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New benchmark SciToT aids scientific paper retrieval using multimodal cues

By PulseAugur Editorial · [1 sources] ·

Researchers have developed SciToT, a new benchmark and dataset designed to improve the retrieval of scientific papers when users can recall content details but not exact identifiers. This multimodal approach addresses the challenge of finding papers based on incomplete memories of text and visual elements like figures. The dataset includes over 100,000 scientific documents and nearly 12,000 synthetic queries, along with various retrieval baselines, all released under an MIT license to foster further research in this area. AI

IMPACT This benchmark could improve how researchers find and access existing scientific knowledge, potentially accelerating discovery.

RANK_REASON The item describes a new academic paper introducing a benchmark and dataset for a specific research problem. [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 benchmark SciToT aids scientific paper retrieval using multimodal cues

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The item describes a new academic paper introducing a benchmark and dataset for a specific research problem. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Maarten de Rijke ·

    SciToT: Multimodal Tip-of-the-Tongue Retrieval for Scientific Papers

    Researchers frequently encounter difficulties re-finding scientific papers when they remember aspects of the content but cannot recall reliable identifiers, such as titles or author names. This type of re-finding task, known as tip-of-the-tongue (ToT) retrieval, is particularly c…

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