22 citations · 24 across the 7 of their papers we have counts for
7 papers
PACEShop: Evaluating Personalized, Actionable, Compositional, and Evidence-grounded Shopping Assistants
Weimin Lyu, Chen Luo, Guangrui Li +9
Shopping assistants are shifting from ranked product lists toward structured decision support, where systems must synthesize shopper context, product evidence, and next-step guidan…
Transparent and Controllable Recommendation Filtering via Multimodal Multi-Agent Collaboration
Chi Zhang, Zhipeng Xu, Jiahao Liu +5
While personalized recommender systems excel at content discovery, they frequently expose users to undesirable or discomforting information, highlighting the critical need for user…
LLM Agent Meets Agentic AI: Can LLM Agents Simulate Customers to Evaluate Agentic-AI-based Shopping Assistants?
Lu Sun, Shihan Fu, Bingsheng Yao +7
Agentic AI is emerging, capable of executing tasks through natural language, such as Copilot for coding or Amazon Rufus for shopping. Evaluating these systems is challenging, as th…
EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association
Weiqi Wang, Limeng Cui, Xin Liu +14
Goal-oriented script planning, or the ability to devise coherent sequences of actions toward specific goals, is commonly employed by humans to plan for typical activities. In e-com…
UXAgent: A System for Simulating Usability Testing of Web Design with LLM Agents
Yuxuan Lu, Bingsheng Yao, Hansu Gu +7
Usability testing is a fundamental research method that user experience (UX) researchers use to evaluate and iterate their new designs. But what about evaluating and iterating the…
UXAgent: An LLM Agent-Based Usability Testing Framework for Web Design
Yuxuan Lu, Bingsheng Yao, Hansu Gu +7
Usability testing is a fundamental yet challenging (e.g., inflexible to iterate the study design flaws and hard to recruit study participants) research method for user experience (…
Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data
Juanhui Li, Sreyashi Nag, Hui Liu +7
In real-world NLP applications, Large Language Models (LLMs) offer promising solutions due to their extensive training on vast datasets. However, the large size and high computatio…