16 citations · 16 across the 6 of their papers we have counts for
7 papers
SimTrace: Grounded Multimodal User Trajectories Generation for Online User Modeling
Yunan Lu, Shuang Xie, Meghna Allamudi +4
Virtual clients offer a cost-effective approach to support applications such as A/B testing, recommender system development, and interface evaluation. However, building them requir…
SimGym: A Framework for A/B Test Simulation in E-Commerce with Traffic-Grounded VLM Agents
Han Li, Vibhor Malik, Zahra Zanjani Foumani +17
A/B testing remains the gold standard for evaluating modifications to e-commerce storefronts, yet it diverts traffic, requires weeks to reach statistical significance, and risks de…
ShopGym: An Integrated Framework for Realistic Simulation and Scalable Benchmarking of E-Commerce Web Agents
Chinmay Savadikar, Mingyu Zhao, Yuanzheng Zhu +5
Developing and evaluating e-commerce web agents requires environments that preserve meaningful task structure while enabling controllable, reproducible, and scalable scientific com…
An evidence-guided reinforcement learning method to improve psychiatric reasoning in small language models
Xinxin Lin, Guangxin Dai, Yi Zhong +25
Privacy and computational constraints limit the use of large language models in psychiatry, while adapting small language models (SLMs) often requires substantial data and expert a…
SimGym: Traffic-Grounded Browser Agents for Offline A/B Testing in E-Commerce
Alberto Castelo, Zahra Zanjani Foumani, Ailin Fan +17
A/B testing remains the gold standard for evaluating e-commerce UI changes, yet it diverts traffic, takes weeks to reach significance, and risks harming user experience. We introdu…
CC-OR-Net: A Unified Framework for LTV Prediction through Structural Decoupling
Mingyu Zhao, Haoran Bai, Yu Tian +2
Customer Lifetime Value (LTV) prediction, a central problem in modern marketing, is characterized by a unique zero-inflated and long-tail data distribution. This distribution prese…
Bias of AI-Generated Content: An Examination of News Produced by Large Language Models
Xiao Fang, Shangkun Che, Minjia Mao +3
Large language models (LLMs) have the potential to transform our lives and work through the content they generate, known as AI-Generated Content (AIGC). To harness this transformat…