2 papers
cs.CL2026
Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization
Tiancheng Xing, Jerry Li, Yixuan Du +1
Large language models (LLMs) are increasingly used as rerankers in information retrieval, yet their ranking behavior can be steered by small, natural-sounding prompts. To expose th…
cs.CL2026
Multimodal Generative Engine Optimization: Rank Manipulation for Vision-Language Model Rankers
Yixuan Du, Chenxiao Yu, Haoyan Xu +3
Vision-Language Models (VLMs) integrate visual and textual knowledge into unified representations that increasingly underpin modern retrieval and recommendation systems. However, i…