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

作者 PulseAugur 编辑部 · [3 个来源] · 2026-09-01 00:00

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。

AI 生成摘要 · Google Gemini · 来自 3 个来源。我们如何撰写摘要 →

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Newsworthiness bucket: Research; 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; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
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arXiv cs.CL TIER_1 English(EN) · Runpeng Dai, Kaili Huang, Changsung Kang, Ciya Liao · 2026-09-02 04:00

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…
arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Ciya Liao · 2026-09-01 03:17

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…
Hugging Face Daily Papers TIER_1 English(EN) · 2026-09-01 00:00

双剑合璧：通过强化学习协同进化生成式检索器

CoGR trains LLMs to generate compact keywords for both queries and items, enabling direct inverted-index retrieval optimized via co-evolving reinforcement learning.