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Paper

Credit-assigned Policy Gradient for Early Stage Retrieval in Two-stage Ranking

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AI summary

arXiv:2605. 26385v1 Announce Type: cross Abstract: Large-scale search, recommendation, and retrieval-augmented generation (RAG) systems typically employ a two-stage architecture: an early-stage ranker (ESR) generates a candidate set, which is subsequently re-ranked by a late-stage ranker (LSR).