10 citations · 11 across the 8 of their papers we have counts for
9 papers
CultureConverse: A Multilingual Multi-turn Simulation Harness for Culturally Grounded Assistance in East and Southeast Asia
Bryan Chen Zhengyu Tan, Weihua Zheng, Thong T. Doan +30
Current cultural evaluations for large language models (LLMs) often reduce culture to single-turn factual recall via MCQs, failing to capture a common use case: users seeking pract…
Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural Alignment
Bryan Chen Zhengyu Tan, Zhengyuan Liu, Xiaoyuan Yi +4
Despite their global prevalence, many Large Language Models (LLMs) are aligned to a monolithic, often Western-centric set of values. This paper investigates the more challenging ta…
Small Changes, Big Impact: Demographic Bias in LLM-Based Hiring Through Subtle Sociocultural Markers in Anonymised Resumes
Bryan Chen Zhengyu Tan, Shaun Khoo, Bich Ngoc Doan +3
Large Language Models (LLMs) are increasingly deployed in resume screening pipelines. Although explicit PII (e.g., names) is commonly redacted, resumes typically retain subtle soci…
The Imperfect Learner: Incorporating Developmental Trajectories in Memory-based Student Simulation
Zhengyuan Liu, Stella Xin Yin, Bryan Chen Zhengyu Tan +5
User simulation is important for developing and evaluating human-centered AI, yet current student simulation in educational applications has significant limitations. Existing appro…
MMA-ASIA: A Multilingual and Multimodal Alignment Framework for Culturally-Grounded Evaluation
Weihua Zheng, Zhengyuan Liu, Tanmoy Chakraborty +32
Large language models (LLMs) are now used worldwide, yet their multimodal understanding and reasoning often degrade outside Western, high-resource settings. We propose MMA-ASIA, a…
BLEnD-Vis: Benchmarking Multimodal Cultural Understanding in Vision Language Models
Bryan Chen Zhengyu Tan, Zheng Weihua, Zhengyuan Liu +4
As vision-language models (VLMs) are deployed globally, their ability to understand culturally situated knowledge becomes essential. Yet, existing evaluations largely assess static…