhanced Product Descriptions in eCommerce

Jianghong Zhou, Bo Liu, Jhalak Nilesh Acharya Yao Hong +2

In the dynamic field of eCommerce, the quality and comprehensiveness of product descriptions are pivotal for enhancing search visibility and customer engagement. Effective product…

cs.LG2023

A Deep Reinforcement Learning Approach for Interactive Search with Sentence-level Feedback

Jianghong Zhou, Joyce C. Ho, Chen Lin +1

Interactive search can provide a better experience by incorporating interaction feedback from the users. This can significantly improve search accuracy as it helps avoid irrelevant…