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AutoIndex learns document representation programs to boost retrieval performance

By PulseAugur Editorial · [3 sources] ·

Researchers have introduced AutoIndex, a novel framework designed to learn executable transformations for document representation. This system optimizes document preprocessing before indexing, moving beyond traditional fixed methods. AutoIndex demonstrated significant improvements in retrieval tasks, enhancing recall and nDCG scores across various benchmarks. AI

IMPACT Enhances information retrieval systems by optimizing document representation, potentially improving search accuracy across various applications.

RANK_REASON The cluster contains a research paper detailing a new framework for information retrieval.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

AutoIndex learns document representation programs to boost retrieval performance

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The cluster contains a research paper detailing a new framework for information retrieval.
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COVERAGE [3]

  1. arXiv cs.AI TIER_1 English(EN) · Sam O'Nuallain, Nithya Rajkumar, Ramya Narayanasamy, Hanna Jiang, Shreyas Chaudhari, Andrew Drozdov ·

    AutoIndex: Learning Representation Programs for Retrieval

    arXiv:2607.18603v1 Announce Type: cross Abstract: We present AutoIndex, a framework for learning representation programs: executable transformations that map raw documents into the representations exposed to a retrieval system. Rather than tuning retrievers, rerankers, or a small…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Andrew Drozdov ·

    AutoIndex: Learning Representation Programs for Retrieval

    We present AutoIndex, a framework for learning representation programs: executable transformations that map raw documents into the representations exposed to a retrieval system. Rather than tuning retrievers, rerankers, or a small set of preprocessing hyperparameters, AutoIndex s…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    AutoIndex: Learning Representation Programs for Retrieval

    We present AutoIndex, a framework for learning representation programs: executable transformations that map raw documents into the representations exposed to a retrieval system. Rather than tuning retrievers, rerankers, or a small set of preprocessing hyperparameters, AutoIndex s…

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