RAG-Match is a three-stage framework for semantic relevance modeling that integrates knowledge-augmented pretraining, hierarchical reasoning alignment, and preference-based decision calibration, outperforming LLM baselines on a search benchmark.
Rradistill: Distilling llms’ passage ranking 20 ability for long-tail queries document re-ranking on a search engine,
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RAG-Match: Retrieval-Augmented Knowledge Injection and Hierarchical Reasoning for Calibrated Semantic Relevance
RAG-Match is a three-stage framework for semantic relevance modeling that integrates knowledge-augmented pretraining, hierarchical reasoning alignment, and preference-based decision calibration, outperforming LLM baselines on a search benchmark.