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New PDMR framework enhances document retrieval with multi-ID approach

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced Passage-Driven Multi-ID Retrieval (PDMR), a new generative retrieval framework that enhances document retrieval by assigning multiple passage-level identifiers to each document. This approach allows models to align queries with specific semantic facets of a document, moving beyond the limitations of single-identifier systems that can lead to lossy representations. PDMR has demonstrated improved performance on benchmark datasets like NQ320K and MS MARCO Document, outperforming existing generative and non-generative methods in recall and mean reciprocal rank. AI

IMPACT This new retrieval method could improve the accuracy and robustness of search systems by better handling multi-faceted documents.

RANK_REASON The cluster contains a research paper detailing a new method for information retrieval. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New PDMR framework enhances document retrieval with multi-ID approach

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The cluster contains a research paper detailing a new method for information retrieval. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 Română(RO) · Mohand Boughanem ·

    PDMR: Passage-Driven Multi-ID Document Retrieval

    Generative Retrieval (GR) models map queries directly to document identifiers, replacing conventional retrieval over external sparse or dense indexes with autoregressive identifier generation. However, most generative retrieval frameworks rely on a single-identifier assumption, m…

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