activity
20242026
most citedCultural Value Differences of LLMs: Prompt, Language, and Model Size

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Alignment by Stereotyping: How LLMs Sacrifice Individual Distinctiveness for Cultural Adaptation

Qishuai Zhong, Zongmin Li, Siqi Fan +1

Large language models are increasingly deployed for personalized interaction, and demographic conditioning via user profiles is a widely adopted strategy for cultural adaptation. W…

cs.IR2025

Multi-Stage Field Extraction of Financial Documents with OCR and Compact Vision-Language Models

Yichao Jin, Yushuo Wang, Qishuai Zhong +3

Financial documents are essential sources of information for regulators, auditors, and financial institutions, particularly for assessing the wealth and compliance of Small and Med…

cs.CL2025

Evaluating LLM Adaptation to Sociodemographic Factors: User Profile vs. Dialogue History

Qishuai Zhong, Zongmin Li, Siqi Fan +1

Effective engagement by large language models (LLMs) requires adapting responses to users' sociodemographic characteristics, such as age, occupation, and education level. While man…

cs.CL2024

RAGulator: Lightweight Out-of-Context Detectors for Grounded Text Generation

Ian Poey, Jiajun Liu, Qishuai Zhong +1

Real-time detection of out-of-context LLM outputs is crucial for enterprises looking to safely adopt RAG applications. In this work, we train lightweight models to discriminate LLM…

cs.CY20241 cited

Cultural Value Differences of LLMs: Prompt, Language, and Model Size

Qishuai Zhong, Yike Yun, Aixin Sun

Our study aims to identify behavior patterns in cultural values exhibited by large language models (LLMs). The studied variants include question ordering, prompting language, and m…