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Robust Fusion of Semantic and Behavioural Signals for LLM Reranking in Personalised Search
Personalised search must satisfy query intent while incorporating user context and historical interactions. LLM-based cross-encoders provide a single reranking interface, but injecting predictive behavioural statistics into their prompts can encourage shortcut learning: reliance on historical signal
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