most citedThe Imperfect Learner: Incorporating Developmental Trajectories in Memory-based Student Simulation

1 citations · 1 across the 6 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Reinforcement Learning with Comparative Evidence for Social Intelligence

Keane Ong, Yuriel Ryan, Sabri Boughorbel +9

Developing socially intelligent AI remains heavily dependent on human-annotated data, limiting the scale and breadth of social understanding models can acquire. Methods that derive…

cs.CL2026

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…

cs.CL2026

SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures

Nedjma Ousidhoum, Junho Myung, Carla Perez-Almendros +27

We present our shared task on evaluating the adaptability of LLMs and NLP systems across multiple languages and cultures. The task data consist of an extended version of our manual…

cs.CY2026

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…

cs.CY2025★ 1 cited

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…

cs.CL2025

Persuasion Dynamics in LLMs: Investigating Robustness and Adaptability in Knowledge and Safety with DuET-PD

Bryan Chen Zhengyu Tan, Daniel Wai Kit Chin, Zhengyuan Liu +2

Large Language Models (LLMs) can struggle to balance gullibility to misinformation and resistance to valid corrections in persuasive dialogues, a critical challenge for reliable de…

cs.CL2025

CCL-XCoT: An Efficient Cross-Lingual Knowledge Transfer Method for Mitigating Hallucination Generation

Weihua Zheng, Roy Ka-Wei Lee, Zhengyuan Liu +3

Multilingual Large Language Models(MLLMs) demonstrate strong generalization across languages, yet they remain prone to hallucinations, especially in low-resource languages, due to…

cs.CL2025

AdaMCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Multilingual Chain-of-Thought

Weihua Zheng, Xin Huang, Zhengyuan Liu +7

Large language models (LLMs) have shown impressive multilingual capabilities through pretraining on diverse corpora. Although these models show strong reasoning abilities, their pe…