cs.IR · 2026-07-31 · No. 70

Information Retrieval, 2026-07-31.

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

    TCA-SIR: Learning Target-Conditioned Abstractions for Scientific Inspiration Retrieval

    Yuto Suzuki, Farnoush Banaei-Kashani

    cs.IR · cs.AI · cs.CL

    Scientific hypothesis generation for AI for Science typically involves Scientific Inspiration Retrieval (SIR) followed by hypothesis composition. Existing SIR methods rank papers by topical similarity and do not explicitly represent how a candidate inspiration transfers to a target problem. This is especially limiting for remote inspirations, whose value often lies in reusable problem-solving principles rather than topical overlap. Motivated...

    arxiv.org/abs/2607.28498 · PDF

  2. 02

    Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation

    Long Zhang, Hao Jiang, Sheng Yu, Fei Pan, Peng Jiang, Kun Gai

    cs.IR · cs.AI

    While large language models (LLMs) have advanced ID-based recommendation through Semantic ID (SID) modeling, existing SID generation frameworks largely follow a single-representation-then-quantization paradigm. This design faces two bottlenecks: semantic entanglement mixes heterogeneous attributes, such as geography, brand, and category, causing information loss during quantization, low-quality SIDs, and severe collisions; moreover, black-box...

    arxiv.org/abs/2607.27944 · PDF

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