Newest papers

Evolving Semantic Indexes for Generative Retrieval

Jinming Nian, Jyun‐Yu Jiang, Henry Tsai, Yi Fang, Zhirong Liang · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.28568 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

可靠性是可靠的空间检索工具(GR)作为分散的语义标识符(SIDs)的分散式检索和建议。SID设计大多决定了GR质量,但其分散的、相互依存的组件(SID构建、碰撞处理、解码和培训)无法用梯度进行终端优化,而且大部分都是手工设计的。我们引入了一套框架,通过LLM驱动的进化计划搜索来改进这些组件,我们知道这个方法的第一个应用程序是GR。本地服务的、开放式31B模型可以改造可执行的GR组件,所以没有专属的LLM API在流程上使用,并且1M传输参数代理解码器提供了快速反馈,而不是重复训练1B目标生成器。在NQ3

Machine translation (Meta M2M100); the English original follows.

Abstract

Generative retrieval (GR) casts search and recommendation as autoregressive generation of discrete semantic identifiers (SIDs). SID design largely determines GR quality, but its discrete, interdependent components (SID construction, collision handling, decoding, and training) cannot be optimized end-to-end with gradients and remain largely hand-designed. We introduce a framework that improves these components through LLM-driven evolutionary program search, to our knowledge the first application of this approach to GR. A locally served, open-weight 31B model mutates executable GR components, so no proprietary LLM API is used, and a 1M-parameter proxy decoder provides fast feedback in place of repeatedly training the 1B target generator. Across 21 SID programs on NQ320K, proxy and target Recall@100 show strong rank correlation (Spearman $ρ= 0.90$). Guided by this proxy, evolution improves the seed GR on NQ320K, MSMARCO300K, and a multilingual e-commerce dataset under a fixed training recipe. On NQ320K, jointly evolving SID construction and collision handling improves Recall@1 from 55.8% to 59.3% and Recall@100 from 85.8% to 90.6%. A component study shows that proxy reliability depends on what is evolved: improvements transfer reliably for the semantic index but not for the generator's training objective or the full pipeline. LLM-driven evolutionary search is thus a practical tool for GR design, provided proxy reliability is established for the chosen search space.

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Topics: Executable, Computer science, Proxy (statistics), Generative model, Generative grammar, Reliability (semiconductor)

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