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

Japanese

信頼性は確実な空間リリースツールです(GR)は、独自の固定識別子(SIDs)の生成として検索と勧告を提供します。SID設計は、ほとんどがGRの品質を決定しますが、その独自の、相互依存するコンポーネント(SID建設、衝突処理、デコーディング、およびトレーニング)は、最終的に最適化されないため、グレディントで独自のLLM APIが使用されず、主に手動で設計されています。私たちは、LLM駆動の進化型プログラムの検索を通じてこれらのコンポーネントを改善するフレームワークを導入します。私たちの知る限り、このアプローチの最初のアプリケーションはGRです。ローカルでサービスされたオープンワイド31Bモデ

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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