Ziqi Xu

Large language models (LLMs) are widely used for question answering (QA) but can generate biased or stereotype-driven answers due to demographic associations learned during pre-training. Existing mitigation strategies often rely on model access or fine-tuning, which limits their applicability to...

Large Language Model (LLM)-based agent simulation has emerged as a promising approach to meet the increasing demand for real-time and rigorous evaluation in modern recommender systems. A typical LLM-driven simulation framework comprises three essential components: the profile module, memory modul...

The rapid growth of large-scale datasets in outlier detection (OD) makes exhaustive evaluation of diverse candidate models for each new dataset impractical. The unsupervised outlier model recommendation (UOMR) problem remains underexplored and presents two major challenges: severe cold-start cons...