cs.IR · 2026-08-16 · No. 86

Information Retrieval, 2026-08-16.

2 new papers in cs.IR. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Generative Universal Multimodal Retrieval with Dual-role Identifiers

    Kaipeng Li, Haitao Yu, Xuanchen Zhou

    cs.IR · cs.AI

    Generative information retrieval (GIR) has emerged as a compelling alternative to the conventional index-retrieve-then-rank retrieval pipeline by training a generator to produce the identifiers of relevant items directly. Despite its promise, a number of open challenges still remain. First, constrained left-to-right decoding is vulnerable to prefix-level errors and local optima. Second, most prior GIR research remains largely unimodal,...

    arxiv.org/abs/2608.12987 · PDF

  2. 02

    FSGR: Mitigating Token Frequency Bias for Fair SID-Based Generative Recommendation

    Yuchen Zheng, Sihan Xu, Jingwen Yang, Xiangrui Cai, Haiwei Zhang, Xiaojie Yuan

    cs.IR · cs.AI · cs.LG

    Semantic ID (SID)-based generative recommendation has recently achieved remarkable success. However, existing methods suffer from a previously overlooked fairness issue, which we term \textbf{Token Frequency Bias}, where high-frequency SID tokens are systematically over-predicted while low-frequency SID tokens are under-predicted. This bias originates from the combined effects of imbalanced semantic codebooks during SID construction, and...

    arxiv.org/abs/2608.12845 · PDF

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