5 citations · 5 across the 8 of their papers we have counts for
10 papers
VoteGEO-Bench: Measuring the Impact of Generative Engine Optimization on Electoral Visibility
Shiqi Zhang, Xiaokui Xiao
Large language models (LLMs) are increasingly used for election information, yet little is known about how external web content shapes the political information they present. Gener…
Understanding ChatGPT Citations: Evidence from Production Web Search Across Model Generations
Yunxuan Jiang, Shiqi Zhang, Anqi Xing +2
Generative engines such as ChatGPT Web retrieve webpages to answer user queries, but only a subset are shown as citations. Understanding this retrieval-to-citation process is impor…
SCOPE: Cost-Efficient Model Selection for Compound AI Systems under Quality Constraints
Yiqian Huang, Shiqi Zhang, Tianyuan Jin +1
A compound AI system consists of multiple LLM modules, together handling complex and multi-step tasks that exceed the capabilities of a single model. Existing systems often use a s…
NBQ: Next-Best-Question for Dynamic Profiling
Yimin Shi, Clarice Wang, Haixun Wang +1
Many real-world conversational settings for knowledge discovery, including podcasts, hiring screens, and marketplaces, require a purpose-driven understanding of a person. We study…
GEM-Bench: A Benchmark for Ad-Injected Response Generation within Generative Engine Marketing
Silan Hu, Shiqi Zhang, Yimin Shi +1
Generative Engine Marketing (GEM) is an emerging ecosystem for monetizing generative engines, such as LLM-based chatbots, by seamlessly integrating relevant advertisements into the…
You Are What You Bought: Generating Customer Personas for E-commerce Applications
Yimin Shi, Yang Fei, Shiqi Zhang +2
In e-commerce, user representations are essential for various applications. Existing methods often use deep learning techniques to convert customer behaviors into implicit embeddin…
KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG
Yiqian Huang, Shiqi Zhang, Xiaokui Xiao
Graph-RAG constructs a knowledge graph from text chunks to improve retrieval in Large Language Model (LLM)-based question answering. It is particularly useful in domains such as bi…
ThriftLLM: On Cost-Effective Selection of Large Language Models for Classification Queries
Keke Huang, Yimin Shi, Dujian Ding +4
In recent years, large language models (LLMs) have demonstrated remarkable capabilities in comprehending and generating natural language content, attracting widespread attention in…
Hyperparametric Robust and Dynamic Influence Maximization
Arkaprava Saha, Bogdan Cautis, Xiaokui Xiao +1
We study the problem of robust influence maximization in dynamic diffusion networks. In line with recent works, we consider the scenario where the network can undergo insertion and…
Efficient and Effective Algorithms for A Family of Influence Maximization Problems with A Matroid Constraint
Yiqian Huang, Shiqi Zhang, Laks V. S. Lakshmanan +3
Influence maximization (IM) is a classic problem that aims to identify a small group of critical individuals, known as seeds, who can influence the largest number of users in a soc…