THUIR at the NTCIR-18 FairWeb-2 Task

The fairness of search systems remains a critical challenge in information retrieval. Building upon our previous work in FairWeb‑1, this paper presents the THUIR team’s approach in the NTCIR‑18 FairWeb‑2 Task. Specifically, we developed a simple yet effective retrieval pipeline that integrates multiple neural rerankers with results aggregated via Reciprocal Rank Fusion to generate balanced search rankings across various entity types. Additionally, we submitted a revived run that combines a PM2-based result diversification algorithm with dense retrieval scores. Our experimental results yield competitive performance on multiple evaluation metrics, demonstrating that enhancements in retrieval relevance inherently promote balanced group fairness. With the right combination of techniques, it is possible to achieve a synergistic reinforcement between relevance and fairness.