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cs.IR2026
Rank4Gen: RAG-Preference-Aligned Document Set Selection and Ranking
Yongqi Fan, Yuxiang Chu, Zhentao Xia +9
In the RAG paradigm, document ranking determines the evidence available to downstream generators. Through controlled analysis, we identify two phenomena underexplored by existing r…
cs.IR2025
TFRank: Think-Free Reasoning Enables Practical Pointwise LLM Ranking
Yongqi Fan, Xiaoyang Chen, Dezhi Ye +6
Reasoning-intensive ranking models built on Large Language Models (LLMs) have made notable progress. However, existing approaches often rely on large-scale LLMs and explicit Chain-…
cs.IR2024★ 1 cited
Spiral of Silence: How is Large Language Model Killing Information Retrieval? -- A Case Study on Open Domain Question Answering
Xiaoyang Chen, Ben He, Hongyu Lin +5
The practice of Retrieval-Augmented Generation (RAG), which integrates Large Language Models (LLMs) with retrieval systems, has become increasingly prevalent. However, the repercus…