Daily edition · Information Retrieval
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27 articles · 2 sources · 25 papers ·
Top topics: Information Retrieval · AI · AI Research
Firefox and Chrome are both excellent browsers. For everyday use, they are largely interchangeable. The differences that matter depend on your specific priorities. Here is a practical comparison for people who actually…
Originally published on CodingCush. Next.js is a free framework built on top of React that helps you build complete, fast and search engine friendly websites and web applications. React on its own is a library for…
arXiv:2512.22838v3 Announce Type: replace-cross Abstract: At billion scale, approximate nearest neighbor search (ANNS) often becomes an out-of-core problem: the full vector collection and index structures exceed memory…
arXiv:2611.09178v1 Announce Type: cross Abstract: While machine learning hiring tools are ubiquitous, the need for privacy regulations and commercial sensitivity makes public benchmarking legally complex. We address…
arXiv:2608.28572v2 Announce Type: replace Abstract: Institutional investors search visually dense pitch decks, board packs, and diligence materials that change hourly near deal closing. OCR followed by figure…
arXiv:2611.09200v1 Announce Type: new Abstract: We study Vietnamese statutory Article retrieval on DRiLL using features for provision identity and local form, same-law support, and citation and lineage evidence. Across…
arXiv:2611.08804v1 Announce Type: new Abstract: Search and recommendation at Shopify require retrieving relevant products from a changing catalog of billions of products under strict latency constraints. We present…
arXiv:2611.09472v1 Announce Type: cross Abstract: Language-model agents use experience through external retrieval and parameter learning. Consolidating stored experience into model weights requires deciding both which…
arXiv:2610.35318v4 Announce Type: replace Abstract: Large-scale industrial ranking models must jointly capture heterogeneous feature interactions, long-term user behaviors, and multi-scenario dependencies under…
arXiv:2611.08935v1 Announce Type: new Abstract: Reliable dermatology AI requires access to verifiable evidence distributed across heterogeneous textual and visual sources. However, conventional retrieval-augmented…
arXiv:2501.08686v2 Announce Type: replace-cross Abstract: Traditional similarity-based schema matching methods fail to resolve semantic ambiguities and conflicts in complex, domain-specific mappings due to a lack of…
arXiv:2611.09728v1 Announce Type: new Abstract: Recommendation systems often enter a new serving window before enough outcomes are available to retrain the deployed model. We study this regime with 0.05-1.0% target…
arXiv:2607.00768v2 Announce Type: replace-cross Abstract: Filtered vector search returns the nearest neighbors among the vectors that pass a predicate. The predicate is often selective: most tag queries of the Big ANN…
arXiv:2611.09040v1 Announce Type: new Abstract: Multi-vector retrieval represents each query and document as a set of embeddings and scores relevance via fine-grained set-to-set interactions such as MaxSim (Chamfer…
arXiv:2611.09680v1 Announce Type: new Abstract: Learned sparse embeddings are a powerful alternative to dense retrieval, yet they have fallen behind single-vector and late interaction models. One reason for their…
arXiv:2605.24297v3 Announce Type: replace Abstract: Two questions regarding practitioners' use of patent embeddings arise: (i) Does one fine-tuning recipe suffice for all downstream applications? (ii) Is fine-tuning on…
arXiv:2611.09126v1 Announce Type: new Abstract: Explainable scholar recommendation aims to identify potential scholars of interest and provide reasonable explanations for the recommendations. However, existing…
arXiv:2611.09006v1 Announce Type: new Abstract: Latent reasoning in generative recommendation faces two practical barriers: constructing teacher-generated chain-of-thought (CoT) supervision is costly, and recurrent…
arXiv:2611.09294v1 Announce Type: new Abstract: Unified search and recommendation systems may update the same item vectors from both interaction streams. We study how repeated updates can increase an item vector's norm…
arXiv:2611.08519v1 Announce Type: new Abstract: Generative recommendation has shown considerable potential in industrial recommendation systems. However, the performance of existing generative methods is limited by…
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