collaborators

12 papers

cs.HC2026

Ethics and Social Responsibility in AI-Assisted Interviewing: An LLM-in-the-Loop Study of AI-Generated Follow-Up Questions

He Zhang, Yueyan Liu, Xin Guan +2

Semi-structured interviews rely on timely, context-sensitive follow-up questions, yet interviewers' cognitive load and limited domain familiarity can constrain probing depth. We re…

cs.SE2026

NormCode Canvas: Making LLM Agentic Workflows Development Sustainable via Case-Based Reasoning

Xin Guan, Yunshan Li, Ze Wang

We present NormCode Canvas (v1.1.3), a deployed system realizing Case-Based Reasoning at two levels for multi-step LLM workflows. The foundation is NormCode, a semi-formal planning…

cs.CY2026

Evaluating 21st-Century Competencies in Postsecondary Curricula with Large Language Models: Performance Benchmarking and Reasoning-Based Prompting Strategies

Zhen Xu, Xin Guan, Chenxi Shi +2

The growing emphasis on 21st-century competencies in postsecondary education, intensified by the transformative impact of generative AI, underscores the need to evaluate how these…

cs.AI2026

NormCode: A Semi-Formal Language for Auditable AI Planning

Xin Guan, Yunshan Li, Zekun Wu +1

As AI systems move into high stakes domains such as legal reasoning, medical diagnosis, and financial decision making, regulators and practitioners increasingly demand auditability…

cs.HC2025

Harnessing the Power of AI in Qualitative Research: Role Assignment, Engagement, and User Perceptions of AI-Generated Follow-Up Questions in Semi-Structured Interviews

He Zhang, Yueyan Liu, Xin Guan +2

Semi-structured interviews highly rely on the quality of follow-up questions, yet interviewers' knowledge and skills may limit their depth and potentially affect outcomes. While ma…

cs.CL2025

MPF: Aligning and Debiasing Language Models post Deployment via Multi Perspective Fusion

Xin Guan, PeiHsin Lin, Zekun Wu +4

Multiperspective Fusion (MPF) is a novel posttraining alignment framework for large language models (LLMs) developed in response to the growing need for easy bias mitigation. Built…