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English(EN) It Takes Two to Match: Co-Evolving Generative Retriever with Reinforcement Learning

新的检索框架CoGR使用LLM为搜索生成关键词

研究人员开发了CoGR,一个新颖的检索框架,它训练LLM为查询和项目生成检索表示。该方法使用两阶段训练过程,首先进行监督微调以对齐关键词空间,然后进行共同演进的强化学习。CoGR在应用市场和基准数据集上展示了卓越的性能,显著优于现有方法。 AI

影响 该框架可以通过让LLM直接生成检索表示来提高搜索引擎的效率和相关性。

排序理由 该集群包含一篇详细介绍信息检索新方法的学术论文。

在 arXiv cs.IR (Information Retrieval) 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新的检索框架CoGR使用LLM为搜索生成关键词

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该集群包含一篇详细介绍信息检索新方法的学术论文。
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Topics
paper, product
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Runpeng Dai, Kaili Huang, Changsung Kang, Ciya Liao ·

    双剑合璧:通过强化学习共同演进生成式检索器

    arXiv:2609.00638v1 Announce Type: cross Abstract: Retrieval is the first stage of modern search and advertising systems, selecting a candidate set from a large item universe for downstream ranking and auction. Recent work increasingly leverages LLMs to improve retrieval through q…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Ciya Liao ·

    双剑合璧:通过强化学习协同进化生成式检索器

    Retrieval is the first stage of modern search and advertising systems, selecting a candidate set from a large item universe for downstream ranking and auction. Recent work increasingly leverages LLMs to improve retrieval through query expansion, data synthesis, and retrieval-feed…